Operations profitability and agility, through data and AI

Operational Intelligence in 2015 – An Idea whose time has come!

Mar 9, 2015 9:45:13 AM / by Ratheesh Raveendran

It was one of the last evenings of February 2015 and I was catching up with two of my buddies over beer. We spent the better part of the evening talking about old times. But given our association with technology, the conversation inevitably veered to what 2015 has in stock for the industry.

I reaffirmed my faith in the continued rise of data driven decisions, and added that 2015 could be the beginning of the decade when Operational Intelligence drives quantum gains in productivity. My friends were not impressed. They argued that many ideas that are driving "Data to become the new Oil" have been around for a while and that only a small fraction of the projects were bringing in tangible business benefits.  They felt it was mostly hype propagated by a handful of software vendors in connivance with a fawning analyst community. This post is based on some of the arguments I made to buttress my view.

Many ideas & inventions have taken decades, if not centuries, before they became common place in our lives. For example Motorola showcased a working cell-phone way back in 1973 – almost 2-3 decades before it transformed our lives.  The history of Operations is no different. Many practices that are taken for granted in factories, distribution hubs, contact-centers etc. have spent many decades in obscurity before mainstream acceptance.  This is because the existence of a problem alone is not sufficient for the solution to be widely adopted. An environment that makes the solution viable or a necessity is needed to push it beyond cases of specialized usage. Few examples from the Operations world are listed below.

Period Idea quo Problem solved Environment that pushed the idea
1800-1810 Eli Whitney popularizes the concept of interchangeable parts in the manufacture of muskets. The idea has been around since the 11th century. Repair was unit specific and not equipment specific. Defective equipment had to be sent for customized repair or replaced. Both options are expensive. • Popularity of mass-manufacturing
• Improvement of measuring gauges
• Improvement of machining accuracy through tools like lathe & milling machine
• Electrification
1900-1920 Ransom Olds and Henry Ford popularize the Assembly line. The idea was in use for many decades in various industries. Difficulty in keeping up with the demand for mass manufactured products. • Improvements in conveyor & lift technology
• Development of intelligent layouts for tool placement
• Popularity of division of labor
1950-1970 Operations Research sees widespread application in business. The idea can be traced back to work by Charles Babbage in the 1830s. Optimization of business models with large number of constraints and variables was difficult. Manual solutions were sub-optimal. • Experience from successful application of Linear Programming in World War II
• Development of the Simplex algorithm by George Dantzig
• Development of computers
1975-2000 Leap in adoption of MRP and, subsequently MRP-II & ERP. MRP had been around for more than a decade then. Scheduling workers, planning procurement & inventory, arranging capacity etc. in large scale manufacturing. Estimation errors were becoming very expensive. • Adoption of mainframe computers for Accounting & Inventory Management
• Availability of accurate BOM and other planning inputs
• Increasing Competition

As in all the examples listed above, the use case for Operational Intelligence has always been there... efforts have always been made to separate the problem transactions from the ones that will go with the flow; it was always well-known that real-time visibility was the perfect antidote for fickle demand and other unpredictable aspects of operations. Coming to the solution side, many of the statistical and mathematical techniques used to predict exceptions have been around for a very long time.

So what has changed... or in other words what is the new Environment that is going to give Operational Intelligence its final push to Glory. Let me recount a few I had told my friends that evening:

Additional Data Sources: Even the best algorithm can come to a naught in the absence of good input data. In the last few years the prevalence of RFID tags, additional sensors on equipment, increased usage of GPS etc. has led to a manifold increase in the amount and variety of data collected. More importantly, these new sources provide data at higher levels of accuracy, and can be harnessed in near real time.

Cross-Enterprise Openness in Information Sharing: In recent years there has been an explosion of consumer mobile apps that rely on access to information like address book, location information etc. The benefits of this new openness have had an impact on Enterprise decision makers too. Many more Enterprises today are willing to share information with their partners because they understand that the value chain efficiencies will percolate to them as well.

Drop in Memory prices & development of In-Memory Technologies: Thanks to the drop in prices, the amount of memory available in computers today is unprecedented. The increased memory availability has been supplemented by powerful new technologies like columnar databases and in-memory analytics.


The New Environment Enterprises are facing today is defined by the 3 trends mentioned above. Additional data due to the first two means that many new analyses can be carried out with existing algorithms (ideas). The third trend allows these analyses to be carried out much faster than what was possible earlier – actually in near real-time. In the world of operations, Analytics driven Insights are extremely time-sensitive. So the analyses are of no use unless the user gets to act on the insights almost immediately after the relevant event. That was the primary reason for the lukewarm adoption of Operational Intelligence in the past.

With these 3 trends, the environment for the giant leap in Operational Intelligence usage has been set. We at OpsVeda are not the only ones seeing this convergence. Almost every customer we talk to are aware of these developments, and in many cases it drove them to get in touch with us. So, in a nutshell... awareness of the problem is there, the solution is well known and the environment for success of the solution is also in place. What can stop Operational Intelligence now? It is indeed an idea whose time has come.

Welcome to the (Chinese) Year of the Goat – 2015!


Tags: Enterprise Software, Business Execution, Operational Intelligence, Real Time Analytics, Columbus, Business Agility, Innovation Intelligence Paradigm Analytics, Supply Chain Visibility

Ratheesh Raveendran

Written by Ratheesh Raveendran

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