The missing piece of the profit economy isn’t ERP

The missing piece of the profit economy

Where are you looking for supply chain improvements?

If you want to know what went wrong (or right) in the past, look in your ERP system. The answers are right there.

But if you’re looking to add significant sums to your bottom line, it’s not the past you need to get a handle on. It’s the future. As Victor Allis, CEO of Quintiq, said in a recent presentation at Gartner’s Supply Chain Executive Conference in Phoenix, Arizona, “There are no decisions to be made in the past. But when you start exploring the future, suddenly you have all these choices. There are an infinite number of possible futures that you can still shape.”

So can you really shape the future? Do your planners have the control they need to achieve business goals?

Not all those futures are equally good for your bottom line. In some of those futures, the business has missed an enormously important order for a customer and is facing cancelled contracts. In others, you’ve ended the year with a 20% reduction in costs and a huge improvement in delivery performance.

How do you navigate all those possibilities to ensure you achieve the best possible outcome for your business?

“I’m CEO of Quintiq, but most of all I’m a guy who likes to solve puzzles.”

Dr Allis’s opening remarks at Gartner were deceptively simple – rather like the supply chain planning puzzles that businesses face daily.

For example, how difficult can it be to plan 43 deliveries with six trucks?

Intuition says, ‘No big deal!’

The math says that inspecting all the available options would be like inspecting each atom on planet earth.

So how do planners actually arrive at a good solution that incorporates all constraints and customer requirements, and maximizes efficiency?

They don’t. They struggle to arrive at a solution in which all orders are delivered on time and, when they find it, they stop looking and move on to the next planning challenge.

Large, successful companies don’t have six trucks and a few orders. They have hundreds of trucks and thousands of orders.

“So if anyone says, ‘Yes, we looked at all the options and this is the optimal solution,’ that’s… ”

First, looking at all those options is humanly impossible.

And second, as Dr Allis pointed out, there are some interesting statistics on the subject.

“One of the things we do for companies is to create benchmarks. We say, ‘OK, so you have this number of trucks. Tell us what your rules are. Give us the addresses of your customers. Give us the routes you actually run for a week. And then we’ll run it on our software platform.”

And here’s the interesting part – we have never come across a situation where we weren’t at least 5% better. Ever. We’re always between 5% and 20% better.”

Even a 7% reduction in distances traveled and a 10% reduction in vehicles used represents a huge amount of untapped optimization potential for a company with a large fleet. If you’re running a fleet of 90 to a 100 trucks your savings easily add up to millions of dollars annually.

And, in case you’re wondering, the 20% ceiling isn’t there because Quintiq – the holder of four world records in logistics optimization – is short of world-class optimization expertise. It’s there because a plan that’s at least 20% worse than what our optimizers achieve tends to be noticeably bad, and gets revised by planners. Anything less than that, and human planners are simply incapable of spotting the difference between plans that save millions and those that leave millions on the table.

. . . . . . . . . . . . . . . . 

To discover more hidden optimization potential in production and workforce planning, catch Dr Allis’s presentation on ‘The missing piece of the profit economy’ here.

To read more about Dr Allis’s views on optimizing logistics, check out ‘Groceries could be Amazon’s next killer app – if it can solve the math’ in Wired.

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  • Wijk de Vliert (Den Bosch-NL)

    Hi Everyone,

    The truck example is striking, showing that relatively easy puzzles can be extremely complex to solve. Talking about optimization puzzles, I am still looking to crack the following problem. Can you help me out?

    In my neighborhood we are organizing a so-called ‘walking dinner’ to stimulate integration and get to know those people you rarely speak. 60 couples will participate and 3 courses will be served (starter/main/dessert). Following rules apply resulting in some level of complexity:

    – 45 couples will be asked to serve 1 dish/course for 8 people including themselves.
    => food will be served at 15 locations and people will eat a 3 different locations that evening
    – when not cooking/serving couples are to be seated at different locations
    – You must dine with 7 different people, each course.
    – And of course we want to balance male/female at each table!!

    Any suggestions how to schedule this? Many thanks in advance for your input!!

    • David Rijsman

      I got notified of this question yesterday so sorry for the late reply but we had a quick look at the problem and this is what you can do (probably easier to give everybody a location where to go but this will demonstrate a bit how we solve these things):

      Imagine the tables in a circle (although they are at different locations), and number the chairs around each table 0 to 7.

      Now let everyone go sit at a table, such that:

      – males sit on an even numbered chair and females sit on an odd numbered chair;

      – for each table the people on chair 0 and 1 form a couple, those on chair 2 and 3 form a couple, etc.

      For the remainder of the dinner, the people will only sit on chairs with the same number as they are currently sitting on. This ensures that each table will always have 4 males and 4 females.

      As the current assignment is not valid for any of the courses (too many couples at every table), we ask everyone not on chair 0 or chair 1 politely to move a certain tables clock counter wise:

      chair 2: 2 tables

      chair 3: 3 tables

      chair 4: 8 tables

      chair 5: 10 tables

      chair 6: 18 tables

      chair 7: 21 tables

      This gives a valid assignment for the first course, which will be served by the couples sitting on chairs 0 and 1.

      After that course, everyone moves as many tables clockwise as the number of the chair they are sitting on. This gives a valid assignment that can be served by couples sitting on chairs 2 and 3.

      Again everyone moves as many tables clockwise as the number of the chair they are sitting on. This again gives a valid assignment that can be served by couples sitting on chairs 4 and 5.

      Now we are done with the dinner.

      The counter clockwise moves were chosen such that during each round, the couples that are supposed to serve are each sitting at the same table. To be more precise, initially everyone was asked to move (their chair number) * floor(their chair number/2) tables clock counter wise.

      All participants have at most 1 course with each other participant at the same table. If two people were to share a table twice, then let a be the difference in course number and b be the difference in chair number. Note that neither a nor b can be 0. the only possible values are a in (1,2) and b in (1,2,3,4,5,6,7). As they are sitting again at the same table the difference in number of tables they moved must be a multiple of 15, hence a*b mod 15 = 0. However, there are no possible a and b such that a*b mod 15 = 0.

      That the remainder of the constraints hold, should be easy to verify.