Why effective enterprise data management is set to go mainstream in 2022
It’s been talked about for three decades—how organizations can fully harness data to drive business growth. Will 2022 be the year effective data management turns a corner and goes mainstream? We think so. Here’s why.
Business @ the speed of thought
Bill Gates penned a book in the late 1990’s with the title ‘Business @ the speed of thought.’ He used it to try to persuade CEOs of the viability of using data to drive business decision-making, perhaps unsurprisingly using Microsoft as a case study in how to do things right (nothing narcissistic about that of course!). In many respects, he was pitching to a willing audience. I don’t know of a single CEO who DOESN’T want actionable insights to drive their business decisioning. But there have been lots of challenges getting in the way of this ambition.
Herein lies the rub: Data abounds, and yet almost no insights are getting through to managers and executives. One of the factoids that Bill Gates draws on is this—‘While the typical company has made 80 percent of the investment in the technology that
can give it a healthy flow of information, typically it gets only 20 percent of the benefits that are now possible.’
The productivity of knowledge workers
Let’s now jump to another legend in the business world, Peter Drucker, described by many as the father of modern day management consulting. One of the most famous quotes by Drucker is—‘The most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the MANUAL WORKER in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of KNOWLEDGE WORK and the KNOWLEDGE WORKER.”
We know now that this productivity shortfall with digital workers comes as the result of working with analog tools. Digital workers require the means to work with actionable insights, by being gifted the ability to ask new questions. Having found better answers to questions, they then need the means to act; to make changes to the state-of-the-art to not just do things better, but to do better things.
Living with data and becoming data driven
Drucker has also said, “Knowledge workers have to manage themselves, they have to have autonomy. If knowledge isn’t challenged to grow, it disappears fast.”
This autonomy is the bit of the data management puzzle that’s been a difficult nut to crack. After all, how can you offer autonomy to workers while giving IT the control over protecting data, governing data structures, and safeguarding endpoints? It sounds counterintuitive to offer more autonomy to workers while, on the other hand, believing that IT needs to retain ever more control. But, autonomy is without doubt what’s needed to encourage information workers to work with data in meaningful ways. We are after all in the digital age. Digital workers need tools DESIGNED for Digital Work.
John Hagel, co-chairman of Deloitte’s Center for the Edge, says that firms need new architectures designed to increase the flow of information and learning inside and outside the organization’s walls.
Traditionally, the organizing principle for businesses was to achieve efficiencies of scale. Now, Hagel states that “scalable learning” must be the aim. Pursuing it begins with redesigning work environments to foster new knowledge creation – that is, to move beyond sharing what’s already known to help workers make genuine discoveries more quickly by tackling performance challenges together.”
What’s changed since 2000?
Gartner has identified that tech providers are pushing towards the development of what they call data fabrics, to envelope the various sources of data that organizations seek to harness, presenting data to autonomous users in the form of composable data.
In the last couple of years, this issue of digital worker autonomy has been hot on the minds of technologists and data scientists alike. Part of this story is the rampant growth of low code and no code software tools that negate or reduce the need for software developers to possess coding skills. But this seed change in attitudes doesn’t stop there.
These trends have been neatly catalogued into Gartner’s 10 digital trends that are neatly summarized in this article by Encanvas, the digital document company. Encanvas is one example of the innovations emerging to service this drive for digital worker autonomy, while allowing IT to maintain their governance over enterprise IT. Taking low code development one step further, these technologies equip digital workers to ask new questions by interrogating quality data presented in such a way that its reusability and value is maximized.
It is this blend of three major new ingredients, (1) the recognition that data needs to be pre-prepared to be composable by creating a data fabric, (2) that digital worker tools need to honor the autonomy use by digital workers, while (3) affording IT professionals the authority they need to govern IT data management and environments, that is allowing firms to become data driven, and thereby helping data management to go mainstream.
Will Bill Gates have his dream fulfilled of businesses working at the speed of thought? Well, Peter Drucker envisioned that the conundrum of knowledge worker productivity would eventually get rolled out in circa 2020. So, perhaps—given Gartner’s most recent marketing campaign on the efficacy of composable data as a top 5 IT priority—the forecasts of both Gates and Drucker may yet still be proven right.