Chief Data Officer Toolkit: Leading the Digital Business Transformation – Part 1

CDOs are the new hot role to rock. Read about the CDO Toolkit, which integrates the disciplines of economics and analytics to help the CDO to ascertain the economic value of the organization’s data and data sources.

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The Chief Data Officer (CDO) role is red hot!! If you don’t have one, then you are totally uncool and unprepared to reap the bounty of wealth offered up by Big Data and the Internet of Things (IOT). Gartner predicts that 90 percent of large companies will have a CDO role by the end of 20191. Hire a CDO, and everything will be good. Or, will it?

Unfortunately, it’s hard to distinguish the charter of the CDO from that of the Chief Information Officer (CIO) or the Chief Technology Officer (CTO). Fortunately, I have a simple fix to this problem; ensure that the CDO charter is to:

Acquire, enrich and monetize the organization’s data (and associated analytics)

Key to the CDO’s success is the ability to determine the economic value of the organization’s data and the resulting analytics, and to use that determination to prioritize and focus data and analytics investments.

So the time is right to introduce the Chief Data Officer (CDO) Toolkit. The CDO Toolkit integrates the disciplines of economics and analytics to help the CDO to ascertain the economic value of the organization’s data and data sources, and use that information to prioritize the organization’s data and analytics investments. This blog will introduce the CDO Toolkit concept with some examples. Future blogs (or possibly an eBook) will drill provide more details including supporting worksheets.

Determining the Economic Value of Data

Before we launch into the CDO Toolkit discussion, there are some aspects of data (and analytics) that form the foundation of the CDO’s charter.

Most currencies, like money or human currency, have a transactional limitation; that is, a dollar can only be used to buy one item or service at a time. Likewise, a person can only do one job at a time.

But data and analytics are not constrained by these transactional limitations. Data as a currency exhibits a network effect, where the same data can be used simultaneously across multiple business processes or business initiatives thereby increasing its overall economic value to the organization. The same network effect can be said of analytics as well, for what is analytics but “curated” data. This makes data and analytics powerful currencies in which to invest.

Data and analytics, as corporate assets or intellectual capital, exhibit a behavior never seen before in the business world. Most business assets operate under the “rule of depreciation”, where the value of an asset is reduced with the passage of time and/or usage. But data and analytic digital assets operate under the “rule of appreciation” where these digital assets become more valuable as they are 1) used simultaneously across multiple business processes and business initiatives and 2) the more that you use them, the accurate they become. Unlike assets that get worn out or outdated, the more you add to existing data sets the stronger, and more insightful even the old data becomes. Data that would otherwise become throwaway data as standalone becomes more valuable when integrated with other sources of data. This economic phenomenon is a game-changer for organizations looking to drive digital business transformation.

Unfortunately, organizations lack a coordination point around which to align the data and analytic currencies. Fortunately that’s the role of use cases, which we define asclusters of decisions around a common subject area in support of an organization’s key business processes or key business initiatives. Use cases provide an anchor point around which the organization can align its data and analytics currencies, and address what I call the “Rubik’s Cube Challenge,” where you have three dimensions (data, analytics and use cases) that the organization needs to align in order to create economic value (see Figure 1).

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Figure 1: Addressing the Data and Analytics Rubik's Code Challenge

The objective of this blog series is to introduce the CDO Toolkit as a framework and associated processes to help the Chief Data Officer to address the questions raised in Figure 1; to provide a toolkit to exploit the unique behaviors of data and analytics as currency to create new sources of organizational intellectual capital and value creation.

Introducing the CDO Toolkit

The CDO Toolkit is designed to help the Chief Data Officer to:

  • Monetize the organization’s data by determining its potential economic value
  • Identify use cases where the data can drive business outcomes
  • Develop a framework for the capture, refinement and sharing of the organization’s data (internal, external, partner, public, syndicated, etc.)
  • Develop a methodology for the capture, refinement and sharing of the resulting analytics

Identify Targeted Business Initiative

The starting point for the CDO charter is a solid understanding of the organization’s key business initiatives2. For this blog, we will focus on Chipotle’s 2012 “Increase Same Store Sales” business initiative found in Chipotle’s 2012 Annual Report(see Figure 2).

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Figure 2: Chipotle Target Business Initiative

Estimate Financial Value of Business Initiative

Once we have identified the targeted business initiative, we next need to calculate a rough order estimate of the financial value of that business initiative. Using data readily available from the 2012 Chipotle Annual Report, we can determine that the estimated value of the Chipotle “Increase Same Store Sales by 7%” business initiative is roughly $191M annually (see Figure 3).

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Figure 3: Estimate Value of Targeted Business Initiative

While this is a fairly rudimentary calculation, it is a sufficient starting point in driving conversations between the CDO and the key business stakeholders in order to gain consensus on the estimated financial value (or range of financial value) of the targeted business initiative.