Rich Peters' second of three articles on building a data strategy focuses on the Assessment.

The assessment phase is where your data vision and strategy meet reality. This is where you map out your current state for each of the core elements (people, process, technology and data) and combine that with your key objectives and capabilities that we defined in the first part of your data strategy. You bring them together by creating solutions that deliver your strategy and vision.

How Data Assessment Works

Assessment is an iterative process where the outcomes are decisions made about the future state and how to get there. However, you need to start with where you are today.

First – assessing your current state
Second – assessing your future state
Third – assessing how to get from your current state to your future state

This iterative process should not become cumbersome. As you focus more closely on the picture of your future state, it will generate more questions about your current state and, just as importantly, how to get from current to future state.

Start the assessment of where you are today utilizing your key objectives and capabilities as guidelines.

  • How close to your data strategy are you today?
  • Where are the gaps?

As you assess your current state, you start to architect your future state.

  • Can you use your existing technology in a different way to meet the needs?
  • Do you need additional tools?
  • Do you need different processes?
  • Will your current data support the objectives?
  • Do you have the right people to deliver the strategy? Do you need additional skills?
  • What will it take for the organization to embrace the future state?

Touchpoints as Guides

Each of your core elements (People, Process, Technology, Data) needs to be divided into components where the assessment can provide actionable information. Many of these components will be broken down into smaller subcomponents as necessary. I call the components and subcomponents “touchpoints”. The touchpoints give you a framework for delivering the assessment as well as a starting point for the upcoming roadmap. To get started, identify your key touchpoints for the assessment across the core elements. The table below gives you a starting point, but each organization is unique in its needs and most will add to this list.

Table 1. Data Assessment Touchpoints







Business process flows (data related)

IT platforms and strategic direction

Subject areas

User communities

Legal or regulatory requirements beyond GAAP

All current or planned systems

Master Data / Hierarchies


Reporting and analytics

Architecture and data flows


Org structure – business and for supporting the data needs

Data ingestion and management

Software licenses and costs

Data quality

Data ownership

Shadow processes – how the organization “really works”

Current data environment – pools, lakes, warehouse

Internal data

Institutional knowledge

Feedback and support

Lifecycle management

3rd party or external data

Thought leaders

Timeliness of data

Shadow IT

Data Silos


The table above shows there are quite a few touchpoints for the assessment. Your organization may already have some of this information. However, the information will need to be collected and validated. For many of these touchpoints, the only way to get the information is through the interviewing process.

Planning the Assessment

Good planning can make the assessment process much smoother and more successful. Here are my recommendations:

  • Start with an initial stakeholder assessment and identify key individuals for each of the touchpoints.
  • Use your key objectives and capabilities to help prioritize your initial assessment plan. There are certain data subject areas, business processes and capabilities that have a higher impact on your organization.
  • Build your plan with some flexibility – some touchpoints may require more iterations or interviews than expected.
  • Set up a site to hold all your documents including interview notes. It is helpful to establish common attributes for the touchpoints and organizational structure so you can quickly find items related to finance and “process”, or sales and “data”, and each or their related touchpoints.
  • This is a significant undertaking and I highly recommend having a dedicated core team. The team should consist of a balanced mix of business and IT resources.

Tip: The assessment phase can benefit from some “quick wins” as you progress. Build credibility and momentum by using your key objectives and capabilities to find one or more areas that can be quickly assessed for current state, future state and architecting potential solutions.


Other articles in this series, by Rich Peters:

Delivering Value Through Data

How to Write Your Data Vision and Mission Statements

How to Build a Data Strategy: Part 1 - Key objectives and capabilities


Keys to Success

1. Be inclusive

Being inclusive is critical across all the core elements.

People → Ensure you have active participation across all functional areas of the organization and at all levels from the individual contributors to the senior leadership. The stakeholder matrix can confirm that there are no gaps. Remember that some of your stakeholders may be external to your organization.

Process → Look at the processes as a whole. Small changes in one area can have large impacts downstream or even upstream in the process. I recommend process review sessions that include some brainstorming activities with the identified stakeholders. It is helpful to look at the entire process and some of the related processes to see how data is created, modified, and used. It is also important to understand how it flows within the process as well as into and out of the process.

Technology → Evaluate your current technology along with new technology. New technologies are not always better. Sometimes a tweak or enhancement will provide what you need at a much lower cost. However, if the new technology will provide a leap forward, then look at all options, and not just the current hot technology.

