In our blog series, we’ve spoken about how digital transformation often starts with discovering hidden insights within your business, as well as uncovering how your people are critical to driving change, even as AI and automation seem to be threatening jobs.
The role of analytics is often a confusing one when it comes to transformation. Analytics are a key bridge between all of these other DX elements and the (hopefully) beneficial decisions you make within your business. Part of the challenge, however, is that people disagree on what analytics comprises.
For some businesses, ERP, BI and spreadsheets may represent the extent of their analytic investments. If you’re a bank, however, these systems may work for certain functions, but won’t help you predict what offers someone will accept (and whether these profit the business), whether they’re committing fraud, or whether they’ll ultimately pay (or settle) an amount that is now more than 60 days past due.
Like big data, it’s not for lack of investment that businesses aren’t getting value from analytics. Often, it’s how all the pieces fit together. If you’re collecting and analyzing all consumer responses to your marketing offers, are your analytic models consistently being retrained to help you make better decisions regarding those consumers in the long run? Or are you simply just collecting information, analyzing a lot of noise in addition to valuable data, and making largely past-looking predictions about what to do next?
Similarly, if your powerful prescriptive analytics software is accessible by only a few analytic gurus in your organization, chances are that that tool will be confined to initiatives that can’t scale to the real-time needs of the business — and just as critically, don’t account for the knowledge embedded in your domain experts.
Closing the Gap Between Data and Decisions
For any business that needs to figure out “what do we need to do with analytics” as part of the DX journey, think of it this way: You need to find faster, smarter and more value-inducing ways to get from the data to decisions (and actions) rapidly. Analytics are key to that process. Analytic tools — their sophistication (and ease of use), their ability to get leveraged by not just analytic experts, and their integration with other tools — will go a long way in helping you uncover insights, at a speed that eclipses anything you could do before.
If you’re not a Fortune 500 company, if you’re just starting out or simply haven’t gotten far with analytics, you’re not likely to suddenly start making DX-powered decisions overnight. Instead, you might want to figure out specific areas of your business that would benefit from analytic augmentation. Using manufacturing as an example, adding optimization to the mix to enhance your production planning or load building (as one global food producer did, to the tune of $35 million in savings) might be a good place to start.
“Land and expand” is a key principle for DX. While the lure of a “digital platform” is hard to resist, businesses should be thoughtful about what this means within their enterprise. Cracking the code on a hard-to-solve problem often leads to applications with their own problems. The optimal digital platform allows each succeeding application to occur faster — with fewer issues, more collaboration across silos, and ultimately faster ROI.
Your DX Journey, Done Your Way
If you’re in business at all, your business is digital — at least to a degree. To map out the full journey, you need to start with an absolutely crystal-clear vision of your business as it stands now, from your employees and consumers to your infrastructure and aspirations.
There’s no roadmap to reinventing business; there are only little steps and huge leaps, surprising discoveries and sometimes failures. But with the right blend of people, data, analytics, machines — and the right mindset — you’ll develop a living, breathing entity that is uniquely your own.
Learn More About Advancing Your Digital Transformation
Download our white paper, The Future of Deciding, to read how businesses are going beyond basic analytics and data science to digitize on a larger scale than ever before.
Read the other posts in this series: