6 ting du ikke vidste om optimering

Lightbulbs in motionOptimering spiller en afgørende og konstant stigende rolle for offentlig transport. Derfor er det overraskende at bemærke, hvor ofte konceptet bliver misforstået.

Optimeringseksperten Ali Khatam har en M.Sc. i Mathematics-Economics, Operations Research og er medstifer af QAMPO (Query, Analyse, Model, Predict, Optimise) – en førende leverandør indenfor optimerings teknologi. Vi snakkede med ham, for at finde ud af mere om dette fascinerende emne, og hvad det betyder for lederne indenfor offentlig transport.

1.      Optimisation is not Automation

What do the terms “automation” and “optimisation” mean to you? Though often used interchangeably, there are fundamental differences between the two, as Ali Khatam explains: “Automation is about using a computer to do work that would have previously been done manually by humans, whereas optimisation is about analysing different possible solutions to select the one that is best compared to the criteria you would like to fulfil." In other words, automation can be considered as a basic level that help you to increase efficiency, while optimisation provides the real power to reach your goals, work smarter and change the whole picture of public transport in a positive direction.

2.      Optimisation makes big data manageable

Ali uses a hospital example to illustrate the amount of data involved: “We worked with a hospital to create a three-week plan for staff, patients and treatment services. They had four patients a week, each with seven treatments. Our task was to make 84 (3x4x7) services fit into the 2,500 available half-hour time units. Total possible combinations? 10^283!”

Automation can certainly manage big figures, but what if you want to go further? The hospital in question wanted to comply with legal requirements for how quickly patients should be treated while utilising the skills of the department's scarce resources in the best possible way and with the fewest working hours. You need optimisation for that.

Big Data image3.      Optimisation can do so much more

Organisations searching for automation or optimisation solutions are usually looking to increase productivity and/or reduce cost. However, optimisation can do so much more. Ali explains that optimisation can even be used to create greater job satisfaction by ensuring that employees focus on tasks they do best. “If one person has skills that another does not, optimisation can ensure they each spend their time on the work they do better." What does this mean for public transport? Seen from a passenger’s point of view, getting in contact with a content and competent consultant in the call centre or taking a ride with a happy and service minded bus driver or train personnel can change the perception of public transport and thereby contribute to increasing ridership.

4.      Optimisation: Ancient mathematics that now becomes powerful

From a certain perspective, optimisation is actually nothing new: “It’s just ancient mathematics,” says Ali. “The algorithms were invented decades ago but we are starting to profit from them now because technology and computing power are so much stronger. Many industries – especially the transport industry – have worked with optimisation for many years, but thanks to technological development they can profit more than they could before."

5.      Next stop for Optimisation? Predictions

Predictions, Ali explains, is the future of optimisation. “Simulating the future is one of the most interesting aspects of optimisation. For example: What can I do if I want to save 10% of my total expenses, or if I would like to get happier employees, offering a better service? What parameters can I adjust and what are the consequences on everything else in my planning? Optimisation can inform such decisions – it’s a crystal ball for experimenting with different scenarios to solve various problems based on your wishes about what should happen in the future.”

6.      Optimisation in Public Transport: We’ve been doing it wrong!

Ali predicts that optimisation will change the way we think. "Today, when doing the planning in a hospital, you start by looking at the roster, which is fixed in advance: Who is at work, and when is it possible to treat the patient? The way we plan today is backwards; what we ought to do is start by looking at demand: What does a certain patient need and who should go to work to solve this particular problem?”

“It’s the same in transport: Routes are established by the authorities, and then the transport providers create shift scheduling and block plans accordingly. But the fewer restrictions you have, the better a plan you can create using optimisation. If transport providers were empowered to determine the routes by themselves, they could achieve a better plan in terms of finance, employees, service levels, or whatever you want to optimise.”