How to Max the Value of Data & Analytics with a Value-Driven Portfolio Approach
Executive Summary
Data Value Realisation is based on a value-driven approach to technology.
This approach addresses the lack of prioritisation, visibility, and alignment in technology projects.
By prioritising value and aligning and measuring value, a solid foundation can be built for data management.
It is essential to bridge the gap between technical and nontechnical people and consolidate information for effective portfolio management.
Defining "good enough" data quality expectations and implementing value-driven governance is crucial for success.
Prioritising use cases and initiatives, tracking data quality, and building a communication tool are all essential to achieving product management.
It is also essential to consider the impact of adoption on people.
Creating a portfolio overview, prioritising data value, and deciding and prioritising a portfolio of use cases are all critical elements in valuing and realising value.
These steps can lead to successful data value realisation and should be considered in any technology project.
Webinar Details
Webinar Title: How to max the value of data & analytics with a value-driven portfolio approach
Webinar Date: 10th July 2023
Webinar Presenter: Nicolas Averseng
Meetup Group: DAMA SA Big Data & Data Science
Write-up Author: Howard Diesel
Contents
Executive Summary
Webinar Details
Debbie Diesel's Updates and Announcements
The Importance of Communicating Value in Data Management
The Importance of Value Management and Technology Challenges
Challenges in Data Optimisation and Value Delivery
Challenges in Alignment and Value Measurement
Challenges of Prioritisation and Measuring Results
Building Principles for Data Collaboration and Adoption
Importance of Building Proximity Between Business and Technical Users
The Importance of Portfolio Syncing in Product Management
Determining "Good Enough" in AI and Machine Learning Models.
The Importance of Data Quality and Defining Expectations.
Importance and Implementation of Business Lineage in Data Governance.
The Importance of Driving Three Dimensions of Value in Data Analytics Portfolio.
The Importance of a Driven Approach, Product Management, Demonstrating Value, and Responsible Data Use in Investment Strategy.
Understanding Clean Rooms and Feasibility in Product Development
Feasibility and Adoption in the Context of Technical Projects.
Demo of the Platform and its Features.
Portfolio and Initiative Management
Notes on Guided Initiatives and Knowledge Graphs.
Importance of evolving configurations in data management
Using use cases and data domains to prioritise data elements and assess data quality.
Tracking Data Quality and Value Contribution.
Benefits of a Dashboard Platform.
Discussion on data value realisation in healthcare.
Key steps and challenges in building a comprehensive data management platform.
The Importance of Data Value and Starting Small
Valuation and Realisation of Financial Assets.
Thank You Note for Webinar Attendees.
Debbie Diesel's Updates and Announcements
In her LinkedIn post, Debbie Diesel recaps a recording and tags those who attended and RSVPed. Debbie Diesel announces that Nicholas and Howard will be available for online chat and shares that the recording will be accessible through comments on the post. She also reminds her followers of upcoming events, such as a data privacy webinar with Caroline Mouton on the 12th, data management webinars on Thursdays, and CDMP Q&A on Fridays. Debbie Diesel invites individuals to discover more about certification and offers study tips and exam tricks. Notably, she mentions the DAMA EMEA conference at the end of the year, which is free for all EMEA members. She confirms that tickets will be distributed to attendees, with the top 20 receiving a free coupon. Lastly, Debbie Diesel invites EMEA members to contact her for the free coupon.
The Importance of Communicating Value in Data Management
I was impressed by the shared perspectives during the presentation about realising data value. The product's potential and value definitions were emphasised through a brief demo. We should all recognise the contributions we make to the business. The speaker recounted a personal anecdote about a project's cancellation due to a failure to communicate its value, which turned out to be their most embarrassing career moment.
The Importance of Value Management and Technology Challenges
Nicolas Averseng finds the story compelling and relatable, despite its painful nature. As the CEO and founder of a France-based company, he aims to bridge the gap between technical aspects and value articulation while also prioritising technical work. It is essential to comprehend how to safeguard and make decisions on technical matters. Nicolas welcomes inquiries and offers an interactive platform demo, promoting a value-driven approach. Nowadays, the primary challenge does not lie in technology but in addressing human and organisational obstacles to its utilisation.
Figure 1. Are we technology-driven or data-driven?
Figure 2. Trying to drive value from a messy data estate.
