Of course I’ve timed it. (What else would you expect from a supply chain planning professional.) The quickest route to work for this Parisian involves hopping on a bus and then catching a train.
Outside peak hours, life becomes more complicated as buses and trains are less frequent. Then it’s worth turning to the local transport authority’s online planning tool for the best choice.
The problem, of course, is that there’s no guarantee that the ‘optimal’ combination of public transport will actually get me to the office in the shortest possible time. The quickest combination may also be one that’s unacceptably vulnerable to disruptions. Why pick a particular bus-train combination if a five-minute delay on the bus leg means waiting hours for the next train?
One of the best dramatizations of the tension between optimality and reality can be found in that childhood favorite, Around the world in 80 days by Jules Verne. It’s a real page turner and a big part of its appeal lies in the constant pressure the hero faces to make the right trade-off between ‘time’ (the most efficient plan) and ‘weather’ (a robust plan that acknowledges the possibility of disruptions).
For those whose recollection of the book is rather hazy, here’s a quick introduction. An Englishman called Phileas Fogg bets he can go around the world in 80 days. He creates a thoroughly efficient plan based on various timetables, and sets off on his travels with a skeptical French domestic. Of course it isn’t long before delays and disruptions start playing havoc with his perfect schedule.
The ending is brilliantly unexpected: time has a trick up its sleeve for the timetable-loving Englishman – but I’ll say no more.
In Mr Fogg’s case, the lack of robustness of his plans meant constant expediting in the form of heavy tipping and the use of exotic, but locally appropriate, alternatives such as an elephant and a wind-powered sledge.
For those of us who prefer our drama in books, here’s a proven three-step process for maximizing the robustness of plans and minimizing expediting:
- How accurate is your data? For example, is your data well integrated and easy to maintain? Are there sanity checks?
- Does the plan fully and accurately capture your business model and all your constraints?
- How well does it enable you to meet your KPIs?
- Can planners build buffers into their plans strategically? Hint: Can they simulate the effects of various disruptions to develop a feel for where and how to place buffers such as safety stock, workers with particular skills, and extra time?
- Can planners explore tradeoffs between efficiency/optimality and robustness – swiftly and easily?
- Is your planning system well integrated with execution data?
- Do planners have immediate insight into all the consequences of a disruption?
- Are planners supported with visual feedback about the effects of their decisions on KPIs and capacity constraints – even before they implement those decisions?
- Do planners have immediate access to plans that are optimized against multiple goals? Can they choose which parts of the plan to re-optimize?
Way before Murphy’s Law was invented, the pragmatic French were already using the same word for ‘time’ and ‘weather’: ‘le temps’.
How well is your business coping with the competing demands of both kinds of ‘le temps’?