Supply chain optimization: 3 tips you shouldn’t ignore

<!–Supply chain optimization–>Here are a couple of time-tested observations about supply chain optimization:

1)   It works best as a well-defined journey

2)   Few people seem to realize this

Of course it’s tempting to assume that supply chain optimization is a simple matter of ‘getting it right’ and flipping the switch. The problem is that ‘getting it right’ is never simple because reality isn’t simple.

Imagine for a moment that you’re the logistics director of a large logistics company that’s about to implement automated optimized planning. The system you’re considering will ensure that all your resources are planned in ways that optimize your chosen KPIs. (I’m using logistics in this example, but the principles apply to any supply chain optimization challenge.)

What do you need to know to give the project the best chance of success?

Almost by definition, all highly successful optimization projects succeed because they’re aligned with the company’s priorities, operating reality and expectations. Here are my top three recommendations for making sure this alignment takes place.

(1)              Define your priorities

Is there agreement on what’s really important to your business? For example, how will you handle the competing priorities of customer service and cost? Should delivering on time always outweigh the cost of doing so? What weights will you assign to conflicting KPIs?

Before you do anything else, define what a good plan looks like in terms of your chosen KPIs.

(2)              Check the feasibility of optimized plans

Fast forwarding to when you actually have your system in place, the next recommendation harks back to my previous comment about reality being far from simple. In most cases, there are hundreds – perhaps even thousands – of tiny rules that produce unacceptable consequences when broken. For example, if the system generates an optimized transportation plan that ignores a simple constraint affecting a couple of customers, planners may well have to start making manual adjustments. Each adjustment will have planning repercussions that necessitate other adjustments, and before you know it the benefits of optimization have been lost.

Before going live with automated optimized planning, your best planners should check and re-check the feasibility  of optimized plans that have been generated with various data sets. Expect to discover quite a few rules that should have been incorporated in the optimizer but weren’t.

Often it’s only when planners see what the optimizer has created that they realize, “Oh yeah, there’s this customer with strange docks that can’t accommodate our C-type trailers.” Or “Oops! We forgot to mention that there are certain stacking rules. Product B may be placed on product A but not the other way around.”

N.B. This isn’t about asking planners if they would have created different plans. (Different doesn’t necessarily mean ‘better’.) It’s simply about planners combing through the optimized plans to determine whether or not they are feasible.

(3)              Benchmark the optimized plans

The number of unique rules and constraints that must be considered often rules out an apples-to-apples comparison with an industry benchmark. No one really knows what the best possible plan is. All you have to go by are the results your planners are achieving without optimization.

So use those results.

To set a useful (and by that I mean challenging) benchmark, get your best planners to create the best possible plans with decision support but without the aid of automated optimization.

Allow them to pick their data sets, give them access to any number of colleagues, and give them as much time as they need to arrive at the best possible results.

The optimization system should meet or exceed these results within the time limits required by the business.

Planners should then be invited to improve these optimized plans. If they succeed, the insights gained should be used to improve the optimizers.

. . . . . . .

Supply chain optimization is about adding significant sums to a company’s bottom line by ensuring that every single decision brings the company closer to its goals. Of course there will always be day-of-operations disruptions that require manual tweaking and re-optimization, but an effective system must be able to incorporate all your rules and constraints. This ‘perfect fit’ is crucial if supply chain optimization is to live up to its promise of creating plans that are both feasible and optimized against your chosen KPIs.


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