SMEs and large corporates sometimes spend millions in obtaining information but they have no idea how to value it appropriately. In many cases it could be worth much more than they think – and in some cases, much less.
This is the basis of a new argument at TechTarget, where Ron Karjian underlines the problem: we simply don’t know how to value data yet. As data becomes commoditised, he says, value will be determined by quality and not quantity. But determining that figure is exactly what businesses aren’t doing, he says. He points to a 2016 McKinsey study which found most companies are only capturing a fraction of their data’s potential value.
“It’s ironic that companies immersed in collecting, prepping and analysing big data to disrupt the marketplace and gain a competitive edge, in the end, struggle to accurately measure the true value of that data.”
So how does this happen? Most of the problems are cultural, he says.
For instance, businesses don’t have enough internal alignment, they lack a coherent strategy when it comes to data, and have no form of data governance.
The answer is simple, but execution will be complex: as global competition increases, businesses need to start applying more reliable methods to their data and keep in mind their future value, not just its present value. They’ll need to change their internal cultures to accomplish those goals.
“The greatest value may be found in scarce data, uniquely aggregated data and data that yields superior analytics,” he says. “But it’s not an either-or situation. Quality data can only be found by combing a lake that’s rich in quantity.”
“In baseball terms, today’s card of an obscure rookie center fielder may someday be worth a million. Data managers need to keep that in mind as they stand at the edge of the lake and do their daily ‘gestalting’.”
In other news:
It’s common knowledge by now that data science and analytics skills are among the most sought after in companies of all sizes. Even LinkedIn lists data science and visualisation as the skills more companies are seeking in their job applications.
Now it’s becoming clearer through venture capital deals and mergers that data science is the new king of the castle.
The Australian Financial Review has listed out several funding deals related to data science in the past year. It’s no wonder. Retailers including Myer and JB Hi-Fi have said data is a huge priority for them given the arrival of Amazon, and more companies including Qantas, Westfield and Woolworths are making investments to hedge their advantage.Just some of the deals include:
- Woolworths signing a three-year deal to send information from their 600+ stores to Skyfii
- AGL put $4 million into energy analytics group Solar Analytics in 2016
- Data Republic secured a $10 million round from Westpac, NAB and Qantas
- Local Measure raised $4.5 million for its customer intelligence platform
- Sequoia China led a $16 million round for virtual data science platform Hyper Anna
These represent a small fraction of the overall data market. The message emphasised by these deals, along with the ongoing information protection movements in both the UK and China, underline a message: when it comes to data, the money is flowing.
Worth a read:
The safety and security of the United States is now relying more on “big data”, but it’s important to understand exactly what types of data are being used and why in order to avoid confusion. The Washington Post.
The opioid crisis is reaching fever pitch. Read up on how medical analytics tools are being used to solve the problem. Forbes.
Until next week.