Data → Look at all your data. This includes all your internal data, external data, master data, operational data, and metadata. It is important to understand all the users for each type of data, how they use it, and why they use it.

2. Transparency

Create a safe space to get open feedback. The assessment will only be as good as the information you gather for it. One of the hardest challenges to overcome is the reluctance of people to fully engage in the process. Make sure to communicate that these sessions are not about venting or dumping. They are working sessions to dig deep into how processes are run and how data is used.

Almost all organizations have shadow processes. Identifying what they are and why they exist is critical to building a better future state. Shadow processes and shadow IT around data should no longer be needed.

3. Clear communications

Be clear in your communications about the data strategy. For example:

    • Why the strategy is important to the organization
    • What the future state look like and how it will benefit the organization
      • Ensure that the future design works across the entire organization and has support from the leadership and key stakeholders / influencers.
      • It may take more than one iteration to come up with the proposed future state.
    • How this change will help the organization

For the team members:

    • Why they are involved
    • What is expected of them
    • Not all pain points and requests can be incorporated into the data strategy.

During the assessment phase, you will be interviewing people from all parts of your organization. These interviews, from basic questions on how they use the data to how the future state will benefit or challenge them, are a big part of communicating your intent to be inclusive and responsive to their needs.

K.I.S.S. – Keep it small and simple

Keep the solutions small, simple to understand, and simple to deliver. Each solution should have a clear answer to why it is needed, and how it will support the vision and strategy, and add value to the organization.

The easiest way to understand this approach is to see each of the solutions as building blocks. There are different types of building blocks. Some are foundational, some are dependent on other building blocks and some may stand alone. The road mapping phase that follows will show how to put the building blocks together and deliver the strategy. To make this approach work it is important to understand the dependencies and constraints for each of the building blocks. When evaluating, remove artificial constraints such as those driven by past failures or the fear of change.

Prioritize Data Usability, Reusability, and Portability

Data has incredible value when it is easy to find, understand and use. That value increases significantly when you can reuse the data to answer different questions without having to build new solutions. This value comes from understanding how the organization works and building solutions that answer today’s and tomorrow’s questions. This value is also driven by having strong metadata integration, so users understand the data, its proper usage and lineage. This reusability helps safeguard that you will deliver on the single version of the truth. It supports future needs where your data may get leveraged by newer AI technologies or even moved to a completely different platform. Tools and platforms that restrict your ability to access your data should be evaluated very carefully to understand the risk and costs that will come from that restriction.

Tip – be careful of getting too tightly aligned to the objectives coming out of the data strategy. It is important to assess all the data that is in use as well as projecting what data could be useful. You can’t always predict what questions will be asked in the future, but by understanding and architecting all of your data, it significantly increases the speed with which you can answer future questions. It also increases trust in your data since it was collected according to a standard process.

Success Requires More than Resources

Define what you need to succeed. Each solution or building block will require resources. These are measured in financial commitments and people’s time. However, don’t forget the leadership commitment and change management effort to overcome resistance to change. You can build an elegant and technically correct solution, but if it is not supported, and people don’t want to use it, then your new strategy will fail. Utilizing the “people lens” will help in this effort. If you continually align on how people will use the future state solutions, the change management effort will become easier.

The Assessment and ROI

Defining return on investment for a data strategy can be daunting. However, there are ways for all organizations to calculate their ROI. First, ensure the assessment collects all known data issues and opportunities. Some of these may be well known on day one, while others will be uncovered during the assessment.

Table 2: Data strategy ROI

Benefits Costs
Strategic – benefits that go across entire organization and are hard to allocate - customer satisfaction and engagement – credibility, leadership, employee satisfaction Foundational – costs that go across entire organization and are hard to allocate – data quality, metadata and data alignment, IT infrastructure and tools, change management and training
Tactical – benefits that can be linked to a specific solution or group of solutions that will be delivered - process improvements, accuracy, speed, re-aligning resources, enabling new products or services Tactical – costs that can be linked to a specific solution or group of solutions that will be delivered - process improvements, accuracy, speed, re-aligning resources, enabling new products or services


Many organizations have significant data strategy foundational needs that will need to be met prior to significant ROI for the entire program. This is where three important parts of your strategy come together. First, leadership commitment and change management that sends a clear message that this is important to the organization. Second, building a roadmap that lays the foundation while delivering value. Third, identifying several “quick wins” that shows the value and gains positive traction.

