Final Report Summary - AAPD (Application and Analytics Platform Demonstration)
Executive Summary:
The project AAPD is the follow-up of RAISME, the very successful 'Research for SMEs' project (Grant Agreement number 262469), that came to a successful conclusion on 31st of August 2012. RAISME was aimed at providing a configurable platform for rapid development of software applications, with embedded advanced interactive interfaces and visualisation services, enabled to allow an integration ecology of users, developers and providers. AAPD addresses a very significant opportunity given the rapid global uptake in cloud computing and the EU’s unique infrastructure of SMEs to deliver the RAISME platform and it’s innovative services for all EU SMEs enabling access to more advanced ICT than through usual architectures. This will generate more ‘adventurous’ use of computing, faster progress into new markets incurring less financial risk, and access to advanced concepts requiring high performance or high throughput computing.
AAPD has been focussed on applying the RAISME platform by demonstrating its application in the context of Risk Management. The Risk Management domain is used to customise the capabilities of the platform into a concrete bundle of services; to be achieved by close interaction with an early-evangelist customer. The AAPD demonstrator platform will handle the type of large and diverse datasets (i.e. Big Data) used in risk and insurance analysis.
AAPD represents a step forward for the SMEs and the customer involved in the project. An important outcome is the demonstration of AAPD business viability as a new extendible cloud service platform for the analysis of complex systems in the area of risk management. By testing and verifying the AAPD platform and its services, with the closest involvement of a customer as user, the project has demonstrated advanced tools and applications dealing with complex analysis using specialised visualisation techniques.
The technical outcomes from AAPD are: Continuous application monitoring of the platform usage, including mechanisms to provide direct feedback from the customer and built-in Business Intelligence algorithms to evaluate customer experience in near real-time. Demonstration of a specific application demanding data processing and integration of analytical tools in a highly customisable cloud-based development environment, easily adaptable to user requirements.
The expected impact for DRTS is a 5 year projected valuation of the company at £150M and increased team from 4 to 19 people with project revenue at £1.4M first year with low operating costs. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance for industry and business consultants.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is claimed as a Dashboard Tool that provides security, interactivity, ease of integration and good design.
Project Context and Objectives:
AAPD is focussed on developing for commercial use the RAISME analytics and reporting platform by demonstrating its application in the context of Risk Management. The Risk Management domain is used to customise the capabilities of the platform into a concrete bundle of services; to be achieved by close interaction with an early-evangelist customer. The AAPD demonstrator platform will handle the type of large and diverse datasets (i.e. Big Data) used in risk and insurance analysis.
The AAPD demonstration project is based on the Customer Development Methodology. The methodology has a strong customer focus using demonstration and feedback to understand requirements and then to focus the product to deliver only the needs for the customer or the business. The second phase of the project iterates the Customer Learning and Discovery tasks to develop and evaluate hypotheses about the customer and business needs. Each hypothesis was tested and evaluated through customer interactions (“experiments”).
The main output from this demonstration project is a well researched business plan from each SME showing market readiness.
MAIN OBJECTIVES
GLOBAL 1: To carry out an industrially focused demonstration of the AAPD platform for the analysis and modelling of complex systems for risk analysis.
GLOBAL 2: To evaluate the performance and commercial viability of the AAPD platform by deploying in a real customer environment and through customer feedback in order to gain fundamental input to product features and business models.
GLOBAL 3: To validate the mashup engineering process of workflows, data security, and data provenance strategies within customers’ requirements for high security.
GLOBAL 4: To use the previous project methodology for integration of the specialised customer’s own tools into the AAPD demonstration system.
DEMONSTRATION 1: To Demonstrate in a tangible manner a cloud-based platform for the easy integration of a number of complimentary software tools forming an overall application.
DEMONSTRATION 2: To test and evaluate the AAPD methodology for the preparation and acceptance of new software tools and technology into the cloud-based platform.
DEMONSTRATION 3: To demonstrate the acceptable security, quality audit and usability of the overall application performance for a customised deployment according to customer requirements.
COMMERCIAL 1: To establish a customer voice providing marketing plans, viable business strategies and sustainable commercial operations for the AAPD platform in the main business domain (Risk Analysis), in addition to general horizontal marketing.
COMMERCIAL 2: To evaluate the ecology of prospective AAPD users, and to have suitable delivery, licensing and pricing models to support business growth.
COMMERCIAL 3: To achieve a customised demonstration version of the original platform, transforming the alpha version output from the previous research project by stabilisation of the code, deployment and open service innovation methodologies.
GENERAL EU FOCUS 1: The SMEs wish to gain competitive advantage in the Risk Analysis market and expect that in next years the international corporations will utilise, benefit from and contribute to the capabilities of the resulting system. Thus, through the demonstration activity, they need to validate the demonstration platform once customised for a real customer and deployed on real infrastructure. Future development will be driven by customer experience evaluated from the demonstration activities and metrics recorded within the platform. Project dissemination of results will help ensuring further potential customers to be acquainted of the system achievements, providing significant market traction for the future product commercialisation, and in consequence the growth of the SMEs business dimension.
TECHNICAL CONTENT/SCOPE 1: AAPD will carry out demonstration activities to prove the viability of the available platform resulting from the previous project. After this demonstration phase, the platform and other results will be in a pre-production state, ready to enter into the last phase of market deployment.
TECHNICAL CONTENT/SCOPE 2: AAPD will perform performance and stress testing of the available prototype, studying its behaviour when it is scaled-up, with a huge load, able to deal with large data and also improving this quality in addition to stabilise the platform. In addition to this, the platform will be improved and integrate new custom solutions needed to cover the customer requirements.
TECHNICAL CONTENT/SCOPE 3: A market analysis will be performed in order to understand the needs and trends of the market in the Risk analysis domain, the gaps that AAPD can fill and the existing risks in this process. Additionally, AAPD will define a business plan and strategy to follow in order to achieve SMEs expectations, ensuring the sustainability and impact of the solution in the market.
EXPECTED IMPACT 1: The demonstration of the research results of a previous project (RAISME) will be used to explore market opportunities in a specific domain (risk management) in order to secure its expected impact.
EXPECTED IMPACT 2: AAPD takes further the results from the previous research project and aims to prove the viability of this solution and to ensure its expected impact can be exploited and put into the market in further commercial stages.
EXPECTED IMPACT 3: To demonstrate that the product, now demonstrated in AAPD, will have a valuable economic impact, will create employment and can be commercialized after further adaptations once demonstration project is finished.
EXPECTED IMPACT 4: The AAPD project will ensure that results of the project are properly disseminated among the customer community and for creating links between the participating SMEs and the interested parties, creating a potential market interest.
Project Results:
AAPD is a Demonstration project without S&T objectives, or expected results. The Demonstration results are as follows.
The AAPD project is based on the Customer Development Methodology which aligns to demonstration activity. The methodology uses a customer focus using demonstration and feedback to understand and iterate towards needs and requirements. The discipline required is to focus the product to deliver only needs for the customer or the business. The second phase of the project iterated the Customer Learning and Discovery tasks to develop and evaluate hypotheses about the customer and business needs. Each hypothesis was tested and evaluated through customer interactions or “experiments”.
Of most value has been to build the Customer Development Methodology into the daily business process. This provided experience in understanding customer, market, delivery channels and strategies, including licensing models and services. The Customer Experiments covered a wide range of activities including deployment and monitoring of product features and hypothesis; interviews with users; demonstrations of new product features, prototypes and concepts; and testing marketing information.
The primary goal of the project is the successful delivery of the Business Plan, allowing the SMEs to move forward from AAPD to fully commercialise the products and services. Along with the Business Plan, the Market Strategy and Licensing Models have been developed. The Market Strategy is built on the market and channel surveys, understanding how to deliver the products, what features, ideas and presentation will help with customer retention and customer gain.
The development cycles in the project have provided a robust AAPD Platform, changing the software from research prototype into a near production ready market state. The infrastructure has been enhanced with billing and improved monitoring, scalability and security. Big Data Testing and Stress Testing have helped improve code quality and quantify system performance. Automated testing is now built into the development process ensuring continued robustness for the future product. An important result of the testing has been to update the data importing services, to improve big data handling and automated data type detection.
Additionally the AAPD Platform has prototyped, demonstrated and evaluated several product enhancements to potential customers. The main areas have been collaboration features for cognitive mapping, text analysis for document importing to cognitive maps, and data visualisation dashboard and reporting.
SUMMARY OF PROJECT ACHIEVEMENTS
The following summarises how each project objective has been successfully fulfilled.
[GLOBAL 1: To carry out an industrially focused demonstration of the AAPD platform for the analysis and modelling of complex systems for risk analysis.]
Through hundreds of customer interactions, meetings and tests, using the Customer Development Methodology as a framework, AAPD has transformed the RAISME research platform into a commercially viable and tested concept platform. The demonstration activities were mainly targeted at the risk analysis domain.
[GLOBAL 2: To evaluate the performance and commercial viability of the AAPD platform by deploying in a real customer environment and through customer feedback in order to gain fundamental input to product features and business models.]
The AAPD platform was deployed as a production ready environment that has been used by Milliman as customer representative. This platform has been evaluated against customer and business requirements on a feature-by-feature basis, using iterative develop, tests and evaluate. The evaluation establishes the overall commercial viability of the various solutions and product as a whole. The main project output is the business plan for commercialisation, market development and future product development.
The Stress Testing results proved challenging, but sufficient experience was gained to understand how to deploy the AAPD platform for customers.
[GLOBAL 3: To validate the mashup engineering process of workflows, data security, and data provenance strategies within customers’ requirements for high security.]
Throughout the AAPD project small development changes were made to the product and platform to provide feature updates as part of the Customer Development and Discovery process. The changes were made possible by the scalable and flexible nature of the platform architecture and the ability to integrate new functions within new and existing workflows.
The product domain of Risk Analysis, requires high data security. The platform security was analysed and changes made to protect component connectivity, data integrity and access control. Specific access to user created artefacts on the platform was enhanced, with secure sharing and collaboration.
[GLOBAL 4: To use the previous project methodology for integration of the specialised customer’s own tools into the AAPD demonstration system.]
The AAPD platform implements integration of third party tools through service integration (SOAP or REST) or data service integration, with several database and data messaging systems supported.
Specific integrations achieved include the implementation of Cognitive Maps data importing from customer systems, identified as an opportunity to gain customers with existing Map data.
Additionally the Dashboard project is integrated with Customer systems by defining an API to send data to the dashboard web interface. This interface means only the limited and aggregated data to be displayed is sent via the API, ensuring access to the overall Customer data is secured.
[DEMONSTRATION 1: To Demonstrate in a tangible manner a cloud-based platform for the easy integration of a number of complimentary software tools forming an overall application.]
AAPD successfully took the RAISME platform and by implementing new tools in the Maps application demonstrated the ease of integration.
The new services, such as Annotation, and Text Analysis, required new processing to be implemented to support the user functions. The secure and scalable integration framework made adding new service functions simple.
