At an early last year meeting of the Quality Governing Council (QGC) at a large American Tire manufacturer, the Head of Plant Operations put forward a view that there was an urgent need to arrest the emerging quality issues, well ahead of time, in order for them to maintain their premium positioning and raise the bar for their competition, that is ever breathing down their neck.
The view was endorsed by the Head of the Governing Council, representative of the largest stakeholder in the company, in the wake of rising consumer activism and downward EBITDA movement due to issues pertaining to inconsistent quality that had begun to seriously dent the bottomline.
A decision was taken at the meeting of the GC to put together a mechanism, an IT/Analytics intervention, to address these quality issues and it was unanimously agreed that the group would take up this problem as their priority number one for the coming year.
The group reconvened recently to discuss the progress and to everyone’s dismay, after a year and a couple of millions of dollars down the line, the issue still remained insurmountable and their challenge number one.
What transpired after the meeting last year is a case study in how not to address such issues. Here is what happened:
The group began looking for answers in earnest and had the right thoughts in leveraging Big Data Analytics. Since the field of Analytics has progressed largely as an IT application driven environment, they enlisted the support of the CIO, who with every intention of helping the group, advised deploying another Big Data Analytics application. While the idea was dead right – to leverage Analytics to do the trick, it became one more addition to a long list of applications that the organization already had!
Thus started the elusive search for that perfect application that was to be the panacea for all their quality challenges. Ironically, what was a known and addressable business challenge quickly metamorphosed into an IT challenge, one that not too many had a clue of. Their search for an ideal application led them to zero down on a particular software OEM, who proposed a delivery plan spread across 8 calendar months. This massive gestation, coupled with the uncertainty about the likely results and the skills required to sustain the application after the vendor exited their environment meant that they were setting themselves up for disaster.
The script played out perfectly to a naysayers tune. It so happened that the software OEM missed the delivery timelines by a couple of months, the blame for which both sides argued lied with the other. This was followed by frequent skirmishes between the two sides owing to expectation mismatches. Finally, once the project was handed over, delayed by several months and much to the chagrin of the QGC, it appeared the results had much to be desired.
While the above is a global phenomenon and is true of a large percentage of organizations looking to adopt Analytics, there are alternate strategies available today that help an organization derive the best results from their Analytics endeavors in the following ways:
- Get the best value for the investments
- Be prompt – bring in value quickly
- Reduce the risk for the organization
The alternate strategy entails keeping in singular focus the end game all the time, which is what matters. The end game in the above case was improving quality all the time and not getting caught up in the quagmire of Analytics applications, not a serious forte for many.
Instead, the organization could have opted for an on demand, outcome based analytics adoption, one which is agnostic of the Analytics application and the skills required to run it. The approach in this case is to hire Analytics professionals, from an on demand Analytics platform such as Cogniticx, who may leverage open source applications and provide insights for optimized decision making at a desired frequency.
Such an option offers unique advantages of being best of breed as only the best people for the task work on your project, on demand. The turnaround time for results and effective decision making is the quickest in this case as the focus is on providing the right insights at the earliest, instead of implementing an application.
The above, coupled with huge cost savings that accrue on account of non-ownership of applications, their yearly maintenance contracts, their obsolescence and the expensive resources that need to be hired and retained, tilt the scales decisively in favor of the latter approach.
The world of Analytics, on demand, with its boundless opportunities beckons. It has never been easier to leverage it!