Much has been said, on this blog and elsewhere, about the importance of mobile analytics in today’s business environment. Business intelligence (BI) can’t wait for an employee to get back to his or her desk; it must be generated where (and when) a user is working. That requires secure data analytics solutions that can foster 4-D collaboration. Five years ago, they were still out of reach. Today, they are par for the course.
How are mobile-native BI tools different? Let’s look at 5 design principles that are guiding us as we develop the solutions that will power the business intelligence generation for the future.
1. Mobile BI solutions are designed for a mobile environment.
“Working from home, on-the-go, in a different city or even country has become the norm,” wrote Information Age’s UK contributor Ben Rossi. “This flexibility allows workers not only to keep in contact with their colleagues and clients, but to have instant remote access to files.”
“If organisations opt for the right tools, they can have an integrated secure file sync-and-share strategy that will boost collaboration,” he advised.
What are the “right tools?” They’re systems that are intended to live mobile.
Too often, companies are working with analytics solutions that have been designed to live on desktops or hardwired systems. Some have failed to keep up with the tech curve. Some are trying to eke out additional functionality from legacy systems. Others believe they’ve been priced out of the mobile BI market.
And those players often resort to back-engineering mobile interfaces for solutions that weren’t meant to support such implementations. They try to muddle through with makeshift mobile environments that feature questionable operability, data opacity and perpetuate a siloed environment.
We need to take the opposite approach; today’s effective business insights tools need to be designed, from the ground up, on the principle that real-time collaboration cannot be accomplished to its fullest extent only between the hours of 9 to 5, Monday through Friday, corporate HQ local time. They have to leverage the full extent of functionality that mobile devices offer — the personalization and location-based intelligence that is possible through mobile — and not just in a piecemeal manner.
2. Mobile BI solutions are easy for the average user to operate.
This is another tenet of mobile design philosophy. Mobile BI solutions should be intuitive enough for even the most novice users in your company to quickly pick up on.
The more intuitive a mobile BI solution is, the more it will promote both engagement and collaboration. A worker frustrated by a clunky, crowded interface isn’t going to perform. Worse still, he or she will become the bottleneck in the free-flow of information through your organization.
When an analytics solution helps your weakest team member elevate his or her performance, the whole company benefits. After all, a chain is only as strong as its weakest link.
3. Mobile BI solutions are cloud-first.
According to Gartner, cloud technologies will have an impact on more than $1 trillion in IT spending — a spending shift that highlights the necessity of cloud-first strategies.
The agility that cloud-based infrastructure lends is the key competitive advantage in a world where sales cycles don’t cease or slow down — and in which business consequences can play out in a matter of minutes, rather than a matter of weeks.
When a trend or anomaly is developing, today’s organizations must be able to see it in real-time, project it forward and correct their courses, so that their competitors aren’t given chances to swoop in and steal market share.
4. Mobile BI solutions are scalable and easily updated.
The cloud is leveling the playing field. It’s allowing companies to leverage capabilities that they couldn’t have afforded just a few years ago. Small and medium sized businesses can forego large capital outlays for platform builds and proprietary hardware — subscription-based, cloud solutions are now offering them the same functionality that large, global corporations enjoy.
They also offer smaller companies scalability. Solutions can be easily tailored to the size of the team, because they’re simply pushed out to your users’ extant mobile devices. For instance, there’s no need to purchase additional hardware when you bring on a new team member.
Cloud-based solutions put small businesses squarely on the tech curve. Whereas in the past, smaller enterprises had to worry about creeping obsolescence, their solutions now upgrade automatically, in real time, as their software providers roll out new patches or new versions. Cutting-edge operability is built into the subscription agreement.
5. Mobile BI solutions support data accessibility and democratization.
Siloes aren’t conducive to the generation of actionable intelligence. We’ve seen that in the defense world, and we see it in globalized business.
“Work involving analytics is difficult to share. Most tools today rely on people having the physical data on their desktops, then sending the results out as PDFs or spreadsheets,” Rossi wrote. “These results are then hard to automatically update and collaborate on.”
“Guiding people to better decisions – whether that is through more automated and connected data preparation or through more in-depth predictive analytics recommendations – should be one of the key aims for networked enterprises.”
Heard. Time wasted generating and disseminating spreadsheets, or waiting on slow-reporting departments, is crucial time lost in the marketplace.
That’s why any successful business insights and intelligence tools will foster data democratization, giving your company’s users instant access to your company’s data lake. The most successful tools are powered by machine learning that guides users to mission-critical information when they need it, where they need it.
Looking ahead to the future of mobile-based BI.
We don’t always foresee a 2-D interface for BI generation. As technology progresses, interfaces — even mobile-based — may evolve into 3-D virtual displays that can be manipulated, passed and projected across distance, to allow your employees to identify nuances or trends not readily evident in standard X-Y plots.
And artificial intelligence will likely proceed to the point that many business decisions become somewhat automated, although data security considerations will require rigorous (human-centered) control mechanisms to be designed and implemented.
But we believe the day is coming when a company’s employees will be largely freed from the day-to-day drudgeries of BI generation, like data management and reporting.
Instead, they will be allowed to focus their time and energy on concepting, design, and intuition — those intangible areas that machines can’t address. In short, machine learning could allow companies to become more human.