[DEMONSTRATION 2: To test and evaluate the AAPD methodology for the preparation and acceptance of new software tools and technology into the cloud-based platform.]
The Customer Development methodology was used throughout the project. Experience with the methodology resulted in a good appreciation and an improved process by the end of the project.
The methodology and Customer Development process worked successfully with the scalable and flexible AAPD platform. The process allowed free expression of ideas to be tested with potential customers, either as a presentation, prototype or production ready implementation. The cloud-based platform meant demonstrations could be performed anywhere and scaled-up automatically when product demand increases.
[DEMONSTRATION 3: To demonstrate the acceptable security, quality audit and usability of the overall application performance for a customised deployment according to customer requirements.]
The development within AAPD used the agile development methodology with reviews at specific points of integration and before release to safeguard the quality of the output.
The tasks on Big Data Testing and Stress Testing were used to ensure the platform performance provides a good user experience and responds to changes in demand.
Customers are now using and continually testing the tools.
[COMMERCIAL 1: To establish a customer voice providing marketing plans, viable business strategies and sustainable commercial operations for the AAPD platform in the main business domain (Risk Analysis), in addition to general horizontal marketing.]
The Customer Development Methodology included activities for Customer Learning and Discovery, and Customer Validation. These activities drove the product demonstrations, with new features and prototype new product components.
The demonstrations provided an opinion of how valuable and useable each product feature is to the customer. As a whole the analysis of Customer Experiments has been used to develop business and marketing plans, with billing and licensing models.
The overriding commercial output is the Business Plan, which covers the full market evaluation, product positions and product development options. The Business Plan is not static, because the Customer Development Methodology will continue to be used and allow the company and product to change to meet customer needs.
[COMMERCIAL 2: To evaluate the ecology of prospective AAPD users, and to have suitable delivery, licensing and pricing models to support business growth.]
The Customer Validation tasks analysed the customer market across the different product offerings in the AAPD platform. This revealed the different market channel strategies for sales and delivery, which is detailed in the Positioning and Channel Report, and focused in the Business Plan.
An exploitation and IPR study detailing sustainability models and licensing, pricing models has also been reported.
[COMMERCIAL 3: To achieve a customised demonstration version of the original platform, transforming the alpha version output from the previous research project by stabilisation of the code, deployment and open service innovation methodologies.]
The development tasks in AAPD concentrated on improving code quality and moving from the research platform to a production ready platform. This development also needed to support the enhancements to demonstrate to potential customers.
A Continuous Integration server was deployed to execute unit tests on the services and front-end code. These tests were also exercised in the tasks for Big Data Tests and Stress Tests. Therefore ensuring the code is robust and scalable.
Significant effort was spent on code restructuring, however this effort was concentrated in areas where enhancement or bug fixing was considered.
The final output is a beta version of the Platform with several new features and more reliable functions from the original research prototype.
[GENERAL EU FOCUS 1: The SMEs wish to gain competitive advantage in the Risk Analysis market and expect that in next years the international corporations will utilise, benefit from and contribute to the capabilities of the resulting system. Thus, through the demonstration activity, they need to validate the demonstration platform once customised for a real customer and deployed on real infrastructure. Future development will be driven by customer experience evaluated from the demonstration activities and metrics recorded within the platform. Project dissemination of results will help ensuring further potential customers to be acquainted of the system achievements, providing significant market traction for the future product commercialisation, and in consequence the growth of the SMEs business dimension.]
The SMEs needed to prove that product features are valuable enough to the customer to provide a viable business model, and this has been achieved. One example of this is the product features added to Maps have proved useful to the customer representative. This product has been chosen to replace the previously used tool, because it provides easy access and is more presentable to their customers.
Milliman: “We obtained a more coherent analysis platform that clients have found engaging and useful in their consideration of complex problems. The Maps tool represented a significant improvement over previous tools and has facilitated better client engagement and understanding. The opportunities presented by the Network and Analysis functions are interesting as clients struggle to properly make sense of multivariate data. These have led to the interesting concept of a dashboard which can be used to monitor company performance in a more appropriate way.”
[TECHNICAL CONTENT/SCOPE 1: AAPD will carry out demonstration activities to prove the viability of the available platform resulting from the previous project. After this demonstration phase, the platform and other results will be in a pre-production state, ready to enter into the last phase of market deployment.]
As used in AAPD, the Customer Development Methodology focussed on demonstration and evaluation of the product, to support any enhancements developed during the project.
During development of enhancements code quality was improved by restructuring the code where changes where made. Continuous Integration testing supported the development to ensure the robustness of the platform is ready to deploy the product in the market.
[TECHNICAL CONTENT/SCOPE 2: AAPD will perform performance and stress testing of the available prototype, studying its behaviour when it is scaled-up, with a huge load, able to deal with large data and also improving this quality in addition to stabilise the platform. In addition to this, the platform will be improved and integrate new custom solutions needed to cover the customer requirements.]
The AAPD program included a variety of testing, using Big Data tests to exercise the capacity of the system to process data, the Stress Testing to exercise the multi user capability and product feature testing with Customer representatives to validate implementations or prototypes. Additionally, customer validation was performed on the non-technical solutions such as help pages and support solutions.
[TECHNICAL CONTENT/SCOPE 3: A market analysis will be performed in order to understand the needs and trends of the market in the Risk analysis domain, the gaps that AAPD can fill and the existing risks in this process. Additionally, AAPD will define a business plan and strategy to follow in order to achieve SMEs expectations, ensuring the sustainability and impact of the solution in the market.]
A market analysis was performed in the Customer Validation tasks. This studied the competitors across different products that are covered by AAPD, including competitors to Data Analysis, Dashboards and Reporting and Cognitive Mapping. The results are reported in the Business Plan.
MAIN PROJECT RESULTS
The project work was divided into tasks. The output from the tasks is described below.
Platform Testing Tasks
The Big Data Tests consisted of the following activities:
• Build a testing framework to run validation tests on services, using Jenkins
• Implement a suite of tests, using JUnit
• Detect and fix bugs in services
Jenkins Continuous Integration server was installed to run the tests. Additionally, a testing framework was written to run tests with a list of inputs and a list of correct outputs. Each service now has a service to exercise it with a variation of input datasets and outputs. This allows testing datasets with different number of rows and columns, different data types and different errors in the data (for example missing values, bad data types, out of range values).
Building the framework took longer than expected with issues running tests against different large datasets and the time taken to run the full suite when testing the automated execution. Despite the delays, performance issues in memory size and processing time were detected in a few services. Each of these we traced to the shared code in the function ‘putFile’ which is used to detect data type and store the resulting data and metadata. The function was refactored to improve performance, but requires further attention to reduce memory consumption for large data.
The Stress Testing task was completed with difficulties and much extra effort. The tasks aimed to test the platform under the load of multiple concurrent users. In particular, to exercise the analysis calculations and test the scalability of the platform and help determine cost efficient and effective response times for the application.
Since the testing work had concentrated on the Big Data testing framework there was less time available for the Stress Testing. However, the foundation for the Big Data testing has provided the test suite for Stress Testing. The testing framework design means it can be extended with new larger datasets without rewriting the tests. The testing framework did require extending for parallel execution to simulate multiple users. From the Jenkins server, multiple service requests are launched to test the system response, how it scales to maintain availability and robustness.
To facilities the Stress Testing, the scalability of the platform needed to be tested. However, the implementation from the RAISME project used WSO2 Stratos 1.6 as a single machine installation. This needed to be upgraded and effort was made ensure services could be scaled be separating concerns. For the platform, this required updated Stratos to the latest version. During the project Stratos 3.0 was released and effort was made to update the platform. However, towards the end of the project Stratos 4.0 was also released and became supported by WSO2, with the Application, Data, ESB Servers all provided. Subsequently, further effort was used to make the platform use WSO2 Stratos 4.0. This now made the platform:
• Scalable, with dynamic servers
• Able to execute on Amazon EC2 or Openstack (on Rackspace for example),
• Uses Docker to automatically create and deploy servers
• Support high availability, redundant application servers and data servers.
WSO2 Stratos 4.0 update, installation instructions, Amazon EC2.
This task did not produce the Stress Testing results, and therefore platform costs and scaling requirements have been estimated for the Business Plan. However, the result has produced a scalable testing environment using the Big Data tests in a parallel execution framework, using Jenkins to manage the testing processes.
Platform & Service Enhancements
This task involved improving the robustness of the platform, its architecture and code structure. Additionally, the enhancements to functionality make it more marketable. Notably the activities to re architect the code to allow different product to be enabled or disabled. Turning products on and off supports different billing models for the DACORD components, such as paying a premium for Analysis. Also, the restructuring supported the effort to release a different portal StratView connected to the same background.
Additionally, when restructuring code the Analysis component should be able to load multiple datasets as individual systems, enabling the user to compare the behaviour of different systems. Multiple system support in Analysis was integrated late, and the architecture did not fully exploit the backbone.js framework, therefore changes to time point, system selection and variable selection did not always propagate throughout the tool.
The enhancements to the platform include improvements to the service architecture by separating the service between the Datasets, Analysis and Maps components; enhancing the scalability, to enable independence of service processing and state storage and making it compatible across Amazon AWS and OpenStack infrastructure (such as RackSpace); and, Code structuring, improving the architecture to reduce duplicate code and consolidate shared libraries.
The Maps component for cognitive collaborative mapping had many platform level enhancements including Backup and Restore, to allow users to download an archive of their maps and restore the archive later; updating the listing of Maps, allowing the user to sort and find Maps from a long list, Text Analysis service deployed in Python.
The Datasets component for importing and cleaning data ready for visualisation and analysis was improved by fixing platform services to cope with larger data and improved the automatic data type detection. Many data importing functions were simplified during the restructuring of code.
The Analysis component calculates the system stability and connectivity of variables within a system. This was updated mainly by restructuring code to make better use of the backbone.js framework and improving the loading and handling of multiple datasets with Analysis to support comparing system behaviour. The loading speed was improved through better use of asynchronous data loading and error handling, also fixed issues in data navigation, improved time point selection and synchronisation of graphs. Additionally exporting a Network Graph from the Analysis component to DACORD Maps enabled linking of tool sets so the network analysis algorithms could be made available with the Maps interface.
Portal Strategy and Development
The portal user interface and functionality was improved, since through Customer Discovery it was shown the usability and presentation made a significant impact on attracting new customers. The features chosen to implement in the portal are the result of the iterative customer development iterative process.
The strategic development tested new product ideas by prototyping interfaces and basic functionality. These were presented as demonstrations or working prototypes for evaluation by potential customers. A network visualisation and exploration tool was prototyped. This allowed the user to import a network from file and visualise using calculated network analysis functions. The interface allows the user to explore a large network applying filtering, layouts and colours according different calculated characteristics.
Additionally a Dashboard prototype was developed and demonstrated. This connects to the AAPD platform to provide easy collaborative access to the stored data. It has been developed to be simple to integrate into data environments with a good design and range of display widgets. The dashboard visualisation is agnostic in relation to the customer's system and architecture since the API implementation resides on customer's premises. Data to be displayed can be easily aggregated from multiple sources and supports interactive for drill down and multi variate exploration of business performance data.
