The Wrap: Developing a Data-Driven Organization

The benefits of becoming a data-driven organization can include increased sales, reduced operational expenses, and improved customer service.  Relying on trusted data when launching new business initiatives instead of conjecture and assumptions can not only produce more actionable outcomes, but also reveal new opportunities and strategic directions that may not immediately be apparent.

Successfully using data as a key driver of a larger digital transformation effort, however, is not a simple task.  While it may start as a small project, if done right it can evolve into a more extensive operating model, involving technology, people, process, and culture, notes Steve Brennan, VP of data strategy and analytics at Carhartt, Inc., a maker of durable workwear and outdoor apparel.

Steps to take in developing a data-driven organization was one of the key topics in a recent CIO Executive Council Power Hour webcast entitled, “Exploits of the Data Driven.” Joining Steve in the discussion was Mark Picone, VP of Information & Data Services at Adobe, Inc. Both IT leaders work for organizations that have been recognized with CIO 100Awards this year for successfully developing ways to use data as a key driver of business initiatives and creating projects and strategies that were part of a larger digital transformation within their respective companies.

Some tips on taking that first step toward a data-driven environment:

  1. Focus on the customer journey.  How does the customer discover, try and use a product and engage with the company offering that product? To find out, you must first map all the pieces of the customer journey and then define and establish separate KPIs across each journey point.
  2. Develop a playbook based on the customer journey framework.  This includes a top-down understanding of each step of the customer journey and the steps taken by customers – discover, try, buy, use, and renew.  It also includes a bottom-up overview of the centralized and consolidated data assets. Governance is a big part of this, as well as a cross-organizational agreement on the definitions of a data metric or data attribute.
  3. Consolidate and pull everything into a single unified data architecture.  This provides a single source of truth that everything is mapped to. This makes it easier to find actionable business insights as you plow through the data (which can be hard and brutal work.)
  4. Use the right tools.  There are a variety of tools that pull everything back to a central data lake to create that single view of the customer and experiences that are part of the customer journey.
  5. Be prepared to add more structure to your data.  Most of the data you deal with will probably be structured, but some may be unstructured or semi-structured.  If so, it may need a lot of interpretation to make it more structured and easier to pull together in a more coherent fashion.

In terms of developing a data-savvy culture, both IT leaders point out that your role is more about advising and training and not ‘build it and they will come.’ You really must drive that into the organization. Also, communication is important. Create an environment where you can share ideas and identify new relationships. That way, you can crowdsource solutions and discuss problems you may have, and ultimately create priorities for the organization.

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