Data literacy is the backbone of data culture, and increasingly of business success. It is ironic that many companies, regardless of industry type, tend to think about the data that they need to run their business, to make decisions, to be more operationally functional, and to engage their customers more effectively, as an afterthought.
This sounds counterintuitive, but in my experience people’s primary thought is often, “What technology do I need to put in place to make data successful here?” This order of priorities inverts the importance of data. It also means technology choices are often made that do not support the business-data need. Organizations do need data technology, but the primary focus should be on what’s pumping through the technology, the data itself, as well on the business insight needed to support the business now and over the next several years.
Data is oxygen, not oil
Yet I continue to see data being treated as more afterthought than the primary focus. This is often evident in the confluence of efforts between the CIO (and sometimes the CISO) and individual business units to pick up the slack of a data initiative as the tech stack starts to roll out. The problem, as they start to use these tools, is that no one has agreed on a coordinated plan for the data outputs that are needed – across views or within BUs – in order to help them actually glean the benefits of that technology.
This kind of a technology-first approach can lead to people getting stuck, and sub-optimal results with their data. It also can lead to heavy investments in data infrastructure and business applications without a clear definition of the business strategy, the insights needed to ensure the strategy is on track, the insights required to shift strategy, or even how to know with confidence that you’ve achieved the value you expected from your investment.
From a literacy standpoint, we hear all the time that data is the new oil. But harvesting oil and making it useful immediately brings thoughts of technology to the forefront. I think it’s more productive to think about data like oxygen. It's not something that we need to mine. It’s in the air we breathe, and it's something we must have on a day-to-day basis to maintain health and to thrive as an organization. Data as oxygen is not an optional mindset. It’s something that needs to be a primary mindset.
Where data leadership comes in
If I look for the source of this data-second phenomenon, the problem often starts with the Chief Data Officer. Without a consistent definition of the role – or a lack of the role altogether – the focus of the CDO can’t become sticky. If you look at job descriptions posted online, you’ll see what I mean. It’s not merely that the CDO job reads as a bit overwhelming. It’s that the task of managing data as a strategic asset, or operationalizing data governance and quality, so often comes after establishing and delivering technologies to unlock value in defining what a CDO does – or even in the complete absence of defining which business strategy or need necessitated the technology shifts to begin with. This is where the CDO should be operating: bringing data to the forefront and serving as the glue between business, product, technology and workforce strategies.
Data leaders should stick to a few basic questions before unleashing more technology:
- What do we need data for, what are we trying to do as a company, how do we know if we have done it, how do we know where we need to focus?
- How does data come into our company, how is it disseminated through the organization, and how does it move back into the world?
- Where are the weak links in our workflows, governance, access, and security?
- Are we using our data ethically and respecting customer privacy?
- Which processes should we amend to become more focused on our data versus its technology containers?
Technology is a means to an end, a thriving data culture, not the end in itself. You can bring in tech all day long, but tech alone isn't going to help you actually get to what you want, which is the data. And until you and your data teams and business leads start to position data-first as an innate thought process, you may continue to see the same gap between goals and outcomes.