The updates to the Portal are across all the components within the AAPD platform. The developed features for the Maps component include Annotation and Sharing view only Maps with ‘free’ users for improved Collaboration; rapid linking and merging to support larger maps; Text importing for faster map creation from documents or interview transcripts.
The Maps component was also launched as a separate product called StratView. The StratView offering is a Maps only version of the Portal, linked to the same backend. The portal uses different styling and logo to attract a different type of customer to a simpler cognitive mapping product.
The Datasets importing feature was improved with faster access to data cleaning tool. The Analysis component visualising system behaviour was improved with multiple systems handling and graphing, and better error handling to improve the robustness in the portal.
Overall the look and feel of the portal was improved with a new landing page to direct users into the application, new user invitation functions with example datasets and cognitive maps, integration of a Help Desk with support interface and instructional videos, and overall the portal styling was improved.
Develop Customer Experiments
Hypotheses about features, services, marketing and support were developed. Each hypothesis was sourced from Customer needs, through discussion or other communication with customers or customer representatives Milliman; Business needs, required platform enhancements for recording activity through usage monitoring and logging; Bug fixes and optimisation, where features and functions are not working as designed or not providing sufficient performance for customer usage testing; Platform enhancements, where the underlying platform is updated and extended to make the platform more robust.
Each hypothesis was tested and evaluated through customer experiments were designed to learn from about customer and their needs. Specifically, testing how accurate the hypothesis is about the customers needs.
The aspects learnt about the customer domain included:
• Information gathering, through interviewing domain experts from different groups in the organisation;
• Collaboration, group discussions to build shared knowledge
• Reviewing, to discuss the results with the groups and expand, refine or correct the information
• Annotation and change records, commenting on and within the information and recording a history of changes to aid collaboration and review
• Presentation of information is important and different formats need to be use for different audiences, hence the development of product ranges, Analysis, with detailed graphs; Maps, with Annotations; Dashboard, with a range of simple graphs; Network Tool, the filtering and layouts; and Reporting, with commentary and printable output
Within the development of the experiments, the specific types of record keeping were designed for each feature.
Recording methods used included:
• User logs from web portal and service invocations
• Specific records of data sizes stored (analysis of data store)
• Specific records of how many new features had been used (extended logging)
• Interviews with users
• Feedback on demonstrations, specifically with prototypes, wireframes and presentation of concepts
Perform Customer Experiments
The iterative approach to Customer Development resulted in significant to develop and run experiments on the ‘production’ deployment platform after internal testing on the development platform. Prototypes were deployed on either development platform or the production platform for external testing. However, since the development platform was subject to change and the production environment was strictly controlled, results could only be guaranteed on production, unless specific agreement was in place for evaluation of prototype functionality.
The Customer Experiments covered a wide range of activities including:
• Deployment and monitoring of product features and hypothesis
• Interviews with users after deployment
• Demonstrations of new product features deployed in platform
• Demonstrations of new prototypes deployed on development platform or local machine
• Demonstrations of concepts using wireframe design, or PowerPoint presentations
• Marketing brochure for World IT Show, Busan, Korea as part of UK delegation.
The demonstration of prototypes did not always lead to demonstration of product. For example, the Network Tool and Multi-variate complex Dashboard were running prototypes demonstrated to potential customers, but not deployed for customer use. Additionally, some hypothesis on new features were discussed during demonstrations, interviews and other informal discussions, these included:
• Reporting Dashboard, with commentary and printable;
• Offline working for the Maps application (editing is currently only available online).
Analyse Customer Experiments
Analysis of the customer experiments was performed at the end of each iteration. The results of feature usage data and the feedback from prototypes and demonstrations were analysed for their relative merit. Each result was analysed according to how well it meets or could meet the needs of the customer and the business.
The criteria used to judge each hypothesis/feature is:
• Business Development, how the business can grow and gain revenue from the products and features offered. And how to maintain the customer development process to review and evaluate customer experience.
• Market Development, how to understand the customer needs and how to demonstrate that the product features fulfil their needs. How to gain new customers and retain existing customers.
• Technical Development, product enhancements, and bug fixes that fulfil the customer functionality needs, or fulfil business needs in administration or marketing.
The report on Customer Experiments summarises the options about future development of the features analysed, based on the results of customer usage, internal testing, interviews and demonstrations. This summary suggests the priority is marketing activities for the output of AAPD to promote the product and further development of the collaborative features to enable and encourage more users. The output of this task was used in developing the Business Plan and Market Strategy.
Pivot or Proceed Checklist
The pivot or proceed task in the customer development methodology marks the decision point of each iteration on whether to continue with new experiments or repeat the previous experiment with a variation in product, concept or customer audience.
During this activity the experimental results and analysis for each hypothesis were discussed. The individual merits were judged by criteria of potential to increase customers, retain customers or keep DACORD ahead of the competition and how much effort it takes to transform the initial idea to prototype and then to product.
This task identified which changes were developed into product, which were developed into prototypes, which changes were presented as concepts and which we deemed to be completed or of no current value to the customer or business.
During this activity the domains for the product were identified as Risk Management; SODA, Knowledge capture and analysis; Data and Connectivity Analysis; Data Presentation using graphs, dashboard, reporting; Analysis as a service (with reporting); and for the two Business models: Platform as a Service (PaaS) and Software as a Service (SaaS).
Iterate Commercial Service, Product and User Definition
This task identified the product enablers for new and continued business as:
• Collaboration, supporting and encouraging many concurrent users to share, discuss and review data, analysis, results:
• Resulted in the design of 3 types of Annotation features with Maps. 1 type was fully implemented within the product;
• Sharing was enhanced with adding share users and messaging from inside Maps;
• New Reviewer (read only) user was added to enable Maps collaboration without adding a full license, enabling collaboration and extending the license model.
• Analysing multiple systems, to compare and grade performance:
• Fixing and enhancing multiple systems in Analysis.
• Help & Support, using Video examples and Support Desk
• Easy access to share final results, using Dashboard and Reporting
Other options where investigated but did not prove to be currently valuable to the customer. These options included:
• Analysis service, providing reports on data analysis
• Platform for data and analysis processing, scalable and highly available, using open source technology
• Tablet version of the analysis platform
• Offline editing for Maps
• Real-time collaboration on Map editing
• Network Tool: Import and Navigate large network online.
• Maps only product to make it easier to sell (launched as StratView).
Develop Positioning & Channel Hypothesis
This task has been carried out by DRTS together with Milliman. The goal is to find the customer and the path to achieving a repeatable sale. Sales costs must be less than the lifetime payments of that customer to have a viable business.
AAPD started with a number of hypothesis about the customer, segments, and channels, and throughout this second project period, there has been an ongoing process of identifying uncertainties then devising experiments and then finding out how to remove or change the focus of these unknowns.
The success of this particular task is proved by all partners having developed, explored and championed different vies of “the customer”, and how to reach them. DRTS has chosen to view Milliman, and consultants like them, as the customer, requiring a performance management service, whereas Visup have focused on data driven SME’s and a Dashboard service. The success with Milliman has been to test hypothesis and then reflect back to them their own findings, leading to further hypothesis and tests for clarification. These clarifications and reflections help both parties, not only shaping the idea of how to reach the customer but in the Milliman case it changes Milliman’s view of their own needs. For example Milliman have an increased realisation of the power of data and analytics, as evidenced by their website advertising.
Positioning and Channel Testing
Making a guess on the product and customer and how to get them, and then never checking again until the new product is in place, is quite clearly in most cases madness. This task is about the continual testing and checking that the product/service guesses are right, and then changing designs and strategies to suit the new findings.
Testing has been carried out by simple website searches, product trials, interviews, by monitoring use, monitoring competitors, talking to focus groups, talking to competitors and by offering different versions of the same product accessed in different ways. Each SME has moved from assumptions about the market to being able to develop viable business plans.
Develop and Validate Business Model
In this task each SME and Milliman has learnt firstly the importance and opportunity of thinking in Business Model terms. Thereafter ongoing engineering and dynamics of complex business elements have been trialled and re-trialled in thought experiments and in other forms of more realistic testing. This task has succeeded in moving the chances of business success for each SME times ten compared to the pre-AAPD starting position.
Develop and Validate Financial Model
The Financial Model has been developed and improved by the holistic customer development methodology used throughout the project. The success of the financial model is best gauged by the participating market readiness pre- and post-AAPD. There has been a dramatic shift in market readiness, due to market analysis and not due to more technology. This task involved the study of pricing of competitors, trialling software with customers and discussing pricing. Pre-AAPD is guessing hoping, post-AAPD is to know what people will pay for, why, how much they’ll pay, and how they like to pay. The resultant financial model and business plan provides a firm basis to market the AAPD platform, generating sales and revenue.
Deploy Traffic Strategy & Monitor Metrics
The monitoring of the application usage was implemented using a combination of different monitoring and analytics. The metrics and analytics were developed and configured to measure the phases of customer development.
The prime monitoring is built into the Platform with selected event logs recorded from user activity in the portal and service activity in the backend processing. Additional monitoring was used to analyse user entering and exiting the platform, new customer visits and behaviour. The metrics for this activity was implemented using Google Analytics, Freshdesk activity logs (from the Help and Support platform) and additional metrics implemented to analysis feature usage within the AAPD Platform. The tools and metrics are integrated into the product and product development process as part of customer validation.
Develop and Use Sales & Marketing Materials
The sales and marketing material has been developed to demonstrate the product features, educate the customer and excite them to learn about how the product can help them. The AAPD Platform is an online tool, therefore the prime marketing medium are the websites. The project website (www.aapd.eu) was used to provide information about AAPD, its goals and progress. The project partners maintained their website during the project, linking to AAPD project website and updating their own marketing as a result of project and product progress (www.drts.co.uk and www.visup.it).
The main development was the AAPD platform (www.dacord.co.uk). The landing page was significantly improved and different sign up and login strategies were tested to gain new customers. An alternative branding of a simpler version was launched as StratView (www.stratview.net) and limited to Maps only component. Additionally, a new style of user invitation were prototyped to test rapid sign up of users and promote the application functionality by giving new users example datasets and maps. A special version of the user invitation page was launched for the IT Show 2014 in Busan, Korea. The special invitation page includes links to the training and support videos that introduce the product features.
Product Training & Support
Training and Support has been implemented in FreshDesk and links directly to and from the AAPD Platform. FreshDesk hosts the instructional pages written to help with product features and the product videos made to introduce and educate users about new features that are available and how they are used. The support desk also allows customer to make direct queries about product features and issues. Customer questions and answers given by Support can easily be added to help customers with the same problem.
Demonstration activities as part of customer learning also provided support and training to users by educating them about new features or supporting them to better use existing features.
The activities in customer support also contributed to Customer Learning. This leads to understanding about common or uncommon issues that users have with the platform, also the ways in which customer use the platform or need to use the platform.
