Solving complex (social) issues using algorithms and AI: looking at the world around us, we seldom succeed in grasping these opportunities. This is partly because these opportunities have often not even been identified yet, but a lack of understanding about AI also contributes to this.

“To identify opportunities, you need an understanding of what’s theoretically possible,” says Gerrit Timmer, Co-founder and Chief Science Officer (CSO) at ORTEC. “You need to have a clear picture in your mind, otherwise you won’t succeed. Or as Johan Cruijff, former Dutch footballer, put it: you don’t see it until you’ve figured it out. In particular, top management is lagging far behind in this respect.” The corporate world contains far too few people with a sufficient understanding of AI. The bottleneck lies in the fact that existing methods and techniques need to find their way to the market more easily. For that to happen, enough people should have some understanding about those methods.

“A real pity,” Timmer concludes, “because there are opportunities all around us.” Let’s take a look at the opportunities in healthcare and business, described below.

In hospitals

• Optimum capacity
  In hospitals, the various components, such as nursing wards, outpatient clinics, and operating rooms, operate far apart from each other. That means staff are constantly either working flat out or stalled. Imagine a situation in which a surgeon performs multiple operations, after which a patient needs to stay in the hospital for a prolonged period: will there be a bed available in that ward? At the same time, in the case of multiple operations and few consultations with new patients, doctors might end up with too little work because the flow of patients is drying up. Much more is possible if this is better coordinated and capacity is used to the fullest. This is also known as integral capacity management.
  
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  Example: more operations during COVID-19 pandemic thanks to smart forecasting
  The high number of COVID-19 patients in ICUs means that less ‘regular’ care has been provided over the past few months because of the risk of there being no ICU bed available if one is required after surgery. A closer examination shows that more operations are possible than are currently being performed in hospitals (source: STAtOR, 2021). With the support of ORTEC and Rhythm, for instance, it turns out that many more operations could be carried out at OLVG, a hospital in Amsterdam. At Rijnstate, a hospital in another Dutch region, hospital beds were causing the bottleneck. Whereas the wards always used to be full to overflowing on some weekdays, they were fairly empty on others. By performing the right types of operations on the right days, the ward capacity is now being used more efficiently and more operations are taking place.
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• AI leading and supporting doctors
  AI will play a much bigger role in our healthcare in the near future, including in hospitals. AI currently plays a supporting role in healthcare, but in ten years’ time we expect AI to be leading and doctors supporting.
• Patient empowerment
  According to Prof. Folkert Asselbergs, cardiologist at UMC Utrecht Hospital, the most important thing AI will bring to healthcare is patient empowerment. “The experience and knowledge gap between patients and doctors is enormous, including data knowledge. We speak our own language and wear a white coat, all of which creates distance.” That distance will soon be eliminated because patients will know exactly what the doctor knows.

In medical science

There’s a huge amount of data available in medical science. From illnesses patients have had and medication they’re taking to MRI scans. AI enables us to get much more out of this data, such as improved diagnosis and treatment, including prevention. For example, adjustments to lifestyle or treatments can yield health benefits. This includes things like quitting smoking, getting more exercise, cutting down on salt and/or fat etc. Data can also tell us the health benefits we can derive from starting a particular treatment via what’s known as a lifetime prediction. (Dutch link)

Opportunities in business

Companies are often divided into smaller departments and each of these departments work primarily from the perspective of that individual department. This has historical roots: to function well, humans perform better if they work within the limited scope of one department. Otherwise each employee will get lost in the complexity of the total scope. However, thanks to the processing power of computers and the increasing ingenuity of algorithms, it’s now possible to think and optimize processes across departments, enabling you to achieve better, more efficient, and more profitable solutions.

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An example: the limits of thinking within departments
Company X has a production department and a sales department. The sales department sells the products at a deadline that the production department is unable to meet. The opposite may also occur: production is not coordinated with demand, leading to large quantities being produced that the sales department is then unable to sell.
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AI enables large retailers to coordinate the individual departments with each other. For instance, they link pricing and delivery times: you pay a higher or lower price, depending on when you want to receive your order. Your preferred time influences the logistic costs for the retailer, for example: does it fit within their existing route? Beforehand, it’s calculated much extra it will cost to deliver your order at your preferred time.

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An example: aligning the sales and logistics departments
A large multinational in the United States uses ORTEC’s load designer in a creative manner to align the sales and logistics departments with each other. While Loaddesigner was originally created to provide insight into how to load goods into a truck so you get as much in as possible, this company uses the tool in its sales department. If a customer phones through an order, the salesperson can see in real time whether it will fit in the truck. If it just does not fit, then the salesperson will say that one of the products in the order will be on sale the next week. The customer may then skip the product for now and what remains is a load that fits perfectly into one single truck. Vice versa: if there’s room left in the truck, the salesperson could try to persuade the customer to order a bit now more by offering some discount.

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Gerrit's future prediction

"All in all, our current knowledge of AI and data science in business is far too low. And this will continue for the foreseeable future,” Gerrit Timmer predicts. Trends are evolving so rapidly that it’s easy to get left behind.