How to Foster a Culture of Data-Savvy Managers
Big Data is a buzzword, and for good reason: If used correctly, it can help organizations make decisions that lead to higher profits, great collaborations, and other business benefits. But Big Data is only useful to an organization if its employees know how to analyze it effectively.
Often the people entrusted with this responsibility are in the IT department and know little to nothing about business strategy. Meanwhile, the folks who could potentially make sense of Big Data—managers and executives—mistakenly think they lack the technical skills to be in involved in such products. But senior managers, mid-level managers and technical personnel all need to share responsibility for planning Big Data research and taking advantage of the information it uncovers, from developing a meaningful question, asking that question correctly, building an understanding of data-driven decision making, and creating a culture to implement these decisions quickly.
More than 1.5 million data-savvy managers are needed by 2018 in the U.S. alone, a McKinsey group report pointed out last year. This is because the requisite skills and experiences have not become established practices within many traditional firms, and, importantly, are being taught in only a few universities (N.C. State being one).
Here at CIMS, we’ve been working with collaborative teams at organizations such the Clinton Health Access Initiative, Patheon, Kelly Services, Grifols, and Quintiles to more effectively employ data analytics to improve decision making. CIMS Professor Richard E. Kouri and data scientist Chad Morris are among those leading this effort. “Working together,” they report, “we have learned that the application of computer-assisted data analytics is rather straightforward—the real hurdles are people.”
An article about their work appears in the May-June issue of the CIMS Innovation Management Report. Here is an excerpt:
Six Attributes of a Data-Savvy Manager
By Richard Kouri and Chad Morris
From our eight years working with more than 50 managers and engineers, we have identified the following attributes of data-savvy managers:
1. They listen well in order to understand the problem that senior or mid-level managers are facing.
2. They have good communication skills so that they place the problem into a set of questions that are actionable if answered; also, they make sure others understand that decisions must be made once these questions are answered adequately.
3. They understand the data analytics platform sufficiently so that actionable questions can be placed into a data model compatible with their platform.
4. They understand how to evaluate the alternative approaches suggested by the data and are able to assemble the right team help prioritize them.
5. They recognize and can mitigate the inherent biases team members will have during the evaluation and prioritization process.
6. They help managers communicate the decision throughout the organization, putting the communication architecture in place and allocating the proper resources.
The data-savvy manager will often find himself/herself allied with the other managers as they work to democratize the data-driven decision process throughout the organization. Employees, whether technically skilled or not, should recognize that data has the potential to impact every aspect of the business. The manager will be responsible for championing this message throughout the organization and begin shifting the organizational culture to one that is data decision-oriented.
A data-savvy manager must be able to structure a strategic problem and facilitate discussion in which the resolution or decision criteria are presented in an actionable fashion. As an example, this could be establishing the phase criteria for new product development to move to testing and validation or discontinuation of new product development. Using a project team of decision makers and subject matter experts, biases and alternatives to the decision criteria can be identified and formulated into a series of questions and sub-questions supported by the analytic platform and based on the decision criteria.
We believe that having the project team participate early in workshops for critical thinking and creative problem solving can help them offer insights into biases and identify needed resources upfront, thereby setting the projects up for success. This should allow discussion to focus around the strategic problem and ultimately get its buy in on the plan moving forward. Gaining agreement early on is important for establishing accountability and responsibility throughout the process.
Strategic Questions Drive the Process
We stress that the strategic questions and sub-questions will drive the analytic process and must always be clearly tied back to the business need and desired outcome. Achieving early small wins can lead to big victories toward ultimately changing the organizational culture through the demonstration of value created for the firm and others.
In the planning phase, data-savvy managers must consider how to strategically advance the data decision process. By understanding the data platform and clear objectives for the data needs, the manager will be able to communicate effectively with the scientists or engineers and drive the needed data collection, modeling and analysis, based on the desired outcome.
As for the technical platform, we have seen a number of cases where managers have made technological investments in their analytical stack based on the desired outcome and future planned applications. This was done to prevent costly investments in resources that might not provide a significant ROI and would add additional complexity to implementation and use. Having an understanding of the platform and the vision of what can be achieved, a data-savvy manager can identify opportunities to continue building out the desired analytical platform and the resources to further develop their data decision.
Maintain Data Collection
A critical component of the groundwork is to establish the practice of maintaining the data collection so that it can be applied to future work. The solution to the original questions almost always engenders additional questions. Thus, these data collections should become one of the regular tools that all employees can use when trying to address additional questions.
For example, the data-savvy manager uses these data collections, and some additional tools, in an iterative manner to orchestrate getting the right data to the right person at the right time. This is a tough, and also fun, job. Employing explicit data standards and processes early on can simplify the reuse of data for future questions.
Finally, it is critical that a data-savvy manager incorporate all of the information into the decision-making process. Whether it is information marketing will use for customer segmentation, or research and development for knowledge discovery, there must be an avenue for the information to be incorporated into the decision making process. A data-savvy manager must structure the process with the end in mind.
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