IPR Exploitation & Agreements
The good understanding of the market place and competition was gained by the IPR audit and tracking of foreground, background and external IP through out the project. The IPR exploitation and agreements were developed along side the Business Plan.
One outcome has been to understand how important the moving target of privacy is. This feeds directly into the development of dashboards and big data processing, and the use of technologies to protect services and data access.
The Business Plan and IPR Agreement from the project sets out clear paths to commercialise the AAPD Platform outputs. A key outcome has been to understand how important the moving target of privacy is. This feeds directly into the development of dashboards and big data processing, and the use of technologies to protect services and data access.
Potential Impact:
KEY IMPACT
[EXPECTED IMPACT 1: The demonstration of the research results of a previous project (RAISME) will be used to explore market opportunities in a specific domain (risk management) in order to secure its expected impact.]
Over the course of AAPD the prototype output from the previous project RAISME has been transformed through a process of code restructuring and feature enhancement. For example, the Maps component has been changed from a prototype to a fully working collaborative cognitive mapping product that supports Risk Analysis and is now being aimed at being used in Financial Risk analysis to meet recent changes in the regulatory process.
[EXPECTED IMPACT 2: AAPD takes further the results from the previous research project and aims to prove the viability of this solution and to ensure its expected impact can be exploited and put into the market in further commercial stages.]
The AAPD platform is the development of the RAISME project platform. It has been enhanced to fully support scalable services on cloud infrastructure. The product is an innovative approach to data analysis using a holistic systems approach to understand organisational behaviour and relative business performance. The AAPD platform integrates the Systems Analysis algorithms with intelligent data importing and improves the already established advanced visualisation services, and has been evaluated with potential customers as a valuable and viable tool to analyse any type of organisational data or otherwise.
[EXPECTED IMPACT 3: To demonstrate that the product, now demonstrated in AAPD, will have a valuable economic impact, will create employment and can be commercialized after further adaptations once demonstration project is finished.]
The expected impact for DRTS is: 5 year projected valuation of the company at £150M and increase the team from 4 to 19 people. With project revenue at £1.4M first year with low operating costs. Costs mostly being attributed to wages. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance to be marketed to business consultants worldwide.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is a Dashboard Tool that provides security, interactivity, ease of integration and good design.
[EXPECTED IMPACT 4: The AAPD project will ensure that results of the project are properly disseminated among the customer community and for creating links between the participating SMEs and the interested parties, creating a potential market interest.]
The dissemination activity of the project output has been an essential component of the project. Dissemination included running demonstrations and tutorials of prototypes and implemented product features to establish their value in the market. Opportunities to discuss and present (many hundreds of 3rd party interactions) the project output have been beneficial to explore and validate the customer domains. A brand identify has been achieved and a chain of interested users and providers of services.
SUMMARY OF IMPACT
AAPD represents a step forward for the SMEs and the customer involved in the project. An important outcome is the demonstration of AAPD business viability as a new extendible cloud service platform for the analysis of complex systems in the area of risk management. By testing and verifying the AAPD platform and its services, with the close involvement of a key customer as user, the project has demonstrated its progress beyond the state-of-the-art both for the targeted domain and in technological terms. The activity has provided important enhancements in financial risk analysis: Risk as one feature of emergent behaviour from complex adaptive systems; and, Risks seen as connected and changing over time. Modelling and optimisation software for risk analysis, has been integrated in a configurable chain of tools to deterministically build models using connectivity and uncertainty from data without imposed assumptions.
The AAPD results represent a relevant technological advance beyond the state of the art, allowing the participating SMEs to position themselves in the forefront of advanced tools and applications dealing with complex predictive analysis with specialised visualisation techniques. Each participant providing its expertise in a concrete application area has allowed for successfully achieving ambitious collaborative goals, where the adoption of an open service innovation approach enables new business services offerings.
Many R&D projects face serious difficulties when it comes to prototyping a demonstration. AAPD goes a step further and tests the feasibility of its integrated platform into a demonstration exercise whose objective is to validate the viability of the proposed system and the advantages it provides in terms of applicability, adaptability and performance in comparison with other similar, although not fully comparable, frameworks. The technical outcomes from AAPD are: Continuous application monitoring of the platform usage, including mechanisms to provide direct feedback from the customer and built-in Business Intelligence algorithms to evaluate customer experience in near real-time. Demonstration of a specific application demanding data processing and integration of analytical tools in a highly customisable cloud-based development environment, easily adaptable to user requirements.
The expected impact for DRTS is a 5 year projected valuation of the company at £150M and increased team from 4 to 19 people with project revenue at £1.4M first year with low operating costs. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance for Milliman and their 55,000 consultants.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is claimed as a Dashboard Tool that provides security, interactivity, ease of integration and good design.
DRTS’s DACORD using the updated and improved RAISME platform resulting from AAPD, provides a much needed paradigm shift, providing end-to-end problem exploration to solution. The simple to use and time saving services offer advanced visual analysis, embrace complexity and uncertainty, answer questions about critical risks and provide decision support for business performance and planning. DACORD is a new generation business platform fit for the age of big data connectedness and people-centred systems.
This new service will deliver novel services to enable radical re-engineering of businesses and their performance, address Complexity-based Risk Analysis, and also will be adapted to manage other categories of complex adaptive systems such as Smart Cities. This will bring about disruptive change by showing where uncertainties lie in businesses and systems, and show how these uncertainties are connected, and also how they affect business performance, then advise what is best to change. Knowing which areas need attention and how to adjust them will improve business performance significantly and enable operational savings of high financial worth. This will at the same time deliver against visible objectives from inherently more resilient business structures.
As the result of a long gestation of experience, inspiration, research, industry collaboration and entrepreneurial vision. The technology platform will leverage world-class fundamental research, already successfully trailed in other domains and prototyped in the previous EU-FP7 projects RAISME and now AAPD. These projects have delivered dynamic cloud services, management of complex systems, big data analytics, visualisation services, management of risk and network steering; also a well-evidenced business proposition for high commercial growth. The RAISME and AAPD results, supplemented with IPR owned and developed by DRTS, will galvanise a long-standing industrial relationship with Milliman, one of the worlds largest and respected actuarial consulting firms, to achieve early market trials, focused market demonstrations and market replication. This will be first through Milliman’s ten European offices, then worldwide through their 55 international offices. Leading to wider world use of these ideas and tools.
The technology is software-based and cannot be easily patented in Europe, although there are proprietary algorithms and business processes potentially patentable for the US market. However, product lifecycles are quite short in the business areas of focus. Product leadership will therefore be maintained mainly via ongoing investment in new product and service development and by maintaining strategic advantage through channel partnerships, agile and robust processes, and by staying aligned to other companies processes (e.g. Milliman). Key founders are engaged by contract to remain in the business for the next 5 years at least. Access to their know-how and their commitment to the business development are therefore fully secured. This ongoing investment and research will draw in other EU organisations and Universities and the revenue from sales will be recycled to the benefit of other EU communities providing a global lead in this area.
The current software product line includes four different modules collectively known as DACORD™. The first module, DACORD™ Maps enables soft start analysis of complex business situations, DACORD™ Data, is aimed at big data access and curation. The third module, DACORD™ Analysis performs multivariate investigation, insight and prediction. The fourth module DACORD™ Network harnesses network visualisation and insight techniques. The fifth module DACORD™ Dashboard enables Board level analysis and reporting. Modularising the software in this way enables multi-axis charging through customer depth of usage. These services are likely, with further investment, to set a global benchmark, which will demonstrate Europe at the centre of these types of service.
Visup’s use of the AAPD Dashboard Tool will enable users to easily configure dashboards and will allow advanced possibilities beyond pure data analysis. In particular, AAPD Dashboard Tool will allow efficient data discovery possibilities and create benefit from real-time market intelligence that empowers:
SMEs analytics: by providing a visual analytics solution empowering SMEs to perform analyses more rapidly compared to conventional methods, such as excel spreadsheets, and to quickly and easily select and isolate important data from noise;
SME’s decision making: this solution will definitely permit users to gain significant value from big data by extracting relevant data, by processing, organising and analysing them, and finally by presenting them through intuitive and clear reports, allowing the user to easily understand and act upon the findings.
Consequently, SMEs will benefit also by an improvement of their business performance due to the possibility to better understand their data and the ability to make more relevant and timely decisions, gaining substantial competitive advantages compared to their competitors.
In turn, such advantages results in:
Increased revenues: through new insights provided by the use of an analytics and decision making solutions, more informed decisions can lead to increased revenues by targeting better identified consumers and/or needs;
Reduced costs: key insights emerging from data analysis can produce, in particular, cost savings, including amongst other better promotional targeting, more efficient use of capital and resources, reduced maintenance costs, etc...
DISSEMINATION ACTIVITIES
With the context on the AAPD Demonstration Project, Dissemination translates to the Customer Development Methodology and Process, with demonstration, experimentation, and sales with marketing activity. Video case studies and other similar material is part of the customer acquisition process and supports product/service credibility and building trust.
The dissemination events have been meetings and workshops (hundreds of events) specifically to demonstrate or promote the project prototype product (the demonstrators) or when the project objectives have been presented and discussed. The demonstration activities have been used to obtain feedback on the prototypes from potential users and customers. The presentations of the objectives have been to invite users to join the demonstration activities and get involved in the customer experiments.
Develop and Use Sales & Marketing Materials
The sales and marketing material has been developed to demonstrate the product features, educate the customer and excite them to learn about how the product can help them. The AAPD Platform is an online tool, therefore the prime marketing medium are the websites. The project website (www.aapd.eu) was used to provide information about AAPD, its goals and progress. The project partners maintained their website during the project, linking to AAPD project website and updating their own marketing as a result of project and product progress (www.drts.co.uk and www.visup.it).
The main development was the AAPD platform (www.dacord.co.uk). The landing page was significantly improved and different sign up and login strategies were tested to gain new customers. An alternative branding of a simpler version was launched as StratView (www.stratview.net) and limited to Maps only component. Additionally, a new style of user invitation were prototyped to test rapid sign up of users and promote the application functionality by giving new users example datasets and maps. A special version of the user invitation page was launched for the IT Show 2014 in Busan, Korea. The special invitation page includes links to the training and support videos that introduce the product features.
Product Training & Support
Training and Support has been implemented in FreshDesk and links directly to and from the AAPD Platform. FreshDesk hosts the instructional pages written to help with product features and the product videos made to introduce and educate users about new features that are available and how they are used. The support desk also allows customer to make direct queries about product features and issues. Customer questions and answers given by Support can easily be added to help customers with the same problem.
Demonstration activities as part of customer learning also provided support and training to users by educating them about new features or supporting them to better use existing features.
The activities in customer support also contributed to Customer Learning. This leads to understanding about common or uncommon issues that users have with the platform, also the ways in which customer use the platform or need to use the platform.
