Business technology is only just beginning to catch up to customers’ changing UX preferences.
Even as consumers continue to gravitate en masse toward mobile computing, wearables and personal assistant applications powered by artificial intelligence, some business solutions providers have doggedly persisted in designing their systems for desktop platforms, instead of designing them to be mobile-native.
Many have also undervalued the need for data democratization. Born of their clients’ lingering data security concerns, limited budgets, and other factors, some business analytics providers are still focusing on designing solutions that bridge one silo with the next. But wouldn’t it be better to design and advocate for solutions that break down data silos by fundamentally eroding them.
So what’s the problem with that?
Consumers are employees. Employees are consumers.
These are not mutually-exclusive behavior spheres. If people are used to increased mobility and connectedness in their personal lives, they’ll want it in their occupational lives, too. They’re not going to feel comfortable in a work environment that still seeks to limit their productivity to the office.
Indeed, virtual workplaces are expected to become a widespread phenomenon within the next 3 years. Business will be conducted by virtual companies that operate wherever their workers are at a given moment — not where companies assign their employees seats.
Over the course of the 2020s, physical offices are likely to become rarer — a legacy of the “old way” of doing business that will be far less important in a workforce dominated by the digital natives of the Millennial and ascendant iGeneration.
Savvy businesses are already recognizing this and facilitating their employees’ mobile productivity by fielding business intelligence solutions that are designed to foster collaboration, irrespective of distance. And those businesses are savvy precisely because they’ve learned how to determine the right time to leap forward with a new technology — and when to hold back.
Distinguishing tech fad from natural tech selection.
To be fair, there is a clear reason why some companies that have failed to fully embrace the mobile revolution. And that’s because they wanted to see proof that mobile is the new normal before investing in a tech outlay that could end up being a costly misstep.
“Our understanding of the shifts that disrupt businesses, industries, and sectors has profoundly improved over the past 20 years,” Adner and Kapoor noted in the Harvard Business Review. “But the timing of technological change remains a mystery.”
Many of the technologies making headlines today (virtual reality, artificial intelligence, cloud computing, etc.) were heralded 25 years ago as imminent game changers, but were painfully slow to mature. Some early adopters and investors got burned.
But the problem wasn’t with those concepts in and of themselves — it was with environments that weren’t well-suited to those adaptations. Historically, we’ve seen this play out in other fields. Let’s consider, for instance, the advent of home fluorescent lighting.
Despite its clear advantages over incandescent light bulbs vis-à-vis efficiency, cost and fire safety, fluorescent lighting was, for decades, almost exclusively relegated to use in industrial and institutional buildings. Why? It seems irrational that consumers wouldn’t want to save money in the long-term.
The reason comes down to environment. When fluorescent lighting first became commercially available, most consumers’ homes were fitted with sockets for incandescent bulbs. They didn’t want the hassle of replacing their hardwired, screw-in light fixtures with new fixtures designed to accommodate pronged fluorescent tubes.
Add to the equation the relative inconvenience of changing a tube, and aesthetic factors that favored incandescent bulbs, and homeowners’ reluctance to adopt fluorescent lighting becomes understandable.
Flash forward to the late 1990s, when screw-in fluorescent bulbs were developed that fit extant fixtures. Suddenly, lighting underwent a transformation. Incandescent bulb sales shrunk. The more efficient technology finally fit in with consumers’ preferences. Without dependency on homeowners’ willingness to rewire their homes, it flourished in the home market.
“In assessing an emerging technology’s potential, the paramount concern is whether it can satisfy customer needs and deliver value in a better way,” Adner and Kapoor argued.
“If the answers suggest that the new technology can really deliver on its promise, the natural expectation is that it will take over the market. Crucially, however, this expectation will hold only if the new technology’s dependence on other innovations is low,” they wrote.
Mobile BI will become the norm because employee-consumers demand it.
Mobile devices have been “convenient,” from the standpoint of portability, for well over two decades. Now, though, they’re convenient in their performance level. And that’s caused consumers to dramatically shift their UX preferences away from desktops and laptops, toward smartphones and phablets.
Efficient mobile computing can proceed completely independent of desk-based platforms. Cloud capacity, wireless speeds and wireless network coverage have matured to the point that mobile systems have been freed from the necessity of interfacing with hardwired data storage. They can thrive on their own.
We’ve reached the Mobile-Native Age.
As Madison Square Garden’s Director of Engineering, Alexander Kharlamov, recently wrote in Forbes:
“No matter how good the technology is, if it's not easy and fun to use, it's doomed to failure. The iPod did not have the best technical specs among MP3 players, but it won because it had the best UX. I believe the same scenario will play out with new tech -- like virtual reality. Whichever device consumers will like using the most will win, while other options will go the way of Google Glass.”
Companies (and the solution vendors that support them) must recognize this and adapt to a tech “ecosystem” that’s already radically reshaping business intelligence generation into a decentralized process.
Your employee-consumers demand mobile BI. They demand an easy, intuitive UX. And they demand that their UX should improve over time, through the power of machine learning.
It’s time to meet those demands head on.