Why Data Matters
Why Data Matters
In the world today, data is probably the thing that matters most. It can tell you before the airplane’s brakes fail. It can predict the onset of a natural disaster or forecast when you might suffer a heart attack. This isn’t a fantasy or a future state. It’s happening today.
Right now, the government is collecting data and building machine learning (ML) algorithms that can predict braking failures due to degraded runway conditions, such as a wet or contaminated tarmac. Japan is analyzing satellite imagery data of the earth to predict natural disasters. And doctors are turning to data mining and ML techniques to develop screening tools to identify high-risk heart attack patients.
At its very core, data tells us what we need to do next. Data exposes inefficiencies and disadvantages. It reveals truths about our habits and what we might do next. It opens windows into opportunity, while offering a glimpse into the future. Data shines a light on what’s possible and has the power to make it a reality. But only if you use it in the right way.
We’ve been hearing a lot about data in 2020—from scientists and economists to public health officials and business leaders. We are all collectively looking for data to give us a path forward, and the Covid-19 pandemic is making this rational inclination more of a desperate plea. “Following the data” is how we should determine case trajectories, decide when it’s safe to go back to school, and reopen the economy.
Now that we’re paying such close attention, however, we can see how data can also be inconclusive, misunderstood, and even abused. We sense now that data has a Big Data problem, opening the door to opportunists who manipulate and misrepresent data to promote their own agenda, undermining both public health as well as civil liberties.
From the politicization of data, to the growing realization of data biases and lack of appropriate investment in data analysis, Covid-19 has exposed data: its purpose, integrity and the validity of its predicted outcomes.
There is no question that the pandemic has also become an inflection point in the shift to digital. The companies that will survive—and ultimately thrive—will be the ones that realize data is their key to competitive advantage and invest accordingly. That doesn’t mean building a data lake for the sake of building a data lake. Every investment in data must solve a business problem and align with strategy.
Unfortunately, many businesses still opt for canned, pre-packaged analytics that are disparate and sequestered across different parts of the organization. They treat data like a commodity and liability—poorly managed and hidden away from business units that need it. Treated this way, data has limited value.
Using Data as an asset
The C-suite can no longer view data as an afterthought. It’s a business asset and should be prioritized as highly as revenue, customer experience and profitability.
This mindset is best exemplified by major airlines’ recent decisions to collateralize their customer loyalty programs to secure multibillion-dollar loans to ease the cash flow pressures the pandemic had placed on their respective businesses. Industry pundits estimated the airlines’ data to be worth almost 2-3 times the companies’ own market capitalization values.
But data as an asset goes beyond a line item on the balance sheet. For example, one of America’s largest grocers is selling more than just groceries. By becoming a syndicated data provider and selling its inventory and point-of-sale data, it can generate more than $100 million in incremental revenue per year.