List of Websites:
www.aapd.eu
Jeff Allan, CEO
86 Westbourne Rd,
Sheffield
S10 2QT
UK
The project AAPD is the follow-up of RAISME, the very successful 'Research for SMEs' project (Grant Agreement number 262469), that came to a successful conclusion on 31st of August 2012. RAISME was aimed at providing a configurable platform for rapid development of software applications, with embedded advanced interactive interfaces and visualisation services, enabled to allow an integration ecology of users, developers and providers. AAPD addresses a very significant opportunity given the rapid global uptake in cloud computing and the EU’s unique infrastructure of SMEs to deliver the RAISME platform and it’s innovative services for all EU SMEs enabling access to more advanced ICT than through usual architectures. This will generate more ‘adventurous’ use of computing, faster progress into new markets incurring less financial risk, and access to advanced concepts requiring high performance or high throughput computing.
AAPD has been focussed on applying the RAISME platform by demonstrating its application in the context of Risk Management. The Risk Management domain is used to customise the capabilities of the platform into a concrete bundle of services; to be achieved by close interaction with an early-evangelist customer. The AAPD demonstrator platform will handle the type of large and diverse datasets (i.e. Big Data) used in risk and insurance analysis.
AAPD represents a step forward for the SMEs and the customer involved in the project. An important outcome is the demonstration of AAPD business viability as a new extendible cloud service platform for the analysis of complex systems in the area of risk management. By testing and verifying the AAPD platform and its services, with the closest involvement of a customer as user, the project has demonstrated advanced tools and applications dealing with complex analysis using specialised visualisation techniques.
The technical outcomes from AAPD are: Continuous application monitoring of the platform usage, including mechanisms to provide direct feedback from the customer and built-in Business Intelligence algorithms to evaluate customer experience in near real-time. Demonstration of a specific application demanding data processing and integration of analytical tools in a highly customisable cloud-based development environment, easily adaptable to user requirements.
The expected impact for DRTS is a 5 year projected valuation of the company at £150M and increased team from 4 to 19 people with project revenue at £1.4M first year with low operating costs. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance for industry and business consultants.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is claimed as a Dashboard Tool that provides security, interactivity, ease of integration and good design.
Project Context and Objectives:
AAPD is focussed on developing for commercial use the RAISME analytics and reporting platform by demonstrating its application in the context of Risk Management. The Risk Management domain is used to customise the capabilities of the platform into a concrete bundle of services; to be achieved by close interaction with an early-evangelist customer. The AAPD demonstrator platform will handle the type of large and diverse datasets (i.e. Big Data) used in risk and insurance analysis.
The AAPD demonstration project is based on the Customer Development Methodology. The methodology has a strong customer focus using demonstration and feedback to understand requirements and then to focus the product to deliver only the needs for the customer or the business. The second phase of the project iterates the Customer Learning and Discovery tasks to develop and evaluate hypotheses about the customer and business needs. Each hypothesis was tested and evaluated through customer interactions (“experiments”).
The main output from this demonstration project is a well researched business plan from each SME showing market readiness.
MAIN OBJECTIVES
GLOBAL 1: To carry out an industrially focused demonstration of the AAPD platform for the analysis and modelling of complex systems for risk analysis.
GLOBAL 2: To evaluate the performance and commercial viability of the AAPD platform by deploying in a real customer environment and through customer feedback in order to gain fundamental input to product features and business models.
GLOBAL 3: To validate the mashup engineering process of workflows, data security, and data provenance strategies within customers’ requirements for high security.
GLOBAL 4: To use the previous project methodology for integration of the specialised customer’s own tools into the AAPD demonstration system.
DEMONSTRATION 1: To Demonstrate in a tangible manner a cloud-based platform for the easy integration of a number of complimentary software tools forming an overall application.
DEMONSTRATION 2: To test and evaluate the AAPD methodology for the preparation and acceptance of new software tools and technology into the cloud-based platform.
DEMONSTRATION 3: To demonstrate the acceptable security, quality audit and usability of the overall application performance for a customised deployment according to customer requirements.
COMMERCIAL 1: To establish a customer voice providing marketing plans, viable business strategies and sustainable commercial operations for the AAPD platform in the main business domain (Risk Analysis), in addition to general horizontal marketing.
COMMERCIAL 2: To evaluate the ecology of prospective AAPD users, and to have suitable delivery, licensing and pricing models to support business growth.
COMMERCIAL 3: To achieve a customised demonstration version of the original platform, transforming the alpha version output from the previous research project by stabilisation of the code, deployment and open service innovation methodologies.
GENERAL EU FOCUS 1: The SMEs wish to gain competitive advantage in the Risk Analysis market and expect that in next years the international corporations will utilise, benefit from and contribute to the capabilities of the resulting system. Thus, through the demonstration activity, they need to validate the demonstration platform once customised for a real customer and deployed on real infrastructure. Future development will be driven by customer experience evaluated from the demonstration activities and metrics recorded within the platform. Project dissemination of results will help ensuring further potential customers to be acquainted of the system achievements, providing significant market traction for the future product commercialisation, and in consequence the growth of the SMEs business dimension.
TECHNICAL CONTENT/SCOPE 1: AAPD will carry out demonstration activities to prove the viability of the available platform resulting from the previous project. After this demonstration phase, the platform and other results will be in a pre-production state, ready to enter into the last phase of market deployment.
TECHNICAL CONTENT/SCOPE 2: AAPD will perform performance and stress testing of the available prototype, studying its behaviour when it is scaled-up, with a huge load, able to deal with large data and also improving this quality in addition to stabilise the platform. In addition to this, the platform will be improved and integrate new custom solutions needed to cover the customer requirements.
TECHNICAL CONTENT/SCOPE 3: A market analysis will be performed in order to understand the needs and trends of the market in the Risk analysis domain, the gaps that AAPD can fill and the existing risks in this process. Additionally, AAPD will define a business plan and strategy to follow in order to achieve SMEs expectations, ensuring the sustainability and impact of the solution in the market.
EXPECTED IMPACT 1: The demonstration of the research results of a previous project (RAISME) will be used to explore market opportunities in a specific domain (risk management) in order to secure its expected impact.
EXPECTED IMPACT 2: AAPD takes further the results from the previous research project and aims to prove the viability of this solution and to ensure its expected impact can be exploited and put into the market in further commercial stages.
EXPECTED IMPACT 3: To demonstrate that the product, now demonstrated in AAPD, will have a valuable economic impact, will create employment and can be commercialized after further adaptations once demonstration project is finished.
EXPECTED IMPACT 4: The AAPD project will ensure that results of the project are properly disseminated among the customer community and for creating links between the participating SMEs and the interested parties, creating a potential market interest.
Project Results:
AAPD is a Demonstration project without S&T objectives, or expected results. The Demonstration results are as follows.
The AAPD project is based on the Customer Development Methodology which aligns to demonstration activity. The methodology uses a customer focus using demonstration and feedback to understand and iterate towards needs and requirements. The discipline required is to focus the product to deliver only needs for the customer or the business. The second phase of the project iterated the Customer Learning and Discovery tasks to develop and evaluate hypotheses about the customer and business needs. Each hypothesis was tested and evaluated through customer interactions or “experiments”.
Of most value has been to build the Customer Development Methodology into the daily business process. This provided experience in understanding customer, market, delivery channels and strategies, including licensing models and services. The Customer Experiments covered a wide range of activities including deployment and monitoring of product features and hypothesis; interviews with users; demonstrations of new product features, prototypes and concepts; and testing marketing information.
The primary goal of the project is the successful delivery of the Business Plan, allowing the SMEs to move forward from AAPD to fully commercialise the products and services. Along with the Business Plan, the Market Strategy and Licensing Models have been developed. The Market Strategy is built on the market and channel surveys, understanding how to deliver the products, what features, ideas and presentation will help with customer retention and customer gain.
The development cycles in the project have provided a robust AAPD Platform, changing the software from research prototype into a near production ready market state. The infrastructure has been enhanced with billing and improved monitoring, scalability and security. Big Data Testing and Stress Testing have helped improve code quality and quantify system performance. Automated testing is now built into the development process ensuring continued robustness for the future product. An important result of the testing has been to update the data importing services, to improve big data handling and automated data type detection.
Additionally the AAPD Platform has prototyped, demonstrated and evaluated several product enhancements to potential customers. The main areas have been collaboration features for cognitive mapping, text analysis for document importing to cognitive maps, and data visualisation dashboard and reporting.
SUMMARY OF PROJECT ACHIEVEMENTS
The following summarises how each project objective has been successfully fulfilled.
[GLOBAL 1: To carry out an industrially focused demonstration of the AAPD platform for the analysis and modelling of complex systems for risk analysis.]
Through hundreds of customer interactions, meetings and tests, using the Customer Development Methodology as a framework, AAPD has transformed the RAISME research platform into a commercially viable and tested concept platform. The demonstration activities were mainly targeted at the risk analysis domain.
[GLOBAL 2: To evaluate the performance and commercial viability of the AAPD platform by deploying in a real customer environment and through customer feedback in order to gain fundamental input to product features and business models.]
The AAPD platform was deployed as a production ready environment that has been used by Milliman as customer representative. This platform has been evaluated against customer and business requirements on a feature-by-feature basis, using iterative develop, tests and evaluate. The evaluation establishes the overall commercial viability of the various solutions and product as a whole. The main project output is the business plan for commercialisation, market development and future product development.
The Stress Testing results proved challenging, but sufficient experience was gained to understand how to deploy the AAPD platform for customers.
[GLOBAL 3: To validate the mashup engineering process of workflows, data security, and data provenance strategies within customers’ requirements for high security.]
Throughout the AAPD project small development changes were made to the product and platform to provide feature updates as part of the Customer Development and Discovery process. The changes were made possible by the scalable and flexible nature of the platform architecture and the ability to integrate new functions within new and existing workflows.
The product domain of Risk Analysis, requires high data security. The platform security was analysed and changes made to protect component connectivity, data integrity and access control. Specific access to user created artefacts on the platform was enhanced, with secure sharing and collaboration.
[GLOBAL 4: To use the previous project methodology for integration of the specialised customer’s own tools into the AAPD demonstration system.]
The AAPD platform implements integration of third party tools through service integration (SOAP or REST) or data service integration, with several database and data messaging systems supported.
Specific integrations achieved include the implementation of Cognitive Maps data importing from customer systems, identified as an opportunity to gain customers with existing Map data.
Additionally the Dashboard project is integrated with Customer systems by defining an API to send data to the dashboard web interface. This interface means only the limited and aggregated data to be displayed is sent via the API, ensuring access to the overall Customer data is secured.
[DEMONSTRATION 1: To Demonstrate in a tangible manner a cloud-based platform for the easy integration of a number of complimentary software tools forming an overall application.]
AAPD successfully took the RAISME platform and by implementing new tools in the Maps application demonstrated the ease of integration.
The new services, such as Annotation, and Text Analysis, required new processing to be implemented to support the user functions. The secure and scalable integration framework made adding new service functions simple.
[DEMONSTRATION 2: To test and evaluate the AAPD methodology for the preparation and acceptance of new software tools and technology into the cloud-based platform.]