Delivering the Assessment

  1. Build the team.
  2. Set the plan.
  3. Gather the documents and conduct the interviews.
  4. Document the current state.
  5. Draft the proposed future state
    • By touchpoint and sub touchpoint – Actionable
      • Ensure dependencies are identified,
      • Ensure change impact is identified,
    • By core element (People, Process, Technology, Data) – Strategic
    • Define the benefit for each actionable and strategic element:
      • Expected $$ return
      • Non $$ benefit
    • Identify the business priority and impact for each element.
  6. Identify across the core elements what is needed to support the future state.
  7. Identify the gaps and what is needed to get to the future state.
  8. Identify the effort, resources and change that it will take to get to the future state.
  9. Build the initial ROI evaluation.
  10. Prepare for road mapping effort.

A high level example

Let’s use one of the examples from our previous article, Data Strategy Part 1, to see how the assessment expands the level of detail. The chart below is a sample of key details for a leadership overview. It does not represent all the documentation that you will need to create. There is much more detail for the current state, future state and the architecture of the solutions. However, it does give you a start on building out your assessment phase.

Table 3: Data Strategy Example

What How Why Value / Need
We will enable customers to see a 360 view of their accounts. Provide payment history, payments due, order history, current products on order, delivery status and available product inventory Drives higher customer satisfaction and lowers customer support costs.

Takes friction out of the process and will increase sales
• $X to $Y
• Redeploy headcount
• Increase sales
We will provide seamless customer and product data to our salesforce. They can see current status, open issues, history along with customer and product profitability. Blending Customer Relationship Management (CRM) data along with operational, historical, customer and product profitability will build stronger and more profitable relationships. • $X to $Y
• Low to Medium Value
• Lower Priority
• Simplifies what is done manually


Table 4: Data Assessment Elements

Solution Integrated customer data from all sources
Owner VP Sales
Why Supports internal and external view of the customer. Higher customer satisfaction and better customer interactions,
How Leverage data integration infrastructure to bring together aligned customer data based on guidance from key business resources,
Key Deliverables (What)
  • Identify system of record for each data element/attribute during its lifecycle
  • Architect solution so that data is available for use directly and for successor solutions
  • Define if this will be done physically, virtually or a combination of both
  • Build proof of concept (POC) if necessary
  • Document all findings and why this architecture was recommended
  • Document ROI with all key drivers
  • Identify any outstanding issues or key risks
  • Customer Master Data alignment
  • Data integration infrastructure
  • Customer self serve 360 view of their accounts
  • Seamless customer and product data for our salesforce
Related Efforts
  • Integrate the material / product data from all sources
Change Effort
  • Internal - medium (fear of losing jobs and control)
  • External - medium to high (communication and training as to why this is a value add to the customer
  • Limited data architecture resources
  • Limited data integration resources
Key Resources
  • Data architect
  • Customer service leads
  • Sales leads
  • Data integration
Duration 12 weeks
Costs* 150k - does not include predecessor costs
  • Enables 250k savings per year, but requires investment in data alignment and 360 view to achieve ROI
  • Enables 100k gain in efficiency for sales force and allows sales force to focus on higher margin customers and products

*Costs need to follow organizations standard methodology and need to be for each solution (building block) so they are not under or over counted. (same for ROI)

A Parting Thought

The last question to ask people during the assessment is, “What do we do with the information and why?” This question gets people to open up about how they really use the data. It is common to hear that they use Excel or even more advanced tools to manipulate and analyze the data. Another common theme is that they have stopped asking for what they really need because they are always told that they can’t get it. A key part of the assessment is to break down these barriers and really understand what actionable information people in the organization need, so they can make decisions without having to continue to search for the data or manually manipulate the data. Ultimately, it is the people using the data that make the biggest difference and using the people “lens” to validate the solutions will ensure faster adoption and faster time to value.

Now that you have completed the assessment phase you will start to build out the roadmap. Hopefully, you have also identified some quick wins that can be implemented as a fast follow up to the roadmap or, in some cases, in parallel with the road mapping effort.

Data assessment

Roles We Recruit


Read our weekly e-newsletter packed with career advice and resources for the strategic technology leader, and information about active searches.

The Heller Report

Add a Comment

My CIO Career: How Dan Regalado Uses His Relationship Skills to Deliver Great Customer Experiences at Wynn Resorts

May 15, 2024

6 IT Adages I Know to be True

May 8, 2024