Presidential Campaign Sparks Parallels With Data Governance Challenges
For those of us here in the U.S., an extremely important Presidential election is coming in November. For months, Americans have been inundated with spin doctoring and politicking at its worst from both campaigns. We all hear words like "conservative" and "liberal" used as insults, and rhetoric from both sides say how important it is to foster bipartisan collaboration – while doing everything in their power to alienate those from other political parties.
Putting aside my frustration at seeing nasty politics and posturing to appease the lowest common denominator take precedent over critical debate about issues that truly matter to Americans and our allies, I can’t help but marvel at the similarities in politics at the national level to the organizational politics many of us experience on a daily basis within our own companies. More specifically, how the need to adopt data governance to ensure the usefulness and security of critical enterprise data is inhibited by internal politics and posturing.
A brick wall often exists between business and IT where the business must throw their requirements over the wall and 6 months later IT comes back with a technology solution that may or may not actually meet those requirements. Sometimes the business plays the role of the "bleeding-heart liberal" requesting capabilities and insights that IT feels are unrealistic and undeliverable within a reasonable time and budget.
In these scenarios, IT is often viewed as the "inflexible conservative" that sees new requirements as an insult to the existing systems that they have shed blood, sweat, and tears to deliver and this pride of ownership of the current state makes requests for new technology by the business a threat. But these roles are often reversed. At times, IT is the liberal looking to implement cutting edge or next generation technologies (e.g., SOA, MDM) to allow them to better support and scale ever-changing business requirements, but because the conservative business does not have visibility into the precarious state of their IT infrastructure they don’t want to finance these improvements because "if it ain’t broke, don’t fix it!"
When discussing data quality and trustworthiness, the finger-pointing so common in national politics is also standard practice in large enterprises. The business will often blame IT for data quality issues that they see in their enterprise apps and analytical environments, because the business assumes that if IT is building the pipes, they should also be responsible for the information flowing through those pipes.
In this case, IT (rightly so, mind you) expresses frustration that only the business should define and measure data quality since the business owns the processes and decisions that are enabled with this data. This lack of business sponsorship and support is cited as one of the major inhibitors to successful implementation and adoption of ERP, CRM, business intelligence, master data management, and other data-centric IT investments.
The presidential candidates spin rhetoric such as "bipartisan cooperation is critical" out of one side of their mouths while their campaigns spend more time finding new, creative ways to embarrass their opponents than addresses critical issues. This same passive aggressive/blatantly aggressive behavior plays out within our corporations too where senior executives say "our data is a critical corporate asset that must be protected" but provides no resources, prioritization, or sponsorship to actually change behaviors and processes that are putting this data at risk in the first place.
While there is little I can do to change the behaviors of our sometimes flawed political process here in the U.S., there are a number of recommendations I can provide to changing the tone of your campaign to improve the quality and usefulness of critical enterprise data. These include:
Identifying top-down executive sponsorship early to ensure cross-functional business and IT participation is mandatory, not voluntary.
Limiting initial scope of your data governance program to addressing only the data that supports the business processes most critical to your company, and to those business stakeholders most willing and able to articulate how poor data quality is impacting those processes.
Staffing business and IT stewards with business analysts that can effectively translate business requirements into technology solutions. These individuals are the bridge that must ensure business and IT collaboration. See The New Business Analyst for more on the business analyst role.
Developing a compelling business case that can quantitatively measure the benefits of investing in data quality and governance. See A Truism For Trusted Data: Think Big, Start Small for best practices in developing a bottom-up valuation approach as well as Building The Business Case For Master Data Management for help in aligning your trusted data initiative with your company’s strategic priorities.
In the meantime, I’ll look forward to seeing everyone at the polls on November 4th!