Can you elaborate on the five ways to leverage big data?
The first of those ways is transparency. Simply being able to access big data in an effective and efficient way can often drive a tremendous amount of value within many organizations for whom their use of data just has a lot of friction. Secondly, exposing variability and enabling experimentation. Simply being able to tell the difference in performance between different individuals, different organizations, different sites, can often drive a great deal of improvement in performance. Or perhaps more importantly, the ability to conduct experiments, to view your organization as a 24/7 laboratory, is a new way that leaders in using data are now starting to make management decisions in a very different way. So having a control group, having a treatment group, analyzing the statistics of the experiment afterwards is something that leaders in using data are really starting to do. Thirdly, segmenting populations to customize actions. This is the idea that it's not always most effective to treat everyone exactly the same way, so if you can better understand the characteristics of an individual, of a customer, of a supplier, you can often tailor programmes for those people or those organizations, which makes a win-win situation for both you as well as the partner that you're working with. The fourth one is either supporting or replacing human decision making with automated algorithms. This is this idea that if we use programmers, and it's not necessarily that you're always going to replace humans, sometimes you're just going to be able to provide them with better examples, better suggestions. So for instance, we've seen healthcare examples where you don't replace the doctor's diagnosis, but given the set of symptoms that are included in that electronic health record, you can give the doctor a set of potential diagnoses which they often find to be quite helpful And similarly we've also seen automated algorithms trying to identify when there's fraud in the system, etcetera. And maybe it just means that what you need to do is do additional auditing, but those types of automated systems are quite effective. And then finally, fifthly, this idea of creating new business models through the use of data. And we talked a bit about exhaust data. Well, when you have exhaust data, so for instance, a financial system will have a lot of transactional data that it will generate, a logistics company will generate a lot of data about what products are moving from where to where, a search engine company will have a lot of data about what people are searching for. Oftentimes if you look at the exhaust data that comes out of those systems, you'll find that you'll be able to create value in different ways. So it might be selling consumer insights, it might be providing better advertising, it might be being able to forecast better economic conditions based upon what products are moving from one country to another. All of those are examples of new business models that come about as a result of using data.
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