In 1946, a year after WWII ended, Ford Motor Company lost $60 million (~$700 million in today’s dollars) in just the first eight months. Henry Ford II had just taken over since his father passed away and his grandfather was no longer fit to run Ford; and he knew they were in trouble. So he called upon a brilliant group of men who had just saved the US billions in military expenses during the war. If you know the story, you know this group of “Whiz Kids” was integral in turning Ford around and arguably revolutionized Detroit and business as a whole. Possibly the most famous was Robert McNamara who went on to hold the top spot at Ford for a few weeks before being handpicked by JFK to serve as the Secretary of Defense.
What did they do that Ford so needed at that time? Analytics. During a time when decisions were made based on experience and intuition, the Whiz Kids didn’t know anything about cars. They had to rely solely on facts and data. For the Defense Department and for Ford, they set about collecting massive amounts of data, analyzing it, and then making decisions based upon that data.
Peter Drucker is occasionally attributed with the statement “if you can’t measure it, you can’t manage it”. Though it seems Drucker never made that exact statement, Drucker did write:
“It should indeed be an invariable practice to supply managers with clear and common measurements...soon enough to make any changes necessary for the desired results.”
This quote highlights that data needs to be easy to understand, consistent, timely, and actionable. This is supported by the MIT Sloan Management Review report, "Big Data, Analytics and the Path From Insights to Value,” which found that those who believe “analytics differentiates them within their industry were twice as likely to be top performers as lower performers." In line with Drucker’s statement, the study found that the top three obstacles to using analytics were lack of understanding, lack of time, and lack of skill. To be useful, analytics must be clear, timely, and actionable.
This was a driving force behind the design and implementation of Bomgar Analytics. Another article in MIT SMR, “How Fast and Flexible Do You Want Your Information, Really?” came to the conclusion that “Generating a report from an organization’s data usually demands intervention by IT professionals, which takes time — weeks or months in most cases.” We believe that this is unacceptable and can end up doing more harm than good (which is worse no data or stale data?). This statement from an Information Week article titled “What’s Next In Analytics” captures our intentions:
Analytic apps are entirely about insight and decision support. They generally include … predefined data models, dashboards, metrics, and reports that make them faster and easier to deploy than apps built from scratch. Vendors create them with input from industry experts, drawing on best practices and industry benchmarks. That's reassuring to customers, who otherwise would face the long, risk-fraught process of gathering requirements, building consensus on functionality, developing custom apps using a general-purpose BI/analytic suite, and then hoping--more likely praying--for user acceptance and adoption.
With Bomgar Analytics you have preloaded dashboards built by industry experts using the latest best practices. And, you have the same easy-to-use toolset as our developers to create and modify reports and dashboards to suit your unique business needs.