Businesses have a long way to go when it comes to digital transformation.
At least, that’s the finding of a recent HCL Technologies survey which found that although 70% of businesses have a transformation plan in place, only 10% have planned everything out to completion – including their plans with data and analytics.
According to HCL, it’s all been something of a rushed process. Companies have lacked the board-level expertise they need to get these data projects over the line. They experiment, but they don’t know how to get business value from their data.
So the question remains: how can businesses make data a part of any digital transformation? According to Tech Republic, the answers are pretty straightforward:
- Make data and analytics a cultural change, not just a technical one
- Think more about long-term digital transformation projects
- Design data use around the end experience for users
- Look at the business value chain as a whole
Anand Birje, corporate vice president and head of HCL’s digital and analytics practice, says businesses need to stop experimenting and start doing.
“It’s now time to align project initiatives with a long term strategic plan for the business so there is absolute strategic clarity.”
This warning connects nicely with a similar one from Derek Russell on Towards Data Science, who says what many experts have been suggesting for a while: all businesses will soon become data-led businesses.
While many businesses would no doubt be thinking about how they can create value from their datasets, Russell offers a preliminary warning: that technology conversation can only happen by “understanding your business, how it operates, and what’s most important to your customers”.
Only then can businesses start having conversations about how to use their data. For instance, Russell says, imagine how telemetry behind just the moment to moment way we live our day could help trucking fleets decrease accidents, HR improve productivity or increase retention in the workplace, and empower universities”.
In other news:
After Amazon bought Whole Foods earlier this year, it seemed like the number of massive mergers was dwindling down. However, a $US69 billion deal between pharmacy group CVS and insurance company Aetna has been big news in the United States.
But in a sign that major mergers are now being validated by information and analytics – the Whole Foods deal did the same – CVS and Aetna say they’ll be able to create a more comprehensive service by combining their datasets.
“By integrating data across our enterprise assets and through the use of predictive analytics, we will create targeted interactions with patients to promote healthy behaviors and drive adherence, and this will further improve the quality of care for patients while also resulting in healthier outcomes,” both companies said in a statement.
Aetna CEO Mark Bertolini also said the company’s clients will be able to help reduce costs through the “broader use of data and analytics”.
Whether that will actually happen remains to be seen. But it represents a growing opportunity, and a question: can America’s complex and expensive healthcare system find some respite in the growth of big data?
Worth a read:
Sports and data have a long history, with baseball being the popular example of how information analysis can improve performance. Australian rugby is now heading down a similar path. ITNews.
From companies that make it easy to set up databases on Amazon Web Services, to tools that automate data science tasks, here are 10 of the best data startups that found some success in 2017. CRN.
Los Angeles traffic is famously slow and congested. The city is now experimenting with data to see how it can clear up its roads and make driving a more pleasant experience. Statescoop.
Until next week.