Challenges in Data Optimisation and Value Delivery
Nicolas Averseng stresses the significance of concentration and expertise for successfully implementing data strategy. One of the significant hurdles in data optimisation is the absence of prioritisation, as organisations need help in identifying what holds the most importance and may be swayed by the views of the top-paid personnel. Another obstacle is obtaining visibility, with different teams and technologies making it challenging to guarantee consistency, progress, and excellence throughout the entire data value chain. Coordination and synchronisation among various stakeholders and indicators are crucial for ensuring alignment, which is a critical factor in optimising data value.
Figure 3. Significant Challenges Facing Data Management
Challenges in Alignment and Value Measurement
Achieving successful alignment requires considering the ethical and sustainability risks associated with actions. It is crucial to measure value to defend budgets, gain support from stakeholders, and ensure the adoption of investments and business initiatives. A clear and organised starting point is necessary to tackle any changes effectively. Prioritising investments and gaining visibility on progress are essential for achieving alignment and addressing necessary adjustments. Efficiently measuring value is only possible with proper foundational elements in place. A comprehensive understanding of value is needed for prioritisation.
Challenges of Prioritisation and Measuring Results
Achieving desired outcomes requires effective prioritisation. The first step towards prioritisation is defining the value one desires. To prioritise effectively, it is essential to have alignment and clarity in determining goals. Measuring and tracking progress is crucial for adjusting plans. Business cases are necessary to secure budgets and project funding. However, people often forget about the business case after funding, leading to failure to measure actual results. CFOs often feel that data-driven business cases could be more trustworthy. Feedback loops and measuring results are crucial for learning and improvement. A lack of resources is often seen as a significant obstacle in implementing effective prioritisation and measurement.
Building Principles for Data Collaboration and Adoption
To ensure successful data projects, it's essential to prioritise transparent and collaborative principles. The key is to engage with the business and work together to drive transformation and optimise value creation. There are six foundational principles for this collaboration. The first principle is to establish a shared definition of the data investment's life cycle so that the progress and visibility of data products can be communicated. The second principle focuses on bridging the gap between technical and non-technical individuals, ensuring adoption and value creation for all involved.
Figure 4. Make sure you have a well-defined SDLC for your Data Assets
Importance of Building Proximity Between Business and Technical Users
Establishing a closer relationship between businesses and technical users is important by increasing iteration frequency and involving them in program development and task prioritisation. To enable collaboration and understanding, it is necessary to establish a common language with taxonomists and business experts. It needs to be more adequate to rely on one-time exercises or discussions with the business as this may lead to frustration and hinder adoption. Throughout the project's lifecycle, bridging the gap between technical and non-technical individuals is crucial to achieving a successful transformation. A portfolio view aids in comprehending the inventory, products, assets, and relationships between them, as well as identifying use cases that provide value.
Figure 5. Proximity, Adoption & Common Language
The Importance of Portfolio Syncing in Product Management
To manage investments and assets effectively, it's crucial to identify where reinvestment is needed and which Products should be divested. The process of portfolio syncing helps in pinpointing investment opportunities and optimising existing assets. It's vital to consolidate information from different systems and formats to effectively track portfolios and programs. Building a consolidated information system enables better visibility and alignment across various efforts. While making decisions, contextual data quality is more important than absolute quality. Understanding what's "good enough" for specific projects and use cases is necessary. Along with optimising investments and aligning efforts, syncing portfolios is essential in ensuring data is fit for purpose.
Figure 6. Portfolio Synchronisation
Determining "Good Enough" in AI and Machine Learning Models
Understanding the advancements of AI and machine learning models and aligning their various components is crucial, as noted by Nicolas Averseng. Remco Broekmans concurs with Nicolas and raises concerns about establishing when a model has reached its optimum performance. Nicolas stresses that the definition of "good enough" varies depending on the use case, goals, and desired business outcomes. The acceptable level of duplicates or errors in the model is determined by the context of the project. For instance, marketing may permit a certain level of duplication or mistakes, but minimal errors are necessary for transaction reconciliation in a bank. Conflicting expectations of quality may arise in different Products, leading to variations in the definition of "good enough.".
Importance and Implementation of Business Lineage in Data Governance
In data governance, clearly understanding the business lineage is crucial to connecting assets to business priorities with measurable objectives and use cases. The portfolio approach effectively identifies valuable assets, including data sets, machine learning models, and capabilities. Prioritising data literacy programs based on achieving business goals is more beneficial than offering them as standalone training. Assets, which include products and investments, generate value and should be linked to priorities to foster shared understanding and alignment. Value-driven governance enables decision-making, risk control, and ethical expectations alignment. Viewing governance as a means to deliver value rather than an obstacle is essential.
