As awareness around supply chain functions has grown, so has the software applications available to address these functions. In fact the supply chain has been among the most expanded solution area for ERP companies during the last decade.
However, unlike the transaction processing ERP systems, the supply chain functions tend to provide a decision support tool that can be complex. Consider demand forecasting, inventory planning, replenishment planning, transportation planning, bid optimization — these are all areas that actually provide the users with modeling, evaluation, and analysis tools for real-life scenarios rather than simply automating transaction processing. Therefore, these and other supply chain solutions routinely utilize techniques such as statistics, time series analysis, linear programming, mixed integer programming, dynamic programming, decision trees, probability, queues, data mining and so on.
Putting the power of real science to work behind these solutions improves the solution quality, and allows these solutions to model real-life scenarios closely, consider a large number of parameters that may affect the results, and leverage ever expanding computing capabilities to provide solutions within minutes making close to real-time changes possible.
But it also increases the complexity of these solutions, and requires that companies employ people with the right skills who are capable of using such solutions through training, academic background, or both. And that is where most companies appear to lose all their commonsensical ability to judge the value of their investments. There are far too many implementations where the businesses have chosen to spend millions on the best of breed solutions but then pulled back when it came to invest in quality of people who would be using these solutions and actually make possible the solution ROI. No wonder ROI on software solutions has always been questionable even though real results can be achieved with some common sense.
Suppose you spent a few millions buying a jet, you would most certainly invest in an experienced jet pilot, rather than trying to teach your chauffeur on how to fly that damn plane. Almost all large corporations own their private fleet of jets these days, and the pilots and other crew to go with these planes — always without question. Now consider the same corporation investing the same few millions on a high-end demand forecasting system that utilizes sophisticated statistical forecasting techniques, and requires a few people with doctorate or masters in statistics to set up the system, tune the forecasting parameters, review the forecasting errors/trends from time to time to ensure that the system is running at its very best and providing good forecasting projections. While most of the users of this system could be people with average academic and professional experience, but a few of the super users controlling and tuning the system had to be statisticians. Suppose also that the solution vendor is naïve enough to mention this during the sales pitch, where do you think it would go? Chances are such an open admission of skills required to run the system will not go down well, and such naïveté will cost the solution provider the business.
How many times have you heard the refrain that if the system requires a PhD to be run, then that is a problem. But the fact is that some systems are complex, and they do need highly skilled people to run them, tune them, and keep them in good shape. And just like the example with the jet above, these systems do pay back in terms of saved time, increased data accuracies, objective decision support, scenario playing and other similar capabilities that are impossible to achieve manually, or by using systems that don’t quite provide the capabilities to keep them simple.
On the other hand, not everyone may need a jet either. Therefore evaluate your needs clearly, and if you do need a system with all the power of science and mathematics behind it, go for it, but also remember to plan the right people and skill-set to go with that!
Don’t undermine your technology investments, make sure they are leveraged with the right people behind them.