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Data Mastery – An Area for Analytics Leaders to Obsess About

Data Mastery is having expertise on what business value you drive with data, as well as the expert knowledge on the state of that data. Data Mastery is one the 5 Differentiators for Advancing Analytics Maturity.

More Than 10,000 Hours

For what it takes to be an expert (to develop expertise), I would look no further than the ‘Expert on Experts’, the late Anders Ericsson. His research was made popular by Malcom Gladwell in ‘Outliers’, making the concept of 10,000 hours of practice a common phrase. It’s essential to note that he identified that the quality and deliberate intent of those 10,000 hours mattered. Both quality and quantity matter. Considering 10,000 hours is about 5 years of 40-hour work weeks at full focus, it’s clear that very few people in very few companies are data experts. This is not meant to diminish or dispirit anyone, but rather help frame up that the road to data mastery is not short. Of course, very few companies need all of their staff to have both deep and broad expertise in data. All firms, however, do need a few folks who have deep and broad expertise in data and all firms need to have folks with deep data expertise in focused areas across functional and business lines; for example, marketing data or data governance or data storage. Leveraging the cumulative value of this expertise? Well that’s a topic for another time.

Business Before Data

Notice that after “expertise” in the definition above comes “business” despite the fact that “data” dominates the first few sentences of this piece, not to mention the title. Business comes before data for several reasons. You’re infinitely more likely to get the right data and the right amount of data if you are clear on the business objective. You’ll also have a better understanding of the needed quality level of that data. The era of Big Data in the previous decade(s) led many to believe that if you had all of the data you would find the answer in it. And then you could back into the question. That didn’t work. Even in the current era of crowd sourced tools, 3rd party data, and cloud storage, data brings cost and complexity before it brings benefits. As Sara Spivey, CMO of Bazaarvoice smartly observed in this piece on Forbes, the accumulation of data in Marketing reached such peaks that companies hired 3rd parties to come in and stop different functions in their own company from accumulating the same data. They basically hired private data police. That’s a sign that things have gone very wrong. Not only does this redundant data drive additional spending, but often different vendors structure the data differently leading to battles for who’s data is correct, creating inaction. As much as anything it’s a sign that data expertise is severely lacking.

Being clear about the business objective also leads to a needed focus on the most used and most valuable data at the heart of a company’s business, its own data - its own in-house customer, transactional, product, etc. data. While there is definitely potential value in the rich data created by geospatial, IOT, social and mobile data, too often companies chase mediocre competence in these areas at the expense of becoming expert in their own data. Consider this; if you currently can get $100 of value of out of your own data and can improve 10%, then you get 10 extra dollars. If you’re new to a data set like social data and currently get $20 from it, you need to increase by 50% for the same value. Yes, the math is completely made up, but the principle applies; becoming an expert on your own data likely has as much more value than becoming a better amateur on a new data set. Additionally, since your internal data will likely remain the foundational data of all your work, your expertise in it actually increases your capability with external data.

Wash Your Hands, Manage Your Data

As a data person, as an analytics leader you need to develop your expertise on the nitty gritty of data. Your team (or closest partners) must be the experts on the state of the data - where it is, who can access it, and how trustworthy it is. This includes having expertise on some of the fundamentals of data, like data governance and Master Data Management (MDM). These topics are a bit like hand washing – they are often overlooked; we like to assume they’re in place and they’re absolutely essential. Even before COVID, experts in population health cited hand washing as the number one factor in reducing disease spread. It is such common knowledge that everyone knows how important hand washing is so that people just assumed everyone acted accordingly. Of course, we have recently learned that most folks were not doing it enough or correctly. Put plainly, that’s the same with most data management activities, you are not paying them enough attention and likely not doing it right. For inspiration on how to rediscover your energy for these essential tasks check out Scott Taylor, The Data Whisperer. And once you’ve done that, clients that have access to our research library can check our recent Data Strategy paper which outlines 10 steps to get your data house in order.

Developing data mastery is not easy and there are no short cuts, but if you want to be your company to be a leader in analytics, it’s necessary.

About Drew

Drew has close to 20 years of experience, having worked on both the business side of analytics, leveraging insights for business performance, and on the delivery side of analytics driving the use of enterprise analytics. As the lead of Analytics Leadership Consortium, Drew drives engagement with analytics executives and top analytics practitioners in the IIA Community to help them lead their firm’s journey to analytics excellence.

Before joining the IIA, he led the Enterprise Data Analytics and Governance function at IKEA’s global headquarters in Europe. He leveraged analytics in various leadership roles across the IKEA value chain in both the United States and Europe. He received his MBA from Penn State and his undergraduate degree from Boston University.

About The Analytics Leadership Consortium (ALC)

The Analytics Leadership Consortium (ALC) is a closed network of analytics executives from diverse industries who meet to share and discuss real world best practices, as well as discover and develop analytics innovation, all for the purpose of improving the analytics maturity of their firms and securing the business impact they deliver.

You can view more posts by Drew here.

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