These days, most serious business plans are built on data, and most data strategies are intricately linked to business goals. It’s time to stop thinking about the two separately.
When you put your stake in the ground and say “this is where we need to be in two, five, or ten years,” you should not ask “can data help?”; you should ask “how will data help me get there?” Once the goal is set, many of today’s strategic decisions are about what data you need to get there, how you can acquire it and what to do with it once you have it.
Many are already embracing the “data-centric business strategy” approach. We have seen this develop almost in real-time at digital native companies — like Google and Facebook — which have been making long term strategic investments in capturing and acquiring data since their early days, sometimes planning years ahead.
IBM bought the Weather Channel’s digital assets — excluding the TV bit — so it could get its hands on its data. This allowed it to augmentpredictive sales and planning services.
However, data-centric strategies are not just the preserve of tech companies. Many companies and industries that made their mark in a pre-digital age are now acquiring or forming alliances in order to access strategically valuable data. Energy companies are buying internet of things (IoT) device companies to get data on customer energy use, as may be the case in Engie’s acquisition of part of Flashnet. Life sciences companies are buying or working with health platforms — see Roche and Flatiron Health and Pfizer and 23andMe — to develop more targeted and desirable drugs or support medical research. (Full disclosure: Roche and Pfizer are Tessella clients.) Automotive will, of course, be looking for any data that gives them an edge in design and manufacturing, as well as driverless cars.
Others, however, are lagging behind and may find that if they don’t accelerate, they can no longer compete.
Developing A Data-Powered Business Strategy
It is widely accepted that businesses will become more data-driven. The potential for data collection is exploding thanks to new IoT devices. This seems to be driving up demand for infrastructure that stores and manages that data, which in turn is driving the possibility of yet more data collection.
But this doesn’t mean technology alone will deliver. Many make the mistake of acquiring as much data as possible in hopes that it will prove useful at some point down the line. This is time consuming, expensive and distracting from your core strategy. Instead, businesses should first set their strategic direction, then make informed decisions about data acquisition to get there.
For example, if you are a chemical or pharma company, where do you see the future? Is there a particular product line where you have an edge, or where you have spotted an unserved demand? If so, look at how you can best capture and share research and development (R&D) data; whether you can usefully mine old data you captured before the digital age; or whether other companies or researchers have the data you need.
Perhaps your goal is to expand into emerging markets. Many companies spend fortunes making incremental product improvements to get a competitive edge in saturated familiar markets while missing the potential to shift millions of units in new markets. This is often out of fear of the unknown, but again, acquiring the right data on consumer habits and logistics can show the way and de-risk opportunities. However, that data will not fall into your lap; you need to identify it, prioritize based on business needs, and go after it.
Making Your Data Work For You
Where your company isn’t already creating the data you need, capturing it can be achieved in a variety of ways. You may be able to buy it directly. You may acquire a company that has it. You could set up collaborations to create it. Alternatively, you could find creative ways to get people to share it.
This exercise should include looking at competitors, including digital companies outside your industry who might have an eye on your lunch. Apple and Google are acquiring startups with energy and health data and may one day represent serious competition in energy and life sciences. Ask what data they are acquiring and what their strategy is, as well as what data you are terrified of them owning. That should help inform your strategy to either aggressively compete or to choose a different direction.
On the other hand, feeding all your data into a data lake and seeing what happens is not a strategic decision. This strategy can take a long time to yield valuable results and can be much more expensive than an appropriately-sized data lake driven by business needs. If your business’s future lies with a family of enzymes, biological data is likely to be more important than employee efficiency data. Strategic data decisions, like any strategic decisions, are laser-focused on the end goal.
Once you know what you want, it’s time to consider the practical stuff. What systems do you need to capture, store and share data? Will you work with vendors or build capability internally? What technical, business and subject-matter expertise do you need for each data project? How will you plan and evaluate data projects?
These steps all need technical input and tactical decisions, but they must also be guided by your strategy, as these technology decisions will define how you use data for years to come.
The point is that you need to make strategic business decisions about acquiring and using data, and you need to prioritize your approaches. You can’t kick these decisions down the road or hand them to the IT team (unless that IT team has a seat on the board). As the pace of technological change and availability of data increases, you must take the lead, or you could be quickly out-innovated.