Steve Alker - CEO at iSimutron Ltd and Partner with SymVolli Limited
We work internationally, so here is a case from colleagues from afar with updates from 2013 to 2018 from iSimutron ltd.
This is as close as you can get to putting a rocket under the profits of a company. A jump in profits from £2.6Million to £13 Million in just over 24 months. Look at The Yellow Line.
In a simple operation, a near step change can happen.
A company in Ethiopia made only two products. When distilled down, that is what a lot of smaller UK companies do (Think about it.)
After 50 years of state control and being told what to make and when to make it and who to supply it to, they were set free. In market terms, that was 50 years of running at a loss. Then. 3 years of losses later, they had slowly moved into profit, but not much and it was fragile, flatlining at about £1.7 million and then slowly creeping up whilst sales and production grew steadily. At least they had cracked production problems and learned some sales techniques but no marketing or market knowledge. Nothing had been done to optimise sales, marketing or production. Maintenance was good.
So, Prof Maurya and his team went in to see if the plant and production could be optimised and if new marketing and sales efforts would propel the company forward. The results on the ground were startling.
The biggest hurdle to carrying out the work was a total disbelief by the local management that maths alone could improve their fortunes. They had never heard of Linear Programming or Operational Research and the Simplex Algorithm was Simply Black Magic in a Box and probably lies to boot. It took Prof. Maurya three months working with the team at the plant,
gathering data, collecting information in surveys and slowly winning their confidence, before they were ready to commit to the changes needed.
Head in the sand: This attitude is somewhat like the one we find in the boardrooms of the SME firms we target. Disbelief. Ignorable. Not Made Here. We Don't Believe in Linear Programming for Profit. You won’t find this attitude in the Boardrooms of the FTSE because they already use it, for profit, lots of profit, but the algorithms are their preserve and they do not leak out into the mid-market. We cannot afford to spend three months persuading people in the UK, which is a pity, because there are a lot of companies who will benefit from our work and yet treat what we do with deep suspicion. Just like the Ethiopian Management really.
We could do the work on a graph for optimisation, but instead used our simplex engine to experiment with a model we create, and a graph to explain things
By simply changing the quantities of the products they made and going out to their existing and lost customers profits went up from £2 Million to £13 Million. In steps, as shown in the graph above under the heading. Look at the yellow line.
They had to address raw material and supply and marketing problems, but with guaranteed products available to customers, sales soared. Through optimisation, profits rocketed. And the plant benefited from investment, whilst a steady rate of production improved quality. Start and stop in the past damaged both the plant and product quality. The market liked what it was now buying (quality and reliability of supply) and would pay a little more for it and buy more as well. More profits then!
Busses come in threes. So, do two product optimisations. When I and others teach optimisation we nearly always use two product examples for clarity and simplicity (We can use that graph of intersecting lines) and yet we warn that there are not very many two product companies out there. Then I publish three in a row!! Whilst it is a lot of fun to perform a 300-product optimisation, the level of detail revealed means that data mining is needed to interpret and act on the results. We do that, but we often simplify the price list from hundreds of items down to 10 or 20 or 30 with no loss of quality of information for optimisation, modelling, sales forecasting or quoting.
This was a rare example where change could be implemented very quickly, and the results manifested on the plant could be seen in days. And in their bank account in months.
Postscript: The management have announced that they are also going to produce Hydrogen Peroxide at the plant. So now they can't use a graph because they have three products. There is even talk of four products. So, they will have to use our Simplex Algorithm to optimise production.
A moral Dilemma: Do we approach them and risk another three months of wondering if the new magic will work for four products when they can't see the results on a four dimensional graph because you can't see anything in four dimensions.
They need the use of our Simplex Algorithm and our sales and marketing advice to go with it.
Or do we wait until they are in a mess again, and then go and rescue them, giving you a nice new story?
I will be guided by the fellow above, Bertrand Russell. We have a moral duty to go back as soon as possible and help them. Anyone fancy getting sunburned?
Credits to: With work from Prof. V. N. Maurya used for the study:
Vishwa Nath Maurya, Ram Bilas Misra, Peter K Anderson, Kamlesh Kumar Shukla. Profit Optimization Using Linear Programming Model: A Case Study of Ethiopian Chemical Company. American Journal of Biological and Environmental Statistics. Vol. 1, No. 2, 2015, pp. 51-57. doi: 10.11648/j.ajbes.20150102.12
