The Vision Workshop: A Step-by-Step Guide to Creating Your Own Data & Analytics Strategy Roadmap
Data & analytics (D&A) is empowering better, faster, and more strategic decision-making, and leaders from organizations of every size and type are racing to invest in the digital transformation projects data-driven decision-making requires.
And yet, industry experts say, “many of these projects continue to under-deliver or even fail to deliver on expected value or return on investment (ROI)”. These failures can cause real setbacks to the momentum and level of data maturity required for digital transformation.
Reasons for data project failures vary from incomplete, inaccessible, or even biased data to misapplication of analytics. But the one variable most D&A failures have in common?
In this blog post, you'll learn the strategic, step-by-step process our own data experts use to help clients plan out their digital transformation efforts.
By following these steps, you’ll be able to create your own data & analytics strategy roadmap — one you can rely on for successful digital transformation, without failures or stalled projects.
The Vision Workshop
Failure to plan is planning to fail.
Benjamin Franklin repeated this quote often, and it still rings true today.
We understand the temptation to dive head-first into the digital transformation race. But as with any race, disciplined preparation and planning can make all the difference.
At Wimmer Solutions, our data experts help clients plan for successful digital transformation through a structured process we call The Vision Workshop.
The Vision Workshop begins with an evaluation of our clients’ business needs and culminates in a reliable data & analytics strategy roadmap of prioritized projects that will propel your digital transformation journey with maximum efficiency.
By creating this roadmap from the perspective of our clients’ business needs, alongside their organization’s business goals and information about available data and capabilities, our experts help pinpoint:
- Potential pitfalls in the way of meeting business goals
- Opportunities for expediting the organization’s digital transformation journey
- The right initiatives, in the right order, for realizing a sure and cost-effective path to data-driven decision-making.
What Is a Data & Analytics Strategy Roadmap?
A D&A strategy roadmap is a carefully considered, prioritized list of data-related project initiatives (e.g., analytic dashboards, reports, data quality improvements, models, algorithms, etc.).
Teams implement initiatives according to the roadmap and in an iterative fashion, correcting course, filling gaps, and using new opportunities to achieve subsequent goals. This helps organizations realize digital transformation through a series of “wins” rather than costly trial and error.
Are There Other Reasons to Create a Data & Analytics Roadmap?
Achieving digital transformation with maximum efficiency may be the strategic reason to create a D&A roadmap, but here are a few added bonuses:
- Achieve alignment on initiative prioritization. Stakeholders can view details on projects and their respective organizational goals.
- Manage expectations regarding timelines and value. Transparency breeds understanding and consensus.
- Guidance on resource allocation. Make informed choices on investments in technology and skillsets.
- Forecast expenditures. Look ahead at projected expenditures and budget accordingly.
7 Steps to Crafting Your Own Data & Analytics Strategy Roadmap
The following steps will help you define business needs, determine the right data & analytics solutions to meet them, and then prioritize initiatives for optimal implementation. In other words, they’ll help you create your own strategic, executable D&A strategy roadmap.
Step 1: Identify Key Stakeholders
1.1.) Early in the process — once you know which business unit or department you want to serve with data and analytics — make a list of key stakeholders to involve in planning.
1.2.) Consider the impact of data & analytics on each stakeholder you invite.
1.3.) Key stakeholders might include:
- Department leadership (for strategic direction)
- Department representatives and potential end users (to help brainstorm department needs)
- IT and Data team representatives (to inform on data and technical capabilities)
- An executive “champion” of digital transformation (to help with future change management efforts)
- Other staff who might be impacted by new capabilities
Step 2: Define Business Needs
2.1.) With key stakeholders, brainstorm specific business objectives or “needs” (i.e., problems or opportunities that can be addressed through data & analytics).
Satisfying each need should:
- Achieve, or further progress toward, the organization’s broader goals
- Align with the department’s business strategy
- Bring measurable business outcomes
- Drive business value
2.2.) Try fitting each need and its corresponding business objective into the following sentence:
We need to _________ so we can _______.
We need to analyze customer data so we can improve customer experience.
Step 3: Assess Data
Implementing D&A solutions and using them successfully depends, in large part, on the strengths and limitations of available data. It’s vital to have a clear understanding of both.