The Customer Development methodology was used throughout the project. Experience with the methodology resulted in a good appreciation and an improved process by the end of the project.
The methodology and Customer Development process worked successfully with the scalable and flexible AAPD platform. The process allowed free expression of ideas to be tested with potential customers, either as a presentation, prototype or production ready implementation. The cloud-based platform meant demonstrations could be performed anywhere and scaled-up automatically when product demand increases.
[DEMONSTRATION 3: To demonstrate the acceptable security, quality audit and usability of the overall application performance for a customised deployment according to customer requirements.]
The development within AAPD used the agile development methodology with reviews at specific points of integration and before release to safeguard the quality of the output.
The tasks on Big Data Testing and Stress Testing were used to ensure the platform performance provides a good user experience and responds to changes in demand.
Customers are now using and continually testing the tools.
[COMMERCIAL 1: To establish a customer voice providing marketing plans, viable business strategies and sustainable commercial operations for the AAPD platform in the main business domain (Risk Analysis), in addition to general horizontal marketing.]
The Customer Development Methodology included activities for Customer Learning and Discovery, and Customer Validation. These activities drove the product demonstrations, with new features and prototype new product components.
The demonstrations provided an opinion of how valuable and useable each product feature is to the customer. As a whole the analysis of Customer Experiments has been used to develop business and marketing plans, with billing and licensing models.
The overriding commercial output is the Business Plan, which covers the full market evaluation, product positions and product development options. The Business Plan is not static, because the Customer Development Methodology will continue to be used and allow the company and product to change to meet customer needs.
[COMMERCIAL 2: To evaluate the ecology of prospective AAPD users, and to have suitable delivery, licensing and pricing models to support business growth.]
The Customer Validation tasks analysed the customer market across the different product offerings in the AAPD platform. This revealed the different market channel strategies for sales and delivery, which is detailed in the Positioning and Channel Report, and focused in the Business Plan.
An exploitation and IPR study detailing sustainability models and licensing, pricing models has also been reported.
[COMMERCIAL 3: To achieve a customised demonstration version of the original platform, transforming the alpha version output from the previous research project by stabilisation of the code, deployment and open service innovation methodologies.]
The development tasks in AAPD concentrated on improving code quality and moving from the research platform to a production ready platform. This development also needed to support the enhancements to demonstrate to potential customers.
A Continuous Integration server was deployed to execute unit tests on the services and front-end code. These tests were also exercised in the tasks for Big Data Tests and Stress Tests. Therefore ensuring the code is robust and scalable.
Significant effort was spent on code restructuring, however this effort was concentrated in areas where enhancement or bug fixing was considered.
The final output is a beta version of the Platform with several new features and more reliable functions from the original research prototype.
[GENERAL EU FOCUS 1: The SMEs wish to gain competitive advantage in the Risk Analysis market and expect that in next years the international corporations will utilise, benefit from and contribute to the capabilities of the resulting system. Thus, through the demonstration activity, they need to validate the demonstration platform once customised for a real customer and deployed on real infrastructure. Future development will be driven by customer experience evaluated from the demonstration activities and metrics recorded within the platform. Project dissemination of results will help ensuring further potential customers to be acquainted of the system achievements, providing significant market traction for the future product commercialisation, and in consequence the growth of the SMEs business dimension.]
The SMEs needed to prove that product features are valuable enough to the customer to provide a viable business model, and this has been achieved. One example of this is the product features added to Maps have proved useful to the customer representative. This product has been chosen to replace the previously used tool, because it provides easy access and is more presentable to their customers.
Milliman: “We obtained a more coherent analysis platform that clients have found engaging and useful in their consideration of complex problems. The Maps tool represented a significant improvement over previous tools and has facilitated better client engagement and understanding. The opportunities presented by the Network and Analysis functions are interesting as clients struggle to properly make sense of multivariate data. These have led to the interesting concept of a dashboard which can be used to monitor company performance in a more appropriate way.”
[TECHNICAL CONTENT/SCOPE 1: AAPD will carry out demonstration activities to prove the viability of the available platform resulting from the previous project. After this demonstration phase, the platform and other results will be in a pre-production state, ready to enter into the last phase of market deployment.]
As used in AAPD, the Customer Development Methodology focussed on demonstration and evaluation of the product, to support any enhancements developed during the project.
During development of enhancements code quality was improved by restructuring the code where changes where made. Continuous Integration testing supported the development to ensure the robustness of the platform is ready to deploy the product in the market.
[TECHNICAL CONTENT/SCOPE 2: AAPD will perform performance and stress testing of the available prototype, studying its behaviour when it is scaled-up, with a huge load, able to deal with large data and also improving this quality in addition to stabilise the platform. In addition to this, the platform will be improved and integrate new custom solutions needed to cover the customer requirements.]
The AAPD program included a variety of testing, using Big Data tests to exercise the capacity of the system to process data, the Stress Testing to exercise the multi user capability and product feature testing with Customer representatives to validate implementations or prototypes. Additionally, customer validation was performed on the non-technical solutions such as help pages and support solutions.
[TECHNICAL CONTENT/SCOPE 3: A market analysis will be performed in order to understand the needs and trends of the market in the Risk analysis domain, the gaps that AAPD can fill and the existing risks in this process. Additionally, AAPD will define a business plan and strategy to follow in order to achieve SMEs expectations, ensuring the sustainability and impact of the solution in the market.]
A market analysis was performed in the Customer Validation tasks. This studied the competitors across different products that are covered by AAPD, including competitors to Data Analysis, Dashboards and Reporting and Cognitive Mapping. The results are reported in the Business Plan.
MAIN PROJECT RESULTS
The project work was divided into tasks. The output from the tasks is described below.
Platform Testing Tasks
The Big Data Tests consisted of the following activities:
• Build a testing framework to run validation tests on services, using Jenkins
• Implement a suite of tests, using JUnit
• Detect and fix bugs in services
Jenkins Continuous Integration server was installed to run the tests. Additionally, a testing framework was written to run tests with a list of inputs and a list of correct outputs. Each service now has a service to exercise it with a variation of input datasets and outputs. This allows testing datasets with different number of rows and columns, different data types and different errors in the data (for example missing values, bad data types, out of range values).
Building the framework took longer than expected with issues running tests against different large datasets and the time taken to run the full suite when testing the automated execution. Despite the delays, performance issues in memory size and processing time were detected in a few services. Each of these we traced to the shared code in the function ‘putFile’ which is used to detect data type and store the resulting data and metadata. The function was refactored to improve performance, but requires further attention to reduce memory consumption for large data.
The Stress Testing task was completed with difficulties and much extra effort. The tasks aimed to test the platform under the load of multiple concurrent users. In particular, to exercise the analysis calculations and test the scalability of the platform and help determine cost efficient and effective response times for the application.
Since the testing work had concentrated on the Big Data testing framework there was less time available for the Stress Testing. However, the foundation for the Big Data testing has provided the test suite for Stress Testing. The testing framework design means it can be extended with new larger datasets without rewriting the tests. The testing framework did require extending for parallel execution to simulate multiple users. From the Jenkins server, multiple service requests are launched to test the system response, how it scales to maintain availability and robustness.
To facilities the Stress Testing, the scalability of the platform needed to be tested. However, the implementation from the RAISME project used WSO2 Stratos 1.6 as a single machine installation. This needed to be upgraded and effort was made ensure services could be scaled be separating concerns. For the platform, this required updated Stratos to the latest version. During the project Stratos 3.0 was released and effort was made to update the platform. However, towards the end of the project Stratos 4.0 was also released and became supported by WSO2, with the Application, Data, ESB Servers all provided. Subsequently, further effort was used to make the platform use WSO2 Stratos 4.0. This now made the platform:
• Scalable, with dynamic servers
• Able to execute on Amazon EC2 or Openstack (on Rackspace for example),
• Uses Docker to automatically create and deploy servers
• Support high availability, redundant application servers and data servers.
WSO2 Stratos 4.0 update, installation instructions, Amazon EC2.
This task did not produce the Stress Testing results, and therefore platform costs and scaling requirements have been estimated for the Business Plan. However, the result has produced a scalable testing environment using the Big Data tests in a parallel execution framework, using Jenkins to manage the testing processes.
Platform & Service Enhancements
This task involved improving the robustness of the platform, its architecture and code structure. Additionally, the enhancements to functionality make it more marketable. Notably the activities to re architect the code to allow different product to be enabled or disabled. Turning products on and off supports different billing models for the DACORD components, such as paying a premium for Analysis. Also, the restructuring supported the effort to release a different portal StratView connected to the same background.
Additionally, when restructuring code the Analysis component should be able to load multiple datasets as individual systems, enabling the user to compare the behaviour of different systems. Multiple system support in Analysis was integrated late, and the architecture did not fully exploit the backbone.js framework, therefore changes to time point, system selection and variable selection did not always propagate throughout the tool.
The enhancements to the platform include improvements to the service architecture by separating the service between the Datasets, Analysis and Maps components; enhancing the scalability, to enable independence of service processing and state storage and making it compatible across Amazon AWS and OpenStack infrastructure (such as RackSpace); and, Code structuring, improving the architecture to reduce duplicate code and consolidate shared libraries.
The Maps component for cognitive collaborative mapping had many platform level enhancements including Backup and Restore, to allow users to download an archive of their maps and restore the archive later; updating the listing of Maps, allowing the user to sort and find Maps from a long list, Text Analysis service deployed in Python.
The Datasets component for importing and cleaning data ready for visualisation and analysis was improved by fixing platform services to cope with larger data and improved the automatic data type detection. Many data importing functions were simplified during the restructuring of code.
The Analysis component calculates the system stability and connectivity of variables within a system. This was updated mainly by restructuring code to make better use of the backbone.js framework and improving the loading and handling of multiple datasets with Analysis to support comparing system behaviour. The loading speed was improved through better use of asynchronous data loading and error handling, also fixed issues in data navigation, improved time point selection and synchronisation of graphs. Additionally exporting a Network Graph from the Analysis component to DACORD Maps enabled linking of tool sets so the network analysis algorithms could be made available with the Maps interface.
Portal Strategy and Development
The portal user interface and functionality was improved, since through Customer Discovery it was shown the usability and presentation made a significant impact on attracting new customers. The features chosen to implement in the portal are the result of the iterative customer development iterative process.
The strategic development tested new product ideas by prototyping interfaces and basic functionality. These were presented as demonstrations or working prototypes for evaluation by potential customers. A network visualisation and exploration tool was prototyped. This allowed the user to import a network from file and visualise using calculated network analysis functions. The interface allows the user to explore a large network applying filtering, layouts and colours according different calculated characteristics.
Additionally a Dashboard prototype was developed and demonstrated. This connects to the AAPD platform to provide easy collaborative access to the stored data. It has been developed to be simple to integrate into data environments with a good design and range of display widgets. The dashboard visualisation is agnostic in relation to the customer's system and architecture since the API implementation resides on customer's premises. Data to be displayed can be easily aggregated from multiple sources and supports interactive for drill down and multi variate exploration of business performance data.
