I have just returned from one of the most targeted data governance events out there - the ASUG Data Governance SIG. This is a collection of the brightest minds in data governance brought together to help other companies build and grow their data governance and stewardship programs. As I traveled home to the MKE, I considered the common threads that resonated throughout the hallway discussions, keynotes, and breakout sessions presented over the three days. The following topics summarize a few that stuck out in my mind:
Digital and Governance; Strange Bedfellows?
It was evident from the sessions and hallway discussions that the impact of digital transformation is being felt within the governance community. New data channels created by transformational technologies such as Internet of Things (IoT), social media, and robotic process automation (RPA) will create both opportunities and challenges for data governance and data quality organizations. Characteristics like the scale, volume, velocity and variation (SVVV) of these channels differ significantly from the characteristics associated with the traditional domains of master data management and data governance. The differences will likely require governance organizations to embrace methodologies that are less rigorous and explicit to manage data quality and standards in order to meet the agility demanded by these digital business processes. Adoption of inference based or fuzzy techniques may be required to ensure that an approach which balances the value of governance with the value of the SVVV characteristics for these channels to maximize the benefit to the organization.
Measure, Measure, Measure.
The adoption of tools that provide visibility into data quality, such as SAP Information Steward, appeared to be widespread across the companies present. The visibility provided by these tools are considered a foundational step for a governance organization to be able to communicate the impact and effectiveness of data standards on business processes. The ability to quantitatively measure the cost to correct data quality issues and to model the cost impact of quality issues related to a business process was identified as a springboard to the maturation of an organizations critical capabilities. Organizations that are able to objectively present these type of insights to the the business are better positioned to take the next step of incorporating this information into process improvement techniques such as Six Sigma, Lean, TQM where baseline data and trend visibility is critical instrumentation to complete the feedback loop that drives process improvement.
Spreadsheet Governance is Dying a Slow Death (finally)
In year's past, data governance professionals have shied away from conversations about technology to support their efforts. Whether it was a question of funding, executive support, or something else - only the early adopters were eager to learn about how tools could help them accomplish their mission. This year, technology was a clear winner. More and more data stewards, business analysts, and data leaders were looking for a platform approach to get more value from their data. This market trend is also apparent in the analyst world as both Forrester and Gartner have recognized a clear information governance & stewardship application market. Step one was to begin doing something by gathering business rules and definitions into Sharepoint or Excel, but now it seems people are looking to the next step which addresses the limitations of those systems with purpose built solutions like DATUM's Information Value Management® platform.
Looking to the Year Ahead.
The governance landscape is swiftly evolving to include non-traditional data domains as well as adoption of new techniques to deliver capabilities more effectively in these domains. This evolution appears to be fueled by the success of data governance organizations delivering benefit and value to the business within the traditional master data and KPI domains. To effectively meet the demand driven by the digital transformation a discipline that historically prides itself on a "Rules before Tools" mentality may need to embrace the expanded utilization of tools to identify or enforce governance standards, rules, and policy.