Deriving actionable insights from massive amounts of data is the entire point of business intelligence. For years, businesses have teamed with high-priced consultants and software vendors to glean that one, special piece of information that would change the game — win that huge deal, shave millions from operating costs, or uncover the next groundbreaking product. Yet many of us are left wondering if the way we’ve grown up thinking about business intelligence is going to work for tomorrow’s leading players?
Yesterday’s model of data analysts and software developers taking ad hoc instruction from the corner office is proving increasingly untenable in today’s “acceleration economy.” Things are happening faster than ever before, and the old, command-and-control leadership structure is unsuited for the velocity of business.
Buyers expect instant-on communication with the seller, and everyone is proverbially drowning in the deluge of data being generated every day. More data certainly isn’t the answer.
“Many, if not a majority, of businesses are just now trying to figure out the right questions to ask,” explains Marvin Reem, CIO, Bob Jones University. “To make things more difficult, we not only have to come up with the questions, we also have to build a business case for those questions.”
While conventional wisdom has advocated IT become more business savvy and team with line-of-business leaders to deploy business intelligence initiatives, many CXOs are waking up to the fact that they must empower the end-user customers to achieve the next level of business agility. To shorten the learning curve and accelerate value delivery, Reem advocates searching out help. Rather than simply outsourcing these functions, he recommends that you should, “find somebody to teach you how to fish.”
In fact, Robin Hunt, founder/partner, ThinkData Solutions, believes that a team approach to data analysis is more likely. It is “incredibly difficult to find people with a mathematics background who also understand how to frame business questions,” Reem confirms.
Age of the Brontobyte
Every person in every business is dealing with the explosive growth in data. We come up with new words to deal with the volumes of data seemingly every day, and it can be a daunting challenge for any executive to think about coping with the amount of data our world now produces.
While most of us have just settled into a level of comfort measuring digital capacity in gigabytes, data scientists believe that tomorrow’s digital universe will be measured in brontobytes. That’s 1027 bytes, and is estimated to represent a thousand times more data than the NSA or FBI have compiled on people today, combined.
Not only has the amount of data created a certain element of complexity, the types of data we now have access to are increasingly complex. Whether it be millions of data points per second generated by a fleet of connected Rolls Royce jet engines or semantics analysis requirements of Kraft foods to optimize when, where, and how to sell barbecue sauce, data complexity isn’t just on the rise — it’s off the charts.
Tomorrow’s business intelligence teams not only have to grapple with exponential data growth and complexity, they must strive to empower front-line employees and executives alike, to garner instantaneous insights.
The challenge is that most businesses are constricted by the small pool of individuals who can legitimately understand and fulfill old-world business intelligence initiatives, let alone how long it takes to develop robust capabilities that can materially deliver value back to the investing organization.
Perhaps we must move past the conventional questions we are asking. Perhaps we must ask new questions that require us to think differently about how we approach a problem. What if we could empower end-users — closest to the pulse of our business — to discern, research, and solve issues as they arise? What if we could provide a view into aggregated insights that enable more agile, data-based decision making on the front line?
How do you make something this profoundly complex simple and accessible enough to deliver successful engagements with self-service business customers?
I suggest you start by considering three paradigm shifts you will be required to embrace.
1. Elastic Outlook
One of the key aspects in coping with tomorrow’s business intelligence agenda is to have an elastic outlook. You must also be prepared to think about challenges as opportunities. Sound like 1990s management rhetoric?
Think about Lyft, Airbnb, or TransferWise, or any other disruptive play happening in the market today. Most businesses become so myopically focused on attaining internal milestones, they forget to observe how customers are asking for you to help them solve their problems. This is when complexity, waste, redundancy, lack of ready access and undermined trust conspire to rob you of your throne.
This is why the San Francisco Metropolitan Transit Authority (SFMTA) projected that Uber could put it out of business in a few years, and why Lyft is converting Uber’s driver base at a staggering pace. Uber listened to customers better than SFMTA, and Lyft listened to Uber’s drivers better than Uber did.
One of the core tenets of the acceleration economy is rapid change and disruption. You must be prepared to adapt and iterate quickly. Reem offered some telling words of wisdom, “To be successful at this, be prepared to iterate your business intelligence initiative [to cope with shifting strategies required of the business] … It has taken multiple tries to create something of value.” Be flexible in your pursuit based on the shifting sands of your landscape.
In order to accomplish this, we must dispel cognitive bias and lean on data-driven decisions surfaced through modern business intelligence methods. An elastic outlook requires us to change our thinking about how we engage with information so we can engage better with our market.
2. Information Channels
Siloed information stores are not a thing of the past. These remain a persistent reality most would consider crippling in the acceleration economy paradigm. You must be prepared to shift your paradigm beyond managing structured and unstructured datasets to dynamically structured datasets based on need and demand; time will be the currency you trade.
So, what if we re-imagined our islands of data as channels of information?
While I certainly don’t advocate maintaining legacy systems simply because it is viewed as too painful to change, we must embrace the fact that new information channels will be introduced and be extinct before we can integrate every legacy system. You won’t be able to keep up with the perpetual upgrade cycle.
Our frameworks must be robust, and able to ingest data from any and all discreet channels to surface it in a meaningful way for decision makers to act. Of course this explanation borders on oversimplifying the underlying platform required, but I believe the key issue remains a design problem focused on the challenges and not the opportunity.
This brings me to my final paradigm.
3. Executive Vision
Seventy percent of major changes fail in organizations today. This isn’t because of aging systems, poor process, or even bad people. These changes continue to fail because of poor leadership and communication. Flatly stated, executives don’t know what they don’t know, so they require strong advisors to help them plot a new course.
Executive sponsorship begins with understanding the issue. “Educating leadership to understand that … it requires their active involvement,” is one of the greatest obstacles Reem says he faces today.
Leaders have to be prepared to listen, challenge their teams, and be challenged by their teams. Good leaders get this. But let’s face it, average leaders need some help. Managing up can be as much art as science, and leaders who miss the forest for the trees have to be coaxed as much as prodded until the idea percolates to the front of their perception bubble.
Connecting the Dots
Surviving and thriving in the acceleration economy requires grit, determination, and adaptability. Leading firms harvest and exploit data-driven insights made possible through flexible frameworks that connect customers, team members and executives. Today’s business intelligence, while stronger than 10 years ago, still requires us to shift how we frame the challenges in front of us. Take inventory of your business intelligence initiatives today. They may be the most overlooked, undervalued, and misguided — yet most important — initiatives you are currently working on.
This article originally appeared in the May 2016 issue of Workflow.
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