Good Data is a Lifestyle Not a Project
(Please note that any and all comments below reflect my personal views and do not represent the views of my company nor any organizations I'm affiliated with).
Next week, I'm fairly certain that at some point I'll be sitting though yet another meeting where someone complains about data. Generally these complaints revolve around sweeping generalities: "I can't find the data I need....our data isn't good....we don't share enough data." If you have any involvement with data at your company, I'd suspect you hear similar types of refrains. I've heard a variation in nearly every place I've worked. And it only seems to get louder as the expectation that "data science" will provide the silver bullet for unlocking mysteries of business development becomes more extreme.
So, why is this issue seem so pervasive ? It stems from a variety of reasons. In some cases, the people making the issue lack the requisite SQL and technical skills to obtain the data on their own and are lacking the means to manipulate and analyze the data. Mostly though, the problem stems from a fundamental misunderstanding of how to create a data centric environment.
Data challenges are not resolved through a one-time project or ad-hoc task force. Creating a proper data environment is a lifestyle and not a project. By lifestyle, I mean a commitment to developing key sets of master data; the "golden sources" that are used by other groups throughout the firm. In addition, the lifestyle also involves the use of "data stewards" who ensure the quality and integrity of the data is sufficient for the key purposes of either managing ongoing business processes or one-off analytical projects. Along with the data stewards are the "data operators" who have the ongoing responsibility to set up the feeds and production environment.
Getting senior management committed to this lifestyle presents challenges. It isn't an exciting topic to dwell upon and much less exciting that talking about a new form of "alternative data" that will possibly present a new competitive advantage. Aside from building the business case it also requires having the proper organizational structure to make it happen.
On the positive side, I've had the good fortune to be part of initiatives that created the right lifestyles around single reference master data. I can say from person experience that committing to the "lifestyle" choice of maintaining good instrument reference data resulting in a major source of success for a variety of activities that spanned transaction processing, reporting and research.
So, think about developing more of a lifestyle approach towards improvements in your data environment and less about a one-time project. The progress will not happen overnight but the benefits will perhaps provide a decade or more of improvements to your capabilities.
Knowledge Manager | Capturing, Codifying and Conveying Knowledge for Stakeholder Success
5 年Great take, Michael - I'd like to hear more. What's the biggest challenge to cultivating a lifestyle around quality data? Getting the data in the first place? Curating the data once its in-house? Provisioning that data to critical systems? Achieving agreement and commitment to certain data definitions? Thanks for the article.
Yes, it is definitely a challenge to get the necessary attention placed on the need for quality data.? I think the problem is that it's sometimes difficult for people to appreciate the 'cause and effect' relationship between good data and good performance.
Enterprise Data Management | Enterprise Risk Management | Data Governance | Data Integration | Data Strategy | Pre-Sales | Engagement Manager | Client Proposals
5 年Great article! I am currently dueling with architect that thinks we can run the organization by expressing everything as unstructured data.
Director Learning Events @ Optum | Agile Transformation Leader
5 年Absolutely true! Organizations don’t understand the notion of garbage in will likely mean garbage out. So many efforts and agreed to levels of standardization in ETL is at times a complex & dull discussion. When teams can’t find what they are looking for they end up creating datamarts driving overall confusion & a messy data map for the future. Up front data governance is a necessary evil to allow teams to maintain agile delivery!
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5 年Agreed, am working on the precursor argument, which is why data does not get the level of commitment it deserves.