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 2019. Hire a CDO, and everything will be good. Or, will it?
Identify Use Cases That Support Target Business Initiative
Next, we need to identify the Use Cases3 (or clusters of decisions) that support the targeted business initiative. We interview the key business stakeholders to identify the key decisions that they need to make in support of the targeted Business Initiative, and then we group those decisions into common subject areas or use cases (see Figure 4).
Figure 4: Group Decisions Into Common Use Cases
Listed below are the use cases that came out of the interviews that support Chipotle’s “increase same store sales” business initiative:
Increase store traffic via local events marketing
Increase store traffic via customer loyalty program
Increase shopping bag revenue
Increase corporate catering
Increase non-corporate catering
Improve new product introduction effectiveness
Improve promotional effectiveness
This is also the point in the process where the Business and IT leaders need to prioritize the use cases based upon relative financial value and implementation feasibility over the next 9 to 12 months. Figure 5 shows a 2×2 Matrix that is a marvelous tool for driving group consensus regarding prioritization when used in a facilitated workshop situation. Check out the blog “Prioritization Matrix: Aligning Business and IT On The Big Data Journey” for recommendations on how to use the Prioritization Matrix.
This organizational process is critical for the adoption of the analytics. It is important that all key business stakeholders have a voice in determining the relative value and implementation feasibility of each use case. This may be the single most important step in the CDO Toolkit. This step ensures that all parties are in agreement about where and how to start prior to the organization investing significant money and time building out an analytics capability that the business stakeholders may not use or trust.
Estimate Financial Value of Use Cases
We now need to estimate the financial value for each use case. We can employ a simple polling technique to get an estimate on the financial value of each use case from each business stakeholder. Figure 6 captures the polling results from the different business stakeholders for the Chipotle “increase same store sales” business initiative.
Figure 6: Estimate Financial Value of Use Cases
The spreadsheet then averages all the estimates to come up with an estimate of the financial value of each use case (highlighted by the red box in Figure 6).
Identify Potential Data Sources
Next, we want to conduct business stakeholder interviews and facilitated brainstorming sessions to identify those data sources that might be useful in support of our target business initiative (see figure 7).
Figure 7: Identify Potential Data Sources
During this part of the process, it might be useful to review the definition of data science: Data science is about identifying those variables and metrics that might be better predictors of performance
During this data sources exercise, it is important to embrace the power of the word “might” and capture any and all ideas with respect to what data sources might be useful. The data science team will actually determine which data sources are valuable and which ones are not, but in this part of the process all data sources are worthy of consideration.
Estimate Financial Value of the Data
Next we want to map the data sources to the use cases, and determine the relative importance of each data source to each individual use case. Business Stakeholder interviews and facilitated brainstorming sessions can be very useful in identifying the different data sources and creating a relative weighting on the potential value of each data source to each use cases. See Figure 8 shows an assessment of the relative value of each data source with respect to each use case.
Figure 8: Assess Relative Impact of Data Sources
When assessing the relative value of each data source, I like to use a scale of 0 to 4 (because I can then turn the results into really cool looking Harvey Balls). However a wider scale (0 to 10, or 0 to 100) might provide more granularity on the data source value estimates.
Estimate Value of Data Sources
We now want to integrate the financial value of each use case determined in Figure 6 with the Relative impact of each data source from Figure 7 to calculate a rough order estimate of the value of each data source across all the use cases (see Figure 9).
Figure 9: Estimate Financial Value of Data
The financial calculations are purposely rudimentary. You can make the formula as sophisticated as you want, as long as the business stakeholders can clearly understand the rationale for the formula. If explaining the formula loses the interest of the business leaders, then they will have little confidence in the results of this exercise. Consequently, err on the side of keeping the formula simple versus making it overly complicated.
CDO Toolkit Checkpoint: Where Are We Now?
At this point in the CDO Toolkit process, we should be able to answer the following questions
Have you identified and estimated the financial value your targeted business initiative?
Have you brainstormed with the business stakeholders the decisions that they need to make in support of the targeted business initiative?
Have you clustered the decisions into common subject areas (use cases)?
Have you created a rough order estimate on the financial value of each of those use cases?
Have you brainstormed and mapped the potential data sources to each use case?
Have you created a “rough order estimate” of the value of the data sources for each use case?
Have you aggregated the value of the data across all the use cases to come up with an estimated value of each data source?
We have accomplished quite a bit in support of the CDO’s data monetization role. If you have gotten this far, then your CDO is well prepared to determine the economic value of the organization’s data, and to use that determination to prioritize and focus the organization’s financial and people investments in data (e.g., data acquisition, data cleansing, data alignment, data enrichment, metadata management, security, data governance). But there is more to do. The CDO must now use these insights to drive digital business transformation.
 Gartner Estimates That 90 Percent of Large Organizations Will Have a Chief Data Officer by 2019. http://www.gartner.com/newsroom/id/3190117
 Business Initiative is a cross-functional plan or program that is typically 9 to 12 months in duration, with well-defined financial or business metrics, that supports the organization’s business objectives. For The Disney Company, it might be to “leverage the MagicBand to increase guest satisfaction by 15%” or “leverage the MagicBand to increase visits at Class B attractions by 10%.”
 Use Case is a cluster of actions or decisions, typically defining the interactions between a role (actor) and a system (process) to achieve a specified goal
Source: William Schmarzo, Dell EMC