Don’t Let Tools Drive Enterprise Data Strategy

June 30, 2014 Dennis D. McDonald

By Dennis D. McDonald

Tools outstrip policies

Isaac Sacolick’sFriend or Foe? How Microsoft Excel 2013 Creates New Data Governance Challenges is a refreshing look at the challenges organizations face as the capabilities of data management tools outstrip the policies and processes for governing how such tools are used.

Sacolick focuses on Excel 2013 and its increasingly sophisticated integration and analytical capabilities. As a recent adopter of Office 365 tools myself I see both the power and drawbacks of such tools. Not only are they powerful and easy-to-use but they also greatly simplify data sharing given built-in cloud integration.

While I’m old-school enough to want to know where my files are stored, I also have to admit I’m still sorting through how to best use Office 2013. I’m also a regular user of Google Drive and how it synchronizes both local and cloud-based data files; figuring out how to use these products in tandem while participating in several geographically distributed development projects can be a challenge!

Needed: corporate data strategies

Sacolick focuses on corporate data governance. An obvious take away is that organizations need “corporate data strategies” to help manage how critical data are created, managed, stored, manipulated, and accessed. Developing such a strategy will not be easy given how pervasive data are in organizations and how powerful — and decentralized — the tools are for working with data.

You need to weigh the costs and benefits of different data strategy variants including tight top-down control, a loose Federated governance process, or even no control at all.

Traditionally there has been the need for tight control over what some might referred to as “core data” including customer IDs, transactions involving personal, health, or financial data, and proprietary product or design information. At the same time, people and systems need to be able to talk with each other while simultaneously ensuring that some level of standardization and quality control is maintained over the data. Sacolick points out that tools like Excel 2013 can be used to manipulate and modify such data in ways that can escape the monitoring and control of an official or centralized governance process.

Tightening controls doesn’t always work

Tightening controls over what tools can be used is one approach. I’m reminded of the “tool cages” sometimes maintained in factory assembly-line operations where, if you need a specific tool for a specific maintenance task, you go to the cage and check out what you need to perform a task; woe betide those who don’t return their checked out tools at the end of the day!

Such an approach may not work in today’s decentralized software and data environment. Vendors such as Microsoft might not view it in their best interest to minimize tool proliferation, plus many users will already be making use of data sharing services that can operate “under the radar” of the CIO.

Don’t start with the tools — start with the processes

One challenge for developing a data governance process that supports an organization’s enterprise data strategy is that you must first develop an enterprise data strategy and then decide how and what to govern. Just focusing on the tools that people use for manipulating, sharing, and accessing the data only scratches the surface of the problem.

What you really need is a corporate strategy’s coverage of all the functions that impact or are impacted by data. A good discussion of this issue in terms of data-impacted functions is presented by Jim MacLennan in Who Should Own Digital Strategy:

Product design and business planning
Process design and customer service
Interaction design
Solution design and development
Technology infrastructure
Project and program management

Tool vendors don’t necessarily try to focus on all these areas. They can’t afford to if they want to close a sale in a reasonable length of time. It’s up to the organization to provide the leadership, not the vendor.

One way in strategy development is for organizations to address all these areas and then figure out where the tools fit in. The downside of such a top-down/strategic approaches that it takes time to develop and implement. Meanwhile, staff are “voting with their feet” by adopting and using tools that are outside the control of and difficult to integrate with legacy systems and processes. What to do in the meantime?

Don’t slam the barn door

First, I would not start by “slamming the barn door” while the horses are escaping. I would start by understanding how the people in my organization are using data and what I need to be doing to help them to be more effective and productive.

I would also establish a support unit to assist staff who need help by offering tools and services that are compatible with my data architecture and with my data strategy. In other words, I would build and “sell” a better approach to users who might have already developed analytical models and tools by offering an alternative service that balances desired flexibility to innovate with the need for standardization and control where it is really needed.

Granted, this is more of a collaborative approach to strategy than a more traditional hierarchical approach. Plus, taking into account what people are already doing does not obviate the need for a comprehensive enterprise strategy and the possible need, down the road, to transition from one solution to another. And as already noted, you will always need to protect core data assets especially where privacy and competitiveness are involved.

Bottom line

Failing to involve real-world data users in the process of developing and implementing a rational organizational data strategy, given the power and flexibility of today’s data tools, is an approach that is bound to fail.

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