For most organizations, business intelligence (BI) is one of the most important operational and budgetary priorities. It’s also one of the most frustrating. Despite being a significant source of attention and investment, business intelligence projects remain an enigma, with organizations often left discouraged by their inability to successfully achieve objectives.
That so many organizations continue to struggle with BI despite its place as a major C-level priority speaks to the notion that a series of strategic and tactical mistakes are undermining projects. More often than not, those mistakes are spurred by a number of commonly held BI myths. When bought into, these myths drive organizations to undertake sub-optimal practices that ultimately derail BI initiatives.
Here’s a look at the truth behind the five most common BI myths and how to avoid the pitfalls most commonly associated with them.
Myth 1: Reporting and Analysis are One And The Same
Many organizations fail to understand the difference between reporting and analysis. The problem starts when line-of-business leaders ask IT for a report when what they really need is an analysis. Responding to the request as it was received, IT creates a report off one of their systems. But because most reports merely organize facts based on a simple query of a given data set, they lack the level of analysis needed to provide meaningful insight. Line-of-business teams are left frustrated by their inability to quickly get the answers they need, and IT teams are left frustrated by the feeling that they’re supposed to read minds. It’s a vicious and unproductive cycle.
Self-service offers the beginnings of a solution. Providing line-of-business teams with self-service access to data that can be queried in ad-hoc fashion is a great first step toward ending the back and forth that undermines so many projects. It’s only a first step, however.
Myth 2: Self-Service Cures All
While self-service discovery tools can help alleviate the challenges outlined above, they’re far from a cure-all. Self-service tools are only effective to the extent that the people using them have access to all of the data they need. Providing access to incomplete sets of data will not only lead to incomplete analyses, but to a renewed crisis of confidence. Line-of-business teams not only need access to data, they need confidence in its completeness. They need to know they have the right data, pulled from the right sources. An analysis is of little value if executives have no confidence in it.
This is where it’s critical for IT and lines-of-business to collaborate. Lines-of-business need to clearly articulate their needs, and IT needs to create and govern an environment where ad hoc users can confidently access and combine data they know to be complete.
Myth 3: Single Platform Superiority
Many companies believe if they standardize on a given platform, their reporting accuracy will improve while total cost of ownership (TCO) decreases. The problem is data doesn’t stand still. It evolves rapidly and independent of any given platform. Take the example of social media and internet marketing. Fixtures today, these were nascent concepts five or ten years ago, and the leading monolithic platforms were not built with them in mind.
Companies dependent on a single platform can only evolve as quickly as that platform allows, and often those platforms are the slowest to adapt to disruptive changes. Businesses don’t stand still in the interim, however. If IT is incapable of adapting to the latest shifts, the lines-of-business will—independent of IT and its single-platform standard. The organization will in turn be left with numerous pockets of shadow IT, and nothing destroys accuracy, scalability and TCO faster than silos.
Organizations should take an open-minded approach to their BI infrastructure. Having a single throat to choke sounds good on paper, but in production, flexibility is paramount. Create an environment that enables rapid adaption to critical industry shifts.
Myth 4: BI Tools Can Be Forced Off the Shelf with Training
IT teams tend to purchase tools in a vacuum, without buy-in from the people who are ultimately expected to use them. They mistakenly believe employees will adopt these newly purchased technologies simply because the organization is standardizing on them. In other words, employees will use the tools because they’re being told to use them. Unfortunately, that’s not the way the world works.
Employees use tools because they want to, not because they’re told. No amount of training or standardizing will convince people to use technologies they don’t feel benefit them personally. Shelf-ware cannot be forced off the shelf, and technologies that might otherwise aid BI efforts often go unutilized while projects struggle.
A shift in mindset is needed. IT needs to get the organization to “buy in” before they buy. Instead of telling employees they have to use something, help them clearly understand why they’ll want to use it. Clearly articulate the value proposition and adoption will follow.
Myth 5: With Increased Technological Capability Comes Success
Technology alone doesn’t dictate whether a BI project succeeds or fails. Too many organizations mistakenly believe it does, however, and throw good money toward ever-newer technology solutions when their problems may have nothing to with technology. Successful BI projects happen when good technology and sound processes intersect with a collaborative, data-driven organizational culture. Companies fraught with silos and lacking collaboration across teams have bigger issues that they need to resolve before investing in new technology. When it comes to BI, success cannot be bought. It must be achieved.
Joanna Schloss is a Business Intelligence and Analytics Evangelist for Dell.