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Data Management Value Realization Journey Map

  • Bill Schmarzo 

[Editorial Note: Now THIS is data storytelling! – Kurt Cagle]

I originally published the Big Data Storymap in January 2013 as a way of communicating the key factors to a successful Big Data and Data Science initiative; to provide a creative view of the “data to value” journey by leveraging the Big Data Business Model Maturity Index to transition organizations from their Current State of Business Intelligence and Data Warehousing to the Future State of Big Data, Data Science and Value Engineering (Figure 1).

Figure 1: Big Data Storymap

The goal of a story map was to provide a graphical visualization that uses metaphors and journey landmarks to educate my clients about the key components of a successful big data strategy.  Key Landmarks on the Big Data Storymap (Figure 2):

  • Landmark #1:  Explosive Market Dynamics. Highlight the market challenges that were necessitating a different approach to integrating big data (data and analytics) into one’s business.
  • Landmark #2:  Business and IT Challenges. Highlight the significant challenges that organizations faced in trying to transform their business intelligence and data warehouse environments to take advantage of the business benefits offered by big data.
  • Landmark #3:  Big Data Business Model Transformation. Provide a benchmark that helped organizations understand how effective they were in leveraging data and analytics to power their business models.
  • Landmark #4:  Big Data Implementation Journey. Define a process that drives alignment between IT and the Business to deliver actionable, business relevant outcomes. 
  • Landmark #5:  Operationalize Big Data. Define a data science process that supported the continuous development and refinement of data and analytics in operationalizing the organization’s big data capabilities. 
  • Landmark #6:  Value Creation City. Provide some examples of the business functions that could benefit.

Figure 2: Big Data Storymap Landmarks

Big Data Game Board

Then October 2018, I introduced the Big Data Game Board that expanded upon the Big Data Storymap by providing a fun game board-type experience in helping organizations successfully navigate their journey from data to value (Figure 3).


Figure 3: Big Data Game Board

The Big Data Game Board highlighted the traps that hinder organizations from navigating from data to value.  Those traps included:

  • Trap #1:  Did you get “Caught in the Analytics Chasm” or were you successful in “Exploiting the Economic Value of Data”?
  • Trap #2:  Did you “Fall into The Data Swamp” or are you creating a “Collaborative Value Creation Platform”? 
  • Trap #3: Are you pursuing “Technology Tail-chase Trail” or are you “Focused on Business Outcomes”?
  • Trap #4: Are you “Floating Away with Over-inflated Promises” or taking a “Pragmatic Value Engineering” approach?
  • Trap #5: Have you perished on the “Plain of CLM: Career Limiting Moves” or did you scale the mountain of “Envisioning to Build Business Support”?

Loads of pragmatic advice complete with templates and tools (see the blog “The Big Data Game Board™”) to help organizations win the Big Data and Data Science value creation game.

Introducing the Data Management Value Creation Journey Map

Hopefully, these two artifacts got the organization’s creative juices flowing with respect to becoming being more effective at leveraging data and analytics to power their business models.

Now it’s time for part three of this visual journey; to provide a foundational data management journey that provides that “clear line of sight” from data to value.  The Data Management Value Creation Journey Map provides that “clear line of sight” roadmap from data to value by integrating the disciplines of data management, data science, and business management (Figure 4).


Figure 4: Data Management Value Creation Journey Map

This can be a tricky roadmap.  There are many incorrect decisions that can lead to the path of failure (☠️).  Plus, skipping, or short-cutting steps can sweep you down the “chute” back to the beginning, wasting financial, temporal, and personnel resources, and more importantly, damaging business stakeholder confidence as a result.

The goal of the Data Management Value Creation Journey Map is to highlight the integral collaboration between data engineering, data science, and business management to successfully navigate the journey from data to value; where senior leadership can clearly articulate and quantify the business and operational value realized through the application of data and analytics to the business (Figure 5).


Figure 5: Data Management Value Creation Journey Map Disciplines

The Data Management Value Creation Journey Map brings together the following practices:

  • Value Engineering decomposes an organization’s Strategic Business Initiative into its supporting business (stakeholders, use cases, KPIs), data, and analytic requirements.
  • Data management enables the ingesting, storing, organizing, tagging, cataloging, maintaining, and securing the data created and collected by an organization.
  • Data engineering is responsible for aggregating, preparing, normalizing, standardizing, binning, wrangling, munging, and making raw data usable to the downstream data consumers within an organization and across the company’s ecosystem.
  • Feature engineering drive the collaboration subject matter experts and the data science team to select and mathematically transform data variables to create ML Features that are used to create AI / ML models.
  • Data Science creates the AI / ML ensemble of models used to identify and codify the customer, product, and operational propensities, trends, patterns, and relationships buried in the data.
  • ML Engineering applies software engineering principles to the data management and data science processes to manage, monitor, and operationalize ML models within the operations of the business.
  • MLOps is a set of practices that seeks to deploy and maintain machine learning models in production reliably and efficiently.

Summary: Creating a Data Culture of Empowerment

The Data Management Value Creation Journey Map, along with the Big Data Storymap and the Big Data Game Board, seeks to put a creative yet actionable spin on what organizations need to do to provide that clear line of sight from data to value.

So, let’s tell a story map, grab a game board, and jump on a journey to unleash the greatness of everyone in the organization to become more effective at leveraging data and analytics to power the business.