Figure 7. Principle 5: Value, Initiative & Asset Lineage
The Importance of Driving Three Dimensions of Value in Data Analytics Portfolio
According to Nicolas Averseng, focusing on three dimensions of value is crucial: potential risk, associated cost, and value itself. It's not enough to sell value alone without considering the potential risk and cost involved. Therefore, it's essential to integrate all three elements into the portfolio and the entire life cycle to ensure optimal control and optimisation. Nicolas Averseng suggests creating a "value-driven data analytics portfolio" that incorporates the six principles discussed. This portfolio should include initiatives, supporting assets, data sets, machine learning models, capabilities, training, and strategy to drive value, risk, and cost. Linking investments to existing systems can help bridge gaps and streamline workflows.
Figure 8. Principle 6: The three dimensions of driving value
The Importance of a Driven Approach, Product Management, Demonstrating Value, and Responsible Data Use in Investment Strategy
To improve investment strategies, Nicolas Averseng suggests adopting a more focused and systematic approach rather than relying on a random and unplanned investment method. Averseng also stresses the importance of treating Data & Analytics investment as products, and as such to set the right operating model to support them. It is crucial to demonstrate the value of these investments to convince stakeholders to support the transformation. Additionally, Averseng reminds us to conduct investment activities responsibly and comply with upcoming European AI regulations. Finally, maintaining a clean and organised environment for investment information can help facilitate effective decision-making.
Figure 9. Value-Driven Approach
Understanding Clean Rooms and Feasibility in Product Development
Howard Diesel raises the question of how to accurately assess the cleanliness of a room, highlighting its significance. Meanwhile, Nicolas Averseng expands on the notion of feasibility in product development, encompassing technical considerations, deployment, and usability. In product management, Averseng introduces the "3 U" principle, which underscores the importance of a product being useful, usable, and used. To be deemed useful, a product must fulfil a technical purpose. Meanwhile, usability entails various factors, including data dashboards and decision-making processes, and accessibility is essential in ensuring all individuals can use a product.
Feasibility and Adoption in the Context of Technical Projects
During a discussion on feasibility, Nicolas Averseng emphasised the need to consider the impact on employees and users, not just technical factors. Ethical challenges may also arise when evaluating feasibility, which requires a broader perspective. Howard Diesel pointed out that the ISO 9001 quality standard applies to data and application quality. To help organisations prioritise their efforts, Gartner provides frameworks that consider adoption and transformation. Ethical frameworks are also crucial in evaluating the feasibility and effectiveness of products. Gauchet asked about formulating additional questions for the demo.
Demo of the Platform and Features
Nicolas Averseng is presenting a demo instance of the platform, showcasing service principles' implementation. The platform is designed to be highly flexible, matching the maturity and structure of the organisation using it. The demo portal allows business users to submit demands, ideas and join ideation workshops. Project leaders, business leaders, and delivery teams can explore existing assets and their use cases. The platform emphasises the strategic business priorities of the organisation. The portfolio section displays various use cases grouped by strategic business priorities and maturity stages. With customisable columns, users can get a detailed view of each use case and its associated information. The prioritisation matrix is beneficial for selecting initiatives based on impact, complexity, and dependencies.
Portfolio and Initiative Management
The dependencies can be either functional or technical, across use cases and capabilities. To progress to the next stage, unlocking technical or organisational aspects may be necessary. Initiatives are grouped based on strategic business priorities, business lines or more in the portfolio view. When linked to JIRA or Azure DevOps, underlying project phases can be seen. The Swimlane view offers an overview of use cases per department and stage, enabling investment distribution analysis. Dimensional analysis can be applied to comprehend investment allocation, such as NPS improvement for marketing. The ID card feature thoroughly describes initiatives within a specific use case for delivery.
Notes on Guided Initiatives and Knowledge Graphs
Our platform aims to assist users in every step of the delivery process. By offering prompts and guidelines for each process stage, we ensure that users can quickly fulfil the necessary information requirements. Our system builds a knowledge graph that connects assets to use cases to strategic business priorities and metrics. This enables users to view their portfolio in diverse ways, including value lineage and connections to specific business priorities. Additionally, our system provides a cost view of initiatives and prioritisation tools such as impact versus complexity matrices. We understand the importance of tailoring the framework to balance the number of questions asked, ensuring the process remains effective without overwhelming our users.