The updates to the Portal are across all the components within the AAPD platform. The developed features for the Maps component include Annotation and Sharing view only Maps with ‘free’ users for improved Collaboration; rapid linking and merging to support larger maps; Text importing for faster map creation from documents or interview transcripts.
The Maps component was also launched as a separate product called StratView. The StratView offering is a Maps only version of the Portal, linked to the same backend. The portal uses different styling and logo to attract a different type of customer to a simpler cognitive mapping product.
The Datasets importing feature was improved with faster access to data cleaning tool. The Analysis component visualising system behaviour was improved with multiple systems handling and graphing, and better error handling to improve the robustness in the portal.
Overall the look and feel of the portal was improved with a new landing page to direct users into the application, new user invitation functions with example datasets and cognitive maps, integration of a Help Desk with support interface and instructional videos, and overall the portal styling was improved.
Develop Customer Experiments
Hypotheses about features, services, marketing and support were developed. Each hypothesis was sourced from Customer needs, through discussion or other communication with customers or customer representatives Milliman; Business needs, required platform enhancements for recording activity through usage monitoring and logging; Bug fixes and optimisation, where features and functions are not working as designed or not providing sufficient performance for customer usage testing; Platform enhancements, where the underlying platform is updated and extended to make the platform more robust.
Each hypothesis was tested and evaluated through customer experiments were designed to learn from about customer and their needs. Specifically, testing how accurate the hypothesis is about the customers needs.
The aspects learnt about the customer domain included:
• Information gathering, through interviewing domain experts from different groups in the organisation;
• Collaboration, group discussions to build shared knowledge
• Reviewing, to discuss the results with the groups and expand, refine or correct the information
• Annotation and change records, commenting on and within the information and recording a history of changes to aid collaboration and review
• Presentation of information is important and different formats need to be use for different audiences, hence the development of product ranges, Analysis, with detailed graphs; Maps, with Annotations; Dashboard, with a range of simple graphs; Network Tool, the filtering and layouts; and Reporting, with commentary and printable output
Within the development of the experiments, the specific types of record keeping were designed for each feature.
Recording methods used included:
• User logs from web portal and service invocations
• Specific records of data sizes stored (analysis of data store)
• Specific records of how many new features had been used (extended logging)
• Interviews with users
• Feedback on demonstrations, specifically with prototypes, wireframes and presentation of concepts
Perform Customer Experiments
The iterative approach to Customer Development resulted in significant to develop and run experiments on the ‘production’ deployment platform after internal testing on the development platform. Prototypes were deployed on either development platform or the production platform for external testing. However, since the development platform was subject to change and the production environment was strictly controlled, results could only be guaranteed on production, unless specific agreement was in place for evaluation of prototype functionality.
The Customer Experiments covered a wide range of activities including:
• Deployment and monitoring of product features and hypothesis
• Interviews with users after deployment
• Demonstrations of new product features deployed in platform
• Demonstrations of new prototypes deployed on development platform or local machine
• Demonstrations of concepts using wireframe design, or PowerPoint presentations
• Marketing brochure for World IT Show, Busan, Korea as part of UK delegation.
The demonstration of prototypes did not always lead to demonstration of product. For example, the Network Tool and Multi-variate complex Dashboard were running prototypes demonstrated to potential customers, but not deployed for customer use. Additionally, some hypothesis on new features were discussed during demonstrations, interviews and other informal discussions, these included:
• Reporting Dashboard, with commentary and printable;
• Offline working for the Maps application (editing is currently only available online).
Analyse Customer Experiments
Analysis of the customer experiments was performed at the end of each iteration. The results of feature usage data and the feedback from prototypes and demonstrations were analysed for their relative merit. Each result was analysed according to how well it meets or could meet the needs of the customer and the business.
The criteria used to judge each hypothesis/feature is:
• Business Development, how the business can grow and gain revenue from the products and features offered. And how to maintain the customer development process to review and evaluate customer experience.
• Market Development, how to understand the customer needs and how to demonstrate that the product features fulfil their needs. How to gain new customers and retain existing customers.
• Technical Development, product enhancements, and bug fixes that fulfil the customer functionality needs, or fulfil business needs in administration or marketing.
The report on Customer Experiments summarises the options about future development of the features analysed, based on the results of customer usage, internal testing, interviews and demonstrations. This summary suggests the priority is marketing activities for the output of AAPD to promote the product and further development of the collaborative features to enable and encourage more users. The output of this task was used in developing the Business Plan and Market Strategy.
Pivot or Proceed Checklist
The pivot or proceed task in the customer development methodology marks the decision point of each iteration on whether to continue with new experiments or repeat the previous experiment with a variation in product, concept or customer audience.
During this activity the experimental results and analysis for each hypothesis were discussed. The individual merits were judged by criteria of potential to increase customers, retain customers or keep DACORD ahead of the competition and how much effort it takes to transform the initial idea to prototype and then to product.
This task identified which changes were developed into product, which were developed into prototypes, which changes were presented as concepts and which we deemed to be completed or of no current value to the customer or business.
During this activity the domains for the product were identified as Risk Management; SODA, Knowledge capture and analysis; Data and Connectivity Analysis; Data Presentation using graphs, dashboard, reporting; Analysis as a service (with reporting); and for the two Business models: Platform as a Service (PaaS) and Software as a Service (SaaS).
Iterate Commercial Service, Product and User Definition
This task identified the product enablers for new and continued business as:
• Collaboration, supporting and encouraging many concurrent users to share, discuss and review data, analysis, results:
• Resulted in the design of 3 types of Annotation features with Maps. 1 type was fully implemented within the product;
• Sharing was enhanced with adding share users and messaging from inside Maps;
• New Reviewer (read only) user was added to enable Maps collaboration without adding a full license, enabling collaboration and extending the license model.
• Analysing multiple systems, to compare and grade performance:
• Fixing and enhancing multiple systems in Analysis.
• Help & Support, using Video examples and Support Desk
• Easy access to share final results, using Dashboard and Reporting
Other options where investigated but did not prove to be currently valuable to the customer. These options included:
• Analysis service, providing reports on data analysis
• Platform for data and analysis processing, scalable and highly available, using open source technology
• Tablet version of the analysis platform
• Offline editing for Maps
• Real-time collaboration on Map editing
• Network Tool: Import and Navigate large network online.
• Maps only product to make it easier to sell (launched as StratView).
Develop Positioning & Channel Hypothesis
This task has been carried out by DRTS together with Milliman. The goal is to find the customer and the path to achieving a repeatable sale. Sales costs must be less than the lifetime payments of that customer to have a viable business.
AAPD started with a number of hypothesis about the customer, segments, and channels, and throughout this second project period, there has been an ongoing process of identifying uncertainties then devising experiments and then finding out how to remove or change the focus of these unknowns.
The success of this particular task is proved by all partners having developed, explored and championed different vies of “the customer”, and how to reach them. DRTS has chosen to view Milliman, and consultants like them, as the customer, requiring a performance management service, whereas Visup have focused on data driven SME’s and a Dashboard service. The success with Milliman has been to test hypothesis and then reflect back to them their own findings, leading to further hypothesis and tests for clarification. These clarifications and reflections help both parties, not only shaping the idea of how to reach the customer but in the Milliman case it changes Milliman’s view of their own needs. For example Milliman have an increased realisation of the power of data and analytics, as evidenced by their website advertising.
Positioning and Channel Testing
Making a guess on the product and customer and how to get them, and then never checking again until the new product is in place, is quite clearly in most cases madness. This task is about the continual testing and checking that the product/service guesses are right, and then changing designs and strategies to suit the new findings.
Testing has been carried out by simple website searches, product trials, interviews, by monitoring use, monitoring competitors, talking to focus groups, talking to competitors and by offering different versions of the same product accessed in different ways. Each SME has moved from assumptions about the market to being able to develop viable business plans.
Develop and Validate Business Model
In this task each SME and Milliman has learnt firstly the importance and opportunity of thinking in Business Model terms. Thereafter ongoing engineering and dynamics of complex business elements have been trialled and re-trialled in thought experiments and in other forms of more realistic testing. This task has succeeded in moving the chances of business success for each SME times ten compared to the pre-AAPD starting position.
Develop and Validate Financial Model
The Financial Model has been developed and improved by the holistic customer development methodology used throughout the project. The success of the financial model is best gauged by the participating market readiness pre- and post-AAPD. There has been a dramatic shift in market readiness, due to market analysis and not due to more technology. This task involved the study of pricing of competitors, trialling software with customers and discussing pricing. Pre-AAPD is guessing hoping, post-AAPD is to know what people will pay for, why, how much they’ll pay, and how they like to pay. The resultant financial model and business plan provides a firm basis to market the AAPD platform, generating sales and revenue.
Deploy Traffic Strategy & Monitor Metrics
The monitoring of the application usage was implemented using a combination of different monitoring and analytics. The metrics and analytics were developed and configured to measure the phases of customer development.
The prime monitoring is built into the Platform with selected event logs recorded from user activity in the portal and service activity in the backend processing. Additional monitoring was used to analyse user entering and exiting the platform, new customer visits and behaviour. The metrics for this activity was implemented using Google Analytics, Freshdesk activity logs (from the Help and Support platform) and additional metrics implemented to analysis feature usage within the AAPD Platform. The tools and metrics are integrated into the product and product development process as part of customer validation.
Develop and Use Sales & Marketing Materials
The sales and marketing material has been developed to demonstrate the product features, educate the customer and excite them to learn about how the product can help them. The AAPD Platform is an online tool, therefore the prime marketing medium are the websites. The project website (www.aapd.eu) was used to provide information about AAPD, its goals and progress. The project partners maintained their website during the project, linking to AAPD project website and updating their own marketing as a result of project and product progress (www.drts.co.uk and www.visup.it).
The main development was the AAPD platform (www.dacord.co.uk). The landing page was significantly improved and different sign up and login strategies were tested to gain new customers. An alternative branding of a simpler version was launched as StratView (www.stratview.net) and limited to Maps only component. Additionally, a new style of user invitation were prototyped to test rapid sign up of users and promote the application functionality by giving new users example datasets and maps. A special version of the user invitation page was launched for the IT Show 2014 in Busan, Korea. The special invitation page includes links to the training and support videos that introduce the product features.
Product Training & Support
Training and Support has been implemented in FreshDesk and links directly to and from the AAPD Platform. FreshDesk hosts the instructional pages written to help with product features and the product videos made to introduce and educate users about new features that are available and how they are used. The support desk also allows customer to make direct queries about product features and issues. Customer questions and answers given by Support can easily be added to help customers with the same problem.
Demonstration activities as part of customer learning also provided support and training to users by educating them about new features or supporting them to better use existing features.
The activities in customer support also contributed to Customer Learning. This leads to understanding about common or uncommon issues that users have with the platform, also the ways in which customer use the platform or need to use the platform.
IPR Exploitation & Agreements
The good understanding of the market place and competition was gained by the IPR audit and tracking of foreground, background and external IP through out the project. The IPR exploitation and agreements were developed along side the Business Plan.
