Business Intelligence: The Moa of the Enterprise

by in Marketing, Sales


Prominent painter, Salvador Dali, once said, “Intelligence without ambition is a bird without wings.” That is, intelligence can only go so far. Without an impetus to put it to good and actionable use, IQ is rather unavailing – similar to a bird without wings, constrained to the ground, and unable to take flight.

Business Intelligence (BI) has become a popular discipline in the enterprise sector. Indeed, BI tools offer much appeal. They help us make sense of large collections of data and can inform our decisions and actions. For executives, the implications are diverse and manifold, from helping to identify high and low performing employees, to honing in on promising product lines, to pinpointing new areas for growth, etc.

The hype around BI certainly seems well founded. The novel “Analytics at Work: Smarter Decisions, Better Results” cites cutting-edge research that suggests that BI systems contribute to the success and competitiveness of the modern enterprise. Organizations are already spending $14B on BI software each year, with the overall BI and analytics market slated to grow to $20B by 2019.

Yet in today’s enterprise environment, BI tools can be likened to a bird lacking wings – like a Moa, a wingless bird that once inhabited the islands of New Zealand. Unfortunately, despite the promise of BI tools, they have yet to reach their full potential in propelling businesses to new heights. In an especially powerful slap on the wrist, Gartner, in its 2015 Magic Quadrant for Business Intelligence and Analytics Platforms, moved all BI venders previously located in the “Leaders” quadrant to the left quadrant in terms of “Completeness of Vision.”

Several factors help shed light on why BI tools have yet to reach their full potential:

They’re time consuming

The main appeal of BI is speed and the ability to make sense of large volumes of data in near real-time. For companies to truly reap competitive advantage, they must be able to rapidly distill the big data at their disposal, generate dashboards to communicate the results, and hone in on actionable next steps.

Regrettably, today’s BI tools still require a lot of legwork on the part of the user, especially when it comes to generating dashboards that effectively communicate results. 45% of business and decision-makers report time concerns involved creating/updating dashboards. They get lost in the toggles, data filters, metrics, etc. Until dashboard and report generation is intuitive and straightforward (facilitated by features such as drag and drop filters, customizable fields, default templates, etc.), BI will never reach its full potential. Ease-of-use is critical: BI tools characterized as “very easy to use” experience an internal adoption rate of 35% compared to 22% for tools classified “very difficult to use”. It’s almost mind boggling that it takes, on average, more than six days to build reports using traditional BI tools. Until this time is curtailed, the BI Moa will remain grounded.

They’re reactive

Oftentimes, business leaders know what they want to optimize for (e.g., market positioning, retention rate, customer satisfaction, etc.), but don’t know how to use BI tools to achieve these objectives. Far too often, leaders don’t know how to make sense of the trends, patterns, and KPIs outputted by BI tools.

Until BI tools become more “intelligent” and predictive (versus reactive) in helping business executives formulate questions, adoption levels will continue to fall below their potential. In an ideal world, BI tools will incorporate data science capabilities. They’ll be able to sift through the volumes of data and give users recommendations as to which questions to formulate to achieve top-of-mind business objectives. They’ll proactively identify where things are potentially going awry or could be optimized and then serve up recommendations. They’ll help business leaders answer the “so what”and hone in on actionable next steps. This is far from today’s reality: 64% of business and technology decision-makers have difficulty getting answers from their dashboard metrics.

They depend on data quality

“Dirty data” stifles the potential of BI tools. If the data inputted into a BI tool is “dirty” (i.e., inaccurate, incorrect, contradictory, etc.), the results generated by BI tools will be ill-informed. Ideally, BI tools are able to identify when a Salesforce field has a spelling mistake or when a financial report is stymied by an inaccurate calculation and prompt the user to correct the field. “Blind data” also limits the potential of BI tools. If all data points relevant to a decision aren’t accounted for, the results will be limited in scope and effectiveness. Most BI tools on the market today integrate with only a select few data systems – typically MySQL, Oracle Database, and Microsoft SQL servers. Best-in-class BI tools ought to incorporate all data points relevant to a decision, including marketing, sales, and financial data points. In today’s data-driven world, data lives across many disparate systems. Cutting edge BI tools will support deep integration capabilities with a broad suit of enterprise applications, including Salesforce, Marketo, QuickBooks, Google Analytics, Zendesk, etc. They’ll also integrate with third-party databases (the likes of Hoovers or D&B). This will also offer the added benefit of helping unearth dirty data by identifying situations where internally-generated data may be at odds with external-generated data.

They’re not mobile friendly

Mobility is an essential, though often overlooked, feature of any top tier BI solution. Today’s workforce is a global one: mobile access to work information boosts employee engagement and productivity. BI tools cannot afford to ignore the mobile optimization trend gripping the enterprise software applications world. 42% of companies plan to deploy mobile BI. Mobile technology will inevitable boost adoption rates because data is accessible at the user’s fingertips and can be accessed anywhere – during customer visits, at home, etc. Best-in-class BI tools will cater to the mobile platform by optimizing for a smaller screen, crafting an intuitive user interface, and optimizing for bandwidth usage. This will help ensure healthy adoption levels: nearly 80% of enterprise mobile apps are abandoned after their first use.


The potential of BI is enormous and the top performing companies recognize it. According to Forrester’s Business Technographics Global Data And Analytics Survey, 2014, high business performers (identified as those with 15%-plus year-over-year revenue growth) planned to allocate 38% more of their technology budget for BI than their slower-growing peers and competitors. However, until we overcome the current limitations of BI tools, the Moa will continue to remain grounded. It will exist but will not reach the heights it is capable of.




About The Author

Rebecca Hinds
Rebecca Hinds - View more articles

Rebecca Hinds graduated from Stanford University in 2014 with a M.S. in Management Science and Engineering. In 2013, Rebecca co-founded Stratio, a semi-conductor company developing infrared sensors. The company was selected by the Kairos Society as one of the 50 most innovative student-run businesses in the world.