Importance of Evolving Configurations in Data Management
To achieve adoption, aligning an organisation's maturity and power with the configuration of the platform is crucial. These configurations should also adapt to meet the organisation's changing needs. We offer automated high-level impact and complexity computation based on configured questions to achieve this. Additionally, we can integrate existing frameworks from clients, consulting companies and analysts. Our services include the introduction of portfolio management to replace multiple Excel sheets, linking data requirements to use cases, identifying data sources and owners, workflow validation for data quality and suitability, navigation and synchronisation with your data catalogue, and identifying other use cases that rely on the same assets. We also provide connect to data quality information to support investment decisions and emphasise the importance of understanding contributions from data sets.
Using Use Cases and Data Domains to Prioritise Data Elements and Assess Data Quality
Howard Diesel used a by-product approach to identify critical data elements and define quality expectations for use cases.
Tracking Data Quality and Value Contribution
When creating a data product for a specific purpose, Howard Diesel explains that searching for relevant data and conducting a quality check is crucial. However, sometimes the data quality needs to be improved to deliver the desired results, and further evaluation is necessary. Nicolas Averseng stresses the importance of monitoring data assets and assessing their suitability for new use cases. To ensure responsible use, ethics, data security, and value tracking guidelines, Averseng recommends using risk management questionnaires. He also suggests linking use cases to value contributions and monitoring various metrics over time. Cost analysis can also be a part of tracking value, considering value risk and cost.
Benefits of a Portfolio Management Platform
Businesses can significantly improve the value by deploying a portfolio management approach. The platform is both a management and communication tool, allowing for effective cost tracking and allocation across various projects. It also provide a business-oriented expenditure perspective and help users understand strategic priorities. Additionally, it displays the connection between data and business objectives, provide roadmaps for data assets and use cases, and facilitate collaboration and conversation. For more information, please refer to the LinkedIn (https://www.linkedin.com/in/naverseng/) and website (https://yooi.com) contact information provided.
Key steps and challenges in building a Comprehensive Data Management Platform
During the discussion, Ahmed Hamza Barradah stressed the significance of prioritising decisions and utilising use cases. Howard Diesel concurred and acknowledged the importance of this approach, while Nicolas Averseng highlighted the need to understand the complexity and multi-faceted challenges involved. Ahmed Hamza Barradah agreed with Nicolas Averseng's perspective. Additionally, Nicolas Averseng emphasised starting with a simple view and gradually adding complexity, which Ahmed Hamza Barradah agreed with. Praising the platform's comprehensive approach, Franck Sombo mentioned the integration of business analysis and requirements. Ahmed Hamza Barradah agreed with Franck Sombo's perspective. Franck Sombo also commended the platform's thoughtful design and the importance of resilience and adaptation to various use cases and organisations.
The Importance of Data Value and Starting Small
During a conversation, Howard Diesel shared about engaging with Ahmed in Saudi Arabia and jointly creating a portfolio of 49 use cases for a customer. Howard Diesel emphasised the challenges of not having a product and using Excel to manage Data Product Valuation. Ahmed Hamza Barradah acknowledged the importance of starting small to fully realise a platform’s benefits and generate management enthusiasm for future iterations. He also expressed difficulty in assigning value to data in various industries. Unfortunately, there seems to be a lack of recognition at the executive level regarding the significance of data.
Valuation and Realisation of Financial Assets
Determining the value of paving data is crucial to understanding its return on investment. To properly evaluate its worth, both absolute valuation and potential value realisation through use case links must be considered. It's important to have a mature understanding of the process in order to build accurate valuations and track their value. The DM Council is actively working to determine the dollar value of assets, and there are available papers and approaches to assist in the process. Economic data and ratios play a vital role in providing information and understanding valuation challenges. As best practices for valuation continue to evolve, ongoing discussions are valuable. Please note that this text pertains to discussions surrounding the valuation and realisation of financial assets.
Thank You Note for Webinar Attendees
Howard Diesel expresses gratitude and notes that it's almost a quarter past the hour. He thanks Nicolas for his excellent presentation and invites attendees to connect with him via his website or LinkedIn. Howard encourages people to contact him with any further questions and assures them that he will promptly share the webinar content.
Nicolas Averseng acknowledges Howard's remarks with a simple "Yep." Ahmed Hamza Barradah expresses gratitude to everyone for the opportunity. Nicholas also thanks Howard and all the attendees for having him and wants to continue the discussion. Franck Sombo agrees with the sentiment expressed.
Howard Diesel concludes by thanking everyone for their participation. Ahmed Hamza Barradah echoes this sentiment of gratitude. Finally, Nicolas Averseng wraps up the conversation with a final thank you.
If you want to receive the recording, kindly contact Debbie (social@modelwaresystems.com)
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