Analytics Maturity: Don't Run before You Walk

Analytics Maturity: Don't Run before You Walk

StockSnap_JGBNZOZD3N_walksign_analyticsmaturity_BPYour organization faces numerous challenges as it makes its way towards analytics maturity. We are deliberately using that phrase loosely, since what that maturity looks like for your organization will be different from what it looks like at another, possibly very similar organization. There are several freely available instruments out there to help you assess your analytics maturity, and even to help identify what your ultimate goals are in this area.  But when potential customers come to us to discuss the Data Cookbook, or data governance / data intelligence in general, they are clearly aware that they are not doing as much, or as well, with their data as they'd like to.  This blog post will discuss possible data growing pains.

While specifics differ, data growing pains are often visible in a handful of key areas.

  • Data silos are still far too prevalent. Silos make it more difficult to share data, they make it more likely that data collection and storage efforts are duplicated, and at their most malevolent they actively prevent analysts from gaining access to useful data. As we have written in this space before, they contribute to shadow systems and even shadow analytics.
  • Your data strategy, if you even have one, may not be well aligned with your business strategy. A formal data strategy is, of course, not a requirement for making effective use of data. But your organization's strategy is tied to your mission, and it reflects key priorities and objectives. If your data practices do not support that overall strategy, then are they going to be seen as important contributors to the organization's success?
  • Data is undervalued as an asset, and consequently not treated with the care nor given the attention it merits. Your organization undoubtedly has standards and practices governing the acquisition and use of its financial and physical assets and human capital. While data may not be recognized on the balance sheets or as part of your financial statements, there are legal and ethical ramifications to the data standards you establish (or don't establish), not to mention issues of competitive advantage and financial success.
  • Efforts to establish a culture of data flounder, whether due to lack of executive involvement, an insufficiently data literate workforce, an out-of-date data architecture, or all three in combination. Somehow, the data you collect does not make its way into analytics, or the analytics products created by your organization don't lead to meaningful insight, or that insight doesn't affect the decision-making process. 

It turns out you need a concerted effort to support the vigorous consumption of data. Hiring data scientists and upgrading your BI stack may help you derive previously hidden insight from your data, but without the requisite levels of data literacy among your users and a commitment to practice data-informed decision making by managers, these insights often lead nowhere.

Critical to a culture of data, data governance tells us who is responsible for data and what happens to it at various points in its lifecycle.  It tells us how data is classified and what appropriate and ethical usage of data looks like. But in our view data governance must be coupled with data intelligence if it is to provide real value. If I don't know about the existence of a certain data set, then how can I even begin to ask who's responsible for it? If I can't consult a catalog of curated data products, I could waste countless hours duplicating existing work or even heading down a data dead end. If I can't validate data lineage, or figure out what the architecture of a dashboard or data set is, I may not be able to reproduce results in whatever product I develop.

We recognize that tribal knowledge, data silos, and a general lack of accountability and transparency lead to skepticism or even active mistrust of data, which ought to be one of your most valuable assets. We've deliberately developed the Data Cookbook over the years to be both a data intelligence repository and a data governance engine, specifically to help address the knowledge gaps, communication failures, and process challenges, that prevent you from using data as fully and effectively as you'd like.

Additional reporting and analytics resources can be found in this blog post.

IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance and data intelligence efforts. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.

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Aaron Walker
About the Author

Aaron joined IData in 2014 after over 20 years in higher education, including more than 15 years providing analytics and decision support services. Aaron’s role at IData includes establishing data governance, training data stewards, and improving business intelligence solutions.

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