an abstract of data stacks
Many organizations fail to properly leverage business intelligence in a way that fosters revenue-driving action. PHOTO: beachmobjellies

Data is valuable: worldwide revenues for business analytics are expected to grow from $130 billion in 2016 to more than $203 billion in 2020.

But some companies remain unclear on the true capabilities offered by these analytics.

Despite all the resources brands typically allocate to the facts and figures generated by their business, many organizations fail to properly leverage this information in a way that fosters revenue-driving action.

In fact, according to Experian’s Global Data Management Benchmark Report, only 19 percent of US companies have optimized their data program with defined success criteria.

When data is only used for things like risk management, fraud prevention and compliance-related activities, its awesome potential is never realized and money is left on the proverbial table.

But business intelligence can also successfully tie profits and losses back to everything from promotional campaigns to the weather patterns affecting individual store sales.

With billions of dollars at stake and a worthwhile ROI on the line, it is time for brands to take a closer look at what the numbers are really trying to tell them.

At the root of this problem lies inertia.

Hindsight Over Insight

With the inception of business analytics came the “just show me what’s happening” mentality as owners and operators tried to wrap their minds around looking under the hood with a magnifying glass.

About a third of these leaders now concede they lack the knowledge, skills or staff to help them properly understand and manage their business intelligence programs.

As a result, many organizations rely on early approaches towards reviewing performance data that merely scratch the surface without any expectation of going deeper into uncovering and addressing the related implications.

'A Lack of Creativity'

There is also a general lack of creativity to blame.

The approach to analyzing numbers is often a black and white one that inhibits using them to tell colorful stories.

But in the right hands, data can be positioned to create a narrative that makes analytics an art form, melding tales of historical patterns with a prediction of the future, while including prescriptive, real-time recommendations for course-correcting troublesome factors.

Technological Barriers

The last culprit in this insight-blocking cocktail is technology. Until very recently, analysis did not move at the speed of business. For most organizations of any significant size, this is still the case, despite the rapidly growing availability of data integration tools.

But here, we come back to the power of inertia and lack of creativity: most organizations have yet to fully invest in analytics for revenue-driving action, and many still do not believe in its potential for business transformation.

For most organizations of any significant size, this is still the case, despite the rapidly growing availability of data integration tools.

But here, we come back to the power of inertia and lack of creativity: most organizations have yet to fully invest in analytics for revenue-driving action, and many still do not believe in its potential for business transformation.

Pushing Data to Deliver

The key to unlocking the powerful potential of business intelligence is overcoming not only the silos that keep it fractured but also the typical delay in bringing it all together.

With the tremendous amount of information pouring in, it is not terribly surprising that 25 percent of organizations admit to struggling with managing either the volume or variety of data collected.

Too often, different departments or units report their revenues in ways that are never properly combined therefore unable to offer a 360-degree view of the business landscape.

The first step then to making data work for you at maximum capacity is to streamline everything gathered into one single source of truth with a synchronized process that is done in real-time.

Depending on the organization, that can be a lot of data. You can’t change what you can’t see so informed decision-making requires reporting from every available source.

For a large chain with hundreds of locations, this may mean billions of records including high-level marketing investments and operational costs all the way down to individual sales transaction details.

Ultimately, when there are actionable insights to gain that can deliver directly on growth initiatives, it is worth investing in an infrastructure that can quickly collect, clean and analyze incredible amounts of information.

In-House vs. Experts

The reason more companies have not pushed their analytics programs this far can be that it’s difficult to do correctly in-house as one out of every three businesses feel they lack the internal resources to assure the accuracy of what is collected.

Expertise on the subject of data collection is not innate to most organizations so establishing an internal team to lead a process refinement would be a difficult effort at best.

That’s why it is now common to outsource IT. Unless you run engineering for Dell, you probably aren’t in the position to ask any of your employees to fix their own computers.

Unless you’re a big data company, you likely need a third-party to properly crunch millions of numbers. Ideally, a third-party offering a platform which takes care of the integration, warehousing, benchmarking, analyzing, forecasting, and recommendation creation, because the fewer responsibilities on your company’s plate the more resources you can dedicate to acting on the insights generated.

Business intelligence has greatly evolved since the days of simply adding tabs to Excel spreadsheets to track the activities of a few different departments at once.

Now that you can include things like weather reports, marketing dollars and KPIs in the mix, there is simply too much information to be contained that easily.

To tell a good data story, you need all the chapters. And none of it can fall through the cracks.

The right way to make sure a return on your analytics investment is to enlist a platform able to collect, synthesize and distill vast amounts of information, returning it to you in a way that makes it easy to act on with high-level learnings that contribute to the bottom line.