From Data to Insight: Addressing the Last-Mile Problem

Prakash Aditham

Ask any amateur runner or triathlete and they’ll tell you that the last mile (or last several) of any endurance event is the most challenging and difficult one to cover. In the networking world, the last-mile problem refers to the speed bottleneck which limits the bandwidth of data that can be delivered to the customer. Within the information delivery network, as data travels from the source system to the data warehouse and approaches the last-mile transformation to actionable intelligence, we notice problems as well. Analysts struggle with data issues and decision-makers continue to grumble about having to make decisions with insufficient information.

As a business leader or decision-maker trying to increase the number of actionable insights, it’s beneficial to do some root-cause analysis and focus on the three major causal categories affecting the last mile: people, platform (equivalent of equipment and materials), and process.


People: The Technology-Business Divide

Information Management resources within IT have typically led the building of the information delivery network. However, IT has limited influence in the last mile of the network:  the business functions where data is transformed into actionable intelligence. In his book Zen and the Art of Motorcycle Maintenance, Robert Pirsig appears to be quoting the typical non-IT person: “Somewhere there are people who understand it [systems] and run it but those are technologists, and they speak an inhuman language when describing what they do.”

It has been decades since that seminal work, but the skill and language divide remains, causing misalignment issues and affecting throughput. Early last year Gartner issued a warning that “by 2014, fewer than 30 percent of BI initiatives will align analytic metrics with enterprise business drivers… BI will remain subject to nontechnical challenges.”

So far, successfully traversing the business-technology divide has been dependent on a few power users and business analysts (or consultants) within each function, who are in a sense bilingual and able to interact successfully with systems and IT resources. As IT budgets dwindle, some business leaders have begun creating dedicated IM teams strongly aligned with the business and staffed with such resources.

This organizational power shift is also borne of the latest survey from Dresner Advisory Services, which found that 54% of BI deployments fall under the purview of business units, rather than IT departments. It was in fact Howard Dresner (formerly a Gartner Group analyst) who defined Business Intelligence as “concepts and methods to improve business decision-making by using fact-based support systems”… back in 1989! It might have taken over 20 years, but we finally see business taking the lead in Business Intelligence.

Platform: Software Solutions That Are Business-Friendly

Till recently, even those BI solutions billed as being “self-service” appeared to have been designed by technical resources for tech-savvy resources. The established BI vendors seemed to assume that data in the database or data warehouse was ready to use and only needed to be queried, sliced/diced, and presented in tables and charts to facilitate good analysis. No wonder, then, that Excel became the default business choice for data analysis. In fact, it remains a popular choice because of the flexibility it offers in aggregating, manipulating, and cleansing data.

Here, too, power is shifting to the business user, thanks to intuitive data visualization solutions from the likes of Tableau and QlikTech. These solutions can be deployed with no IT setup or technical training—and drive almost immediate productivity gains. Gartner confirmed this trend in its 2013 Magic Quadrant report: “This emphasis on data discovery… accelerates the trend toward decentralization and user empowerment of BI and analytics”

Process: Artistry

There’s one significant difference between the last mile in a marathon and the journey from data to insight: it is the transformation needed in the latter. This effort is equal parts art and science and requires several different elements like domain knowledge, analytics, visual design, and decision science to come together seamlessly to make an objective case for action. The Academy Awards recognizes the feat of taking a 300-page novel or manuscript and transforming it into a compelling two-hour visual story, with Oscars for Best Adapted Screenplay, Cinematography, and Direction. In our view, data visualization practitioners deserve the title of data artists, because their efforts in transforming gigabytes of data over weeks and months of effort into a single presentation or dashboard is no less of an artistic feat. We need more of them, while not forgetting that several different players make the overall journey possible.

In summary, when the right mix of skilled resources, creative processes, and intuitive technology comes together, bottlenecks disappear and the message shines through, informing your audience and illuminating the best path forward.

Prakash Aditham is a member of Slalom’s Information Management Thought Leadership Committee. For more information, email the team at

About Prakash Aditham
I am a management consultant with a passion for Strategy, Analytics and the Art and Science of decision making. Trained in the sciences and operations management, I have come to believe that for success in the real world, a reliance on data or technology is no substitute for creative problem solving and strong leadership

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