One outcome has been to understand how important the moving target of privacy is. This feeds directly into the development of dashboards and big data processing, and the use of technologies to protect services and data access.
The Business Plan and IPR Agreement from the project sets out clear paths to commercialise the AAPD Platform outputs. A key outcome has been to understand how important the moving target of privacy is. This feeds directly into the development of dashboards and big data processing, and the use of technologies to protect services and data access.
Potential Impact:
KEY IMPACT
[EXPECTED IMPACT 1: The demonstration of the research results of a previous project (RAISME) will be used to explore market opportunities in a specific domain (risk management) in order to secure its expected impact.]
Over the course of AAPD the prototype output from the previous project RAISME has been transformed through a process of code restructuring and feature enhancement. For example, the Maps component has been changed from a prototype to a fully working collaborative cognitive mapping product that supports Risk Analysis and is now being aimed at being used in Financial Risk analysis to meet recent changes in the regulatory process.
[EXPECTED IMPACT 2: AAPD takes further the results from the previous research project and aims to prove the viability of this solution and to ensure its expected impact can be exploited and put into the market in further commercial stages.]
The AAPD platform is the development of the RAISME project platform. It has been enhanced to fully support scalable services on cloud infrastructure. The product is an innovative approach to data analysis using a holistic systems approach to understand organisational behaviour and relative business performance. The AAPD platform integrates the Systems Analysis algorithms with intelligent data importing and improves the already established advanced visualisation services, and has been evaluated with potential customers as a valuable and viable tool to analyse any type of organisational data or otherwise.
[EXPECTED IMPACT 3: To demonstrate that the product, now demonstrated in AAPD, will have a valuable economic impact, will create employment and can be commercialized after further adaptations once demonstration project is finished.]
The expected impact for DRTS is: 5 year projected valuation of the company at £150M and increase the team from 4 to 19 people. With project revenue at £1.4M first year with low operating costs. Costs mostly being attributed to wages. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance to be marketed to business consultants worldwide.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is a Dashboard Tool that provides security, interactivity, ease of integration and good design.
[EXPECTED IMPACT 4: The AAPD project will ensure that results of the project are properly disseminated among the customer community and for creating links between the participating SMEs and the interested parties, creating a potential market interest.]
The dissemination activity of the project output has been an essential component of the project. Dissemination included running demonstrations and tutorials of prototypes and implemented product features to establish their value in the market. Opportunities to discuss and present (many hundreds of 3rd party interactions) the project output have been beneficial to explore and validate the customer domains. A brand identify has been achieved and a chain of interested users and providers of services.
SUMMARY OF IMPACT
AAPD represents a step forward for the SMEs and the customer involved in the project. An important outcome is the demonstration of AAPD business viability as a new extendible cloud service platform for the analysis of complex systems in the area of risk management. By testing and verifying the AAPD platform and its services, with the close involvement of a key customer as user, the project has demonstrated its progress beyond the state-of-the-art both for the targeted domain and in technological terms. The activity has provided important enhancements in financial risk analysis: Risk as one feature of emergent behaviour from complex adaptive systems; and, Risks seen as connected and changing over time. Modelling and optimisation software for risk analysis, has been integrated in a configurable chain of tools to deterministically build models using connectivity and uncertainty from data without imposed assumptions.
The AAPD results represent a relevant technological advance beyond the state of the art, allowing the participating SMEs to position themselves in the forefront of advanced tools and applications dealing with complex predictive analysis with specialised visualisation techniques. Each participant providing its expertise in a concrete application area has allowed for successfully achieving ambitious collaborative goals, where the adoption of an open service innovation approach enables new business services offerings.
Many R&D projects face serious difficulties when it comes to prototyping a demonstration. AAPD goes a step further and tests the feasibility of its integrated platform into a demonstration exercise whose objective is to validate the viability of the proposed system and the advantages it provides in terms of applicability, adaptability and performance in comparison with other similar, although not fully comparable, frameworks. The technical outcomes from AAPD are: Continuous application monitoring of the platform usage, including mechanisms to provide direct feedback from the customer and built-in Business Intelligence algorithms to evaluate customer experience in near real-time. Demonstration of a specific application demanding data processing and integration of analytical tools in a highly customisable cloud-based development environment, easily adaptable to user requirements.
The expected impact for DRTS is a 5 year projected valuation of the company at £150M and increased team from 4 to 19 people with project revenue at £1.4M first year with low operating costs. Marketplace, Risk Analysis tools for knowledge capture, system behaviour and business performance for Milliman and their 55,000 consultants.
The expected impact for VISUP is: projection of revenues at €2.2M after 3 years with a net profit of €500k and an increase in personnel of 4 times. The market offering is claimed as a Dashboard Tool that provides security, interactivity, ease of integration and good design.
DRTS’s DACORD using the updated and improved RAISME platform resulting from AAPD, provides a much needed paradigm shift, providing end-to-end problem exploration to solution. The simple to use and time saving services offer advanced visual analysis, embrace complexity and uncertainty, answer questions about critical risks and provide decision support for business performance and planning. DACORD is a new generation business platform fit for the age of big data connectedness and people-centred systems.
This new service will deliver novel services to enable radical re-engineering of businesses and their performance, address Complexity-based Risk Analysis, and also will be adapted to manage other categories of complex adaptive systems such as Smart Cities. This will bring about disruptive change by showing where uncertainties lie in businesses and systems, and show how these uncertainties are connected, and also how they affect business performance, then advise what is best to change. Knowing which areas need attention and how to adjust them will improve business performance significantly and enable operational savings of high financial worth. This will at the same time deliver against visible objectives from inherently more resilient business structures.
As the result of a long gestation of experience, inspiration, research, industry collaboration and entrepreneurial vision. The technology platform will leverage world-class fundamental research, already successfully trailed in other domains and prototyped in the previous EU-FP7 projects RAISME and now AAPD. These projects have delivered dynamic cloud services, management of complex systems, big data analytics, visualisation services, management of risk and network steering; also a well-evidenced business proposition for high commercial growth. The RAISME and AAPD results, supplemented with IPR owned and developed by DRTS, will galvanise a long-standing industrial relationship with Milliman, one of the worlds largest and respected actuarial consulting firms, to achieve early market trials, focused market demonstrations and market replication. This will be first through Milliman’s ten European offices, then worldwide through their 55 international offices. Leading to wider world use of these ideas and tools.
The technology is software-based and cannot be easily patented in Europe, although there are proprietary algorithms and business processes potentially patentable for the US market. However, product lifecycles are quite short in the business areas of focus. Product leadership will therefore be maintained mainly via ongoing investment in new product and service development and by maintaining strategic advantage through channel partnerships, agile and robust processes, and by staying aligned to other companies processes (e.g. Milliman). Key founders are engaged by contract to remain in the business for the next 5 years at least. Access to their know-how and their commitment to the business development are therefore fully secured. This ongoing investment and research will draw in other EU organisations and Universities and the revenue from sales will be recycled to the benefit of other EU communities providing a global lead in this area.
The current software product line includes four different modules collectively known as DACORD™. The first module, DACORD™ Maps enables soft start analysis of complex business situations, DACORD™ Data, is aimed at big data access and curation. The third module, DACORD™ Analysis performs multivariate investigation, insight and prediction. The fourth module DACORD™ Network harnesses network visualisation and insight techniques. The fifth module DACORD™ Dashboard enables Board level analysis and reporting. Modularising the software in this way enables multi-axis charging through customer depth of usage. These services are likely, with further investment, to set a global benchmark, which will demonstrate Europe at the centre of these types of service.
Visup’s use of the AAPD Dashboard Tool will enable users to easily configure dashboards and will allow advanced possibilities beyond pure data analysis. In particular, AAPD Dashboard Tool will allow efficient data discovery possibilities and create benefit from real-time market intelligence that empowers:
SMEs analytics: by providing a visual analytics solution empowering SMEs to perform analyses more rapidly compared to conventional methods, such as excel spreadsheets, and to quickly and easily select and isolate important data from noise;
SME’s decision making: this solution will definitely permit users to gain significant value from big data by extracting relevant data, by processing, organising and analysing them, and finally by presenting them through intuitive and clear reports, allowing the user to easily understand and act upon the findings.
Consequently, SMEs will benefit also by an improvement of their business performance due to the possibility to better understand their data and the ability to make more relevant and timely decisions, gaining substantial competitive advantages compared to their competitors.
In turn, such advantages results in:
Increased revenues: through new insights provided by the use of an analytics and decision making solutions, more informed decisions can lead to increased revenues by targeting better identified consumers and/or needs;
Reduced costs: key insights emerging from data analysis can produce, in particular, cost savings, including amongst other better promotional targeting, more efficient use of capital and resources, reduced maintenance costs, etc...
DISSEMINATION ACTIVITIES
With the context on the AAPD Demonstration Project, Dissemination translates to the Customer Development Methodology and Process, with demonstration, experimentation, and sales with marketing activity. Video case studies and other similar material is part of the customer acquisition process and supports product/service credibility and building trust.
The dissemination events have been meetings and workshops (hundreds of events) specifically to demonstrate or promote the project prototype product (the demonstrators) or when the project objectives have been presented and discussed. The demonstration activities have been used to obtain feedback on the prototypes from potential users and customers. The presentations of the objectives have been to invite users to join the demonstration activities and get involved in the customer experiments.
Develop and Use Sales & Marketing Materials
The sales and marketing material has been developed to demonstrate the product features, educate the customer and excite them to learn about how the product can help them. The AAPD Platform is an online tool, therefore the prime marketing medium are the websites. The project website (www.aapd.eu) was used to provide information about AAPD, its goals and progress. The project partners maintained their website during the project, linking to AAPD project website and updating their own marketing as a result of project and product progress (www.drts.co.uk and www.visup.it).
The main development was the AAPD platform (www.dacord.co.uk). The landing page was significantly improved and different sign up and login strategies were tested to gain new customers. An alternative branding of a simpler version was launched as StratView (www.stratview.net) and limited to Maps only component. Additionally, a new style of user invitation were prototyped to test rapid sign up of users and promote the application functionality by giving new users example datasets and maps. A special version of the user invitation page was launched for the IT Show 2014 in Busan, Korea. The special invitation page includes links to the training and support videos that introduce the product features.
Product Training & Support
Training and Support has been implemented in FreshDesk and links directly to and from the AAPD Platform. FreshDesk hosts the instructional pages written to help with product features and the product videos made to introduce and educate users about new features that are available and how they are used. The support desk also allows customer to make direct queries about product features and issues. Customer questions and answers given by Support can easily be added to help customers with the same problem.
Demonstration activities as part of customer learning also provided support and training to users by educating them about new features or supporting them to better use existing features.
The activities in customer support also contributed to Customer Learning. This leads to understanding about common or uncommon issues that users have with the platform, also the ways in which customer use the platform or need to use the platform.
List of Websites:
www.aapd.eu
Jeff Allan, CEO
86 Westbourne Rd,
Sheffield
S10 2QT
UK