With your IT or Data team’s help, review the current data operations processes and procedures to help address the following:
3.1.) Assess the current state of your organization’s data landscape:
- What data do we have available?
- How much data do we have?
- How do people use data throughout the organization?
- Does any data exist in siloed systems?
- What is the current state of data quality?
3.2.) Next, with your IT or Data team’s help, assess the future state of the organization’s data landscape (i.e., address the following questions with respect to each business need identified in Step 2):
- What data will be required?
- How much data will we need?
- How will we use data?
- Can we easily access the data we need?
- Has the data we need been processed and cleaned up?
- Identify any gaps between the current and future state of data.
3.3.) List specific initiatives or projects that will resolve any gaps.
For example, initiatives might include:
- Locating new data sources
- Addressing data quality
- Migrating data to the cloud
- Instituting data governance1 policies or new data architecture2
- Outsourcing DataOps services
Step 4: Assess Capabilities
4.1.) As in Step 3, enlist the help of your IT or Data team to itemize and assess the organization’s current analytics capabilities. These will include:
- Skillsets (including analytics capabilities)
- Tools, technology, and infrastructure
4.2.) Itemize and assess the future state of analytics capabilities (i.e., which capabilities will you need to implement each business need identified in Step 2?)
4.3.) Identify gaps between the current and future state of analytics capabilities.
4.4.) List specific initiatives required to address gaps and opportunities noted above. For example, initiatives might include:
- Building data pipelines or custom data collection tools
- Hiring additional skillsets
- Investing in new technology
- Implementing dashboards
Step 5: Prioritize
5.1.) Create a list of initiatives necessary to achieve the future state of both your data and your analytics capabilities.
5.2.) Assign a value to each initiative that represents its complexity and business value relative to the other initiatives. For instance, on a scale of 1 to 3 in complexity, you might assign “1” for simple projects and “3” for the most complex. Do the same for business value.
5.3.) Prioritize initiatives according to each one’s business value and complexity score.
Step 6: Create Your Roadmap
6.1.) With your list of individual initiatives organized into the order they should be implemented, you’ve created an outline for achieving your department's future state data & analytics capabilities, i.e., your roadmap.
6.2.) Make sure your roadmap is detailed enough to illustrate a clear path forward, but flexible enough to allow for adjustments as you proceed with your digital transformations.
Step 7: Implement, Monitor, and Adjust
7.1.) As your D&A capabilities come to fruition, review and update your roadmap regularly.
Taking an iterative3 approach will allow data teams to continuously test, evaluate, and refine coming phases as everyone sees impacts from previous implementations. As new data and insights become available, they can be incorporated into increasingly sophisticated solutions.
A scalable proof of concept (POC) may make sense for some projects. POCs give business leaders the opportunity to test business concepts and allow data teams to adjust and improve processes before developing fully productive capabilities.
These approaches reduce the risk of costly errors and build upon successes from prior implementations.
Organizational needs change, technology improves, people come and go. Your roadmap should also evolve so it remains sustainable — that is, relevant and actionable.
Ensuring value, ROI, and successful digital transformation requires careful planning with the right people and using the right context.
Organizations reach the highest levels of success when individuals work together harmoniously and come to agreements on initiatives, prioritization, and assessed values.
We understand it can be tempting to dive into digital transformation with flashy, tangible solutions. However, the most effective pathways often involve implementing decidedly less exciting, behind-the-scenes projects first.
Once you’ve followed our method for developing your data & analytics strategy roadmap, we believe you’ll find, as we have, that taking a deliberate and disciplined approach to digital transformation isn’t just a good idea — it’s priceless.
For More Information
The Vision Workshop with Wimmer Solutions is a 2-4-week limited engagement that has successfully launched several organizations into digital transformation.
Using our methods, coaching, and specialized tools, in partnership with our clients’ business knowledge, The Vision Workshop helps clients establish structured, clear pathways to meeting their organizational goals and objectives.
For more information about our process, or to enroll in The Vision Workshop with data experts from Wimmer Solutions, contact us today.
1 Data governance establishes clear roles and responsibilities for managing user access to reports and data, as well as policies and procedures for collecting, storing, and keeping it secure.
2 Data architectures establish how your data will be structured and stored and how different teams and systems will be able to access and analyze it.
3 The term "iterative" refers to a process of continuous improvement and refinement through multiple cycles or iterations.