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Whenever I work on any supply chain process improvement engagement, I intuitively classify them as either “Routine Problem” or a “Non- Routine Problem”. A routine problem is something which has a straightforward simple solution. Other simple way to look at routine problem is where you can apply an algorithm to solve the problem – If your supply side costs are high – A cost based optimization engine used effectively will help. However “Non-Routine Problems” are more abstract, problems where even supply chain veterans do not have a simple explanation. (Another rather easier way of identifying a non-routine problem is when your boss explains you the problem and then – There is a long silence from both sides).

With the increasing complexity owing to global nature of today’s supply chains, more and more supply chain problems are falling in the latter category. Couple this with increasing number of events which can cause volatility in your demand and supply markets. Solving a “Non-Routine” problem requires a strategy unique to the problem. One of the common strategy is to think of the problem in terms of “Waste”. A supply chain is not efficient may be because potentially there is a lot of waste that has been created due to various imbalances, events, customer demands, supply fluctuations etc. That is where data analytics can play a huge role in not only quickly identifying this waste but also anticipating the future waste.

These days I am working on a “Non- Routine” problem – “Improve the production capacity utilization so as to cover up the fixed plant costs and sell the additional delta production (due to improved utilization) for a discount (so as not to increase inventory costs)- And generate extra revenue in the entire process”. I classify this as a non-routine problem because a single algorithm will not be able to solve this problem. Capacity decisions impact all areas of operations management as well as other functional areas of the organization. Also it is important to understand that the focus is on improving utilization (=Actual Output/Design Capacity) and not on improving efficiency – (=Actual Output/Effective Capacity)

Establishing an environment of end-to-end supply chain visibility leads to more efficient manufacturing, lower costs and fewer incidents of a mismatch between supply and demand. In implementing that visibility, companies look at everything from sourcing raw materials, to manufacturing, to supplying the sales channel with finished product. However, a frequently missing component in a supply chain visibility strategy is transportation management, or the not-so-simple act of getting finished goods and raw materials from one location to the next.

With increasingly tight margins and higher freight costs, even small supply chain oversights can cause unnecessary expense, in terms of scenarios like product write-offs or write-downs that may occur as a result of an oversupplied sales channel, missed sales opportunities due to an undersupplied sales channel, or higher-than-necessary costs due to a failure to monitor raw materials prices across multiple sources. But beyond that, the biggest "hidden" cost of a poor supply chain is transportation — and the cost of getting goods from one place to another may well mean the difference between profit and loss. Management of freight costs, especially in a large enterprise, becomes extremely important, and the connection between visibility of freight as a component of the supply chain, and the transportation economies that can come as a result, quickly becomes apparent — and in a low margin business, transportation economies are a vital component of establishing profitability.

Visibility isn't just a buzzword