If you don’t understand how to use data, can you be a leader of a health and human service organization? Given the importance of using technology for competitive advantage (see Building Your Tech Edge: Using The Power Of Information & Technology For Competitive Advantage and Strategy, Competitive Advantage & Positioning For Sustainability – What Are The Options?), my answer to this question would be “no.” This concept and the core elements of organizational data strategy were the focus of the presentation, How Do You Build A Better Data Strategy? Using Data & Predictive Analytics To Lead Your Organization, by Ravi Ganesan, Chief Executive Officer of Core Solutions, Inc., at the 2015 OPEN MINDS Executive Leadership Retreat.
One of the key points made by Mr. Ganesan was that, unlike other industry sectors, many organizations in the health and human service field have traditionally been “data poor.” For the executive teams of these organizations, in an attempt to dispel the confusion of working in a data poor environment, they are now producing so much data that they are once again limited in their ability to make decisions. As the saying goes, they are data-rich and information poor.
Mr. Ganesan discussed this phenomenon and the need to develop a data strategy. He noted, “This is easy to do, but it’s also very easy not to do. It is important to remember that data is a corporate asset, and if it’s that important, we need a strategy for how we handle that data.” But, to do this, executive teams first need to assess how “data mature” their organization currently is. There are four stages of data maturity:
Undisciplined – There is data, but the lack of an organization-wide tech strategy leads to a lot of data redundancy and a waste of both technology and human resources.
Reactive – There is still poor organization-wide buy-in, but there are better quality technical employees with a stronger emphasis on the process and the data produced.
Proactive – Management has recognized data as a “corporate asset” and data management initiatives have become common at all levels of the organization.
Governed – Data models are used to capture the business meaning and technical details of all corporate data elements, and the organization has adopted a “zero defects” data management policy.
|Data Maturity – Undisciplined|
|People||Few individual contributors|
|Process||Chaotic and project focused
Putting out fires
Data redundancy and wastage of resources
|Technology||General purpose tools
Minimum data cleansing and standardization
Manual quality improvement process
|Risk and Reward||High Risk; Low Reward|
|Data Maturity – Reactive|
|People||Success depends on the skills of technical employees
Individual process owners; no corporate buy-in
|Process||Stronger process emphasis; better at correcting data quality issues as they occur
Processes are focused on recently discovered problems
|Technology||Tactical data management tools
|Risk and Reward||Risk High; Reward Limited|
|Data Maturity – Proactive|
|People||Increased recognition from management on data as a corporate asset
Most areas of the organization are focused on data management initiatives
Emergence of Metrics
Focus on problem prevention vs correction
|Technology||Technology providers become strategic partners
Emergence of corporate data management group
|Risk and Reward||Risk – Medium/Low; Reward – Medium/High|
|Data Maturity – Governed|
|People||Executive support for data quality management
Operational data management group
“Zero Defect” policies for data management
|Process||Processes for data consistency and accuracy
Impact analysis for new initiatives
|Technology||Data models capture the business meaning and technical details of all corporate data elements
Standard metadata and rules
Results of data quality audits are continuously inspected,
|Risk and Reward||Risk: Low; Rewards: High;|
Once you have assessed you organization’s current data maturity and use of analytics, you can build a strategy that moves you closer to the “governed” level of data management. Mr Ganesan noted – “Data informed decision making means you must take action. You have to use the data, and you must empower the staff to do so also. Think of data, and using data as the driver in the behavior modification business. [Organizations] leverage data to create success, dramatically shortening cycles, and the competition is now someone you don’t know yet. Technology enabled businesses are the more likely to be successful in this environment.”
For more on leading with data, don’t miss the session, How To Make Technology Work For You: The Four Pillars Of Strategic Tech Success, with OPEN MINDS CEO Monica E. Oss, on October 28 at The 2015 OPEN MINDS Technology & Informatics Institute. And, if you couldn’t join us in Gettysburg, be sure to check out our live coverage on Twitter @openmindscircle #OMLeadership, and look for photos of the retreat on our Facebook page at https://www.facebook.com/openmindscircle.