The Texas Parks and Wildlife Department (TPWD) told me how it built an analytical culture in a recent article. During our conversation, TPWD Data Analyst John Taylor also emphasized the importance of a unified data management approach. He explained:
In my experiences working in many different organizations, efficiency and effectiveness suffers from a natural tendency for data and business processes to be segregated into silos corresponding to segregated business units.
As a simple example, each unit may create its own codes for an inventory item, and these codes may not match across business units. To realize the potential of business intelligence analytics in any enterprise, everyone must agree to a common method of communicating about shared data. BI actually offers a way to develop translations of shared data, rather than forcing a change in business processes that can be quite disruptive and result in resistance to that change.
In the above example, if proper cross-references can be created among shared inventory codes, different business units can continue to use their own codes uninterrupted, while translations of those codes can be surfaced to the other business units. These sorts of simple acts of unification with minimal disruption can foster more unified thinking and approaches, and encourage smaller business units to consider the needs of the larger enterprise in the actions they undertake.
From a wider perspective, similar positive results can occur if silos of data management activities and responsibilities are broken down and encouraged to be shared among business units. We have been working hard to do this at TPWD. We have been seeking ways to encourage different business units to combine their data management approaches and efforts wherever clearly shared needs can be identified.
As part of this effort, we are trying to encourage folks to rethink their beliefs about ownership of data and responsibilities. Agreement on an approach to shared goals maximizes data access, as well as collaboration or delegation of data management activities. This leads to efficiency and is effective for the shared interests of all involved.
To do so requires everyone to recognize a clear benefit to their own self-interests. Many times, that is difficult to establish; it always takes some degree of demonstrated proof of concept, communication of a shared vision and trust – often it also requires much patient, although persuasive, discussion. BI has been much more than a tool for unification of data management; it has been the main catalyst for unification.