Four Q’s to Ask Before You Invest in Data Analytics



By Michael Cochrum, CUBI.Pro

I’ve worked with dozens, if not hundreds, of organizations on data analytics projects.  Most often, I encounter my clients at a point of heightened frustration, having spent weeks or months and thousands of dollars to solve what they perceive should be a simple analytics problem.  Unfortunately, some organizations simply give up and retreat to an intuitive decision-making process that is irritatingly slow and notoriously inaccurate.  If I had the opportunity to consult with your organization before you embark on your data journey, here are four questions that I would ask about your organization before proceeding on a journey to data-driven decision making.

Does Your Leadership Support Data-Driven Decision-Making?
Data Analytics and Business Intelligence has become a bit of a fad to talk about, especially since Harvard Business Review named Data Scientist the Most Sexiest Job of the 21st Century in 2012[i].  Who doesn’t want to have a sexy job?  As a trained Data Scientist, I know I’m happy with it.  But, all that glitters is not gold.  There is a big stretch between being excited about the possibilities of what data analytics promise and the reality of fully integrating data into an organization’s decision making.
The gap between hope and application is leadership.  Your organizations leadership must be willing to adopt data-driven decision disciplines and insist that every major strategic decision be supported by relevant and meaningful data analysis.  Entrenched leadership with a practice of top-down management find it difficult to let loose of the HiPPO (Highest Paid Persons Opinion) decision culture, but it is necessary.  If your organization’s leaders doesn’t share your enthusiasm for data-driven decision making, understand that decisions supported by data analytics will be limited to your domain and will often conflict with intuitive decisions made by others without supporting data.

Is the Organization Data Literate?
No one wants to be tagged as illiterate under any circumstances, but it is not unusual for an organization that has not relied on data-driven decisions to not have focused on hiring people who have a high degree of data literacy.  Data Literacy is defined by the ability “to use, understand and manage data”[ii].  Data literacy goes beyond reading reports with charts and graphs but requires that decision-makers know how to evaluate the significance of information and make the appropriate business decision.  It also mandates that the business know how to collect and store data so that it is accurate and available to be used in decision making.  A data literate organization intentionally gathers data with the purpose of using it in decision-making.  Your organization may find it helpful, during the transition, to enlist the help of experienced third-parties to facilitate the training of existing employees and define the required skills of future hires.

Does the Organization Have an Enterprise Data Strategy?
Often overlooked and discounted, it is critically important that your organization develop an Enterprise Data Strategy (EDS) once it has determined that it wants to undergo a transformation to a data-driven decision culture.  An EDS will assess stakeholder requirements, inventory current data sources, map data integrations, define key performance indicators and measures, identify data governance, and create a roadmap for transformation.  Often, data analytics will emerge in an organization as a hodge-podge of departmental initiatives which tend to conflict with decision making at an enterprise level.  Having a strategy in place will help the organization understand how data can be integrated into decision-making at the highest level.  It also provides transparency into how the organization will be managing the transformation so that individuals don’t feel left out, or get disappointed, waiting for their needs to be addressed.

Is There a Single Person or Entity in The Organization Empowered to Govern Data?
If your initial response to this question was something along the order of assuming I.T. would take up your organization’s data cause, you may not fully respect the difference between Information Technology and Business Intelligence.  I.T. resources in most organizations are charged with keeping operational technology up and running and secure.  While I.T. may understand the technology used to store data, they may lack the experience in the business domain to understand how to integrate data into decision making.  However, if you choose to leave data governance with I.T., understand that you will need additional resources and you can’t just add to their existing work load with existing resources in place.

Ideally, you will have a Data Scientist in your organization who will play the role of data “traffic cop”.  They will be responsible for understanding the organizations total data footprint, be able to integrate data from disparate data sources, and ensure that business users are getting actionable data that can be used in decision making.  If your organization can afford this specialized resource, it is important to understand that their role is empowered to take action and force the sharing of information across the enterprise.  In other words, it is important that the Data Scientist has influence over all departments.

In the absence of a dedicated Data Scientist or Chief Data Officer, I like to recommend that smaller, resource constrained organizations create an Enterprise Data Governance and Engagement (EDGE) team.  Playing the role of Chief Data Officer, the EDGE team collectively contributes their individual domain expertise and work with one another to ensure that the transformation to a data-driven decision culture is even and balanced throughout the organization.

About the Author:
Michael Cochrum is CEO/CDO of CUBI.Pro, a company that specializing in working with financial institutions on data transformation projects.  Michael has worked in the financial services industry for almost 30 years and with, or in, credit unions for the last 20 years.  He holds a B.S. in Data Analytics and earned his MBA from Texas A&M – Corpus Christi.  You can email Mr. Cochrum with questions at michael.cochrum@cubi.pro or visit the www.cubi.pro website.



[i] https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century
[ii] https://www.slideshare.net/Library_Connect/slides-research-data-literacy-and-the-library-70689154

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