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What Value Can Businesses Get Out of Data They are Collecting?

Duncan MacRae


businesses data

Inez Hogarth, MD at Data Understood, uses three specific examples to illustrate what value organisations can extract from data they are already collecting – and how they can do it.

Data, particularly ‘big data’, can be confusing and overwhelming – so much so that it can be a thing to be feared. But it needn’t be, as Inez Hogarth, MD at Data Understood, explained at DIGIT’s fourth annual digital transformation conference.

vaccinationMerck is an incredible drugs company. They were the first company to produce a MMR vaccine and they’ve got a really good history of knowing exactly how to develop drugs and vaccines.

“But in 2012 they found out that their ability to create a vaccine was becoming more expensive and required more time. So they looked at the data they were collecting to see if there was a way they could improve their production rates and increase their efficiency. They were collecting a lot of data already and, with the advent of big data, they were able to analyse everything that was being collected, and they found out it was the fermentation process that was actually causing problems in their yield rate.

“For them, this was completely controllable, so they changed their fermentation process, adjusting the temperature and the result was that Merck, in 2014, had the highest number of drugs going to market out of all the pharmaceutical companies. Obviously, 2012 was quite some time ago so a lot of other drugs companies have caught up, but this reveals to me how data can have a massive impact on being able to improve your processes and improve your customer service. If a drug gets to market quicker then it’s ability to save lives is immediately improved.

McLaren F1“Another aspect is providing a method of being more competitive. McLaren is renowned for being competitive – that’s part of their job. They heard about data being useful so they thought ‘how can we use that to our advantage?’ And they did something very simple. They looked at their F1 team and how they could improve their pit stops. So they started photographing and monitoring every pit stop and compared how the right-hand side of the team compared to the left-hand side. They wanted to see if there were any changes their guys could make to improve the speed at which they carried out a pit stop. With the simple act of collecting new data and analysing it visually, they were able to reduce their pit stop time from 4 seconds to 2.3 seconds. That’s massive.

“But it doesn’t just have to be about using your own data or collecting data. You can use third-party sources.

map reading “Most mobile apps are essentially powered by data. They either generate their own or they build it from a third party data source. My favourite app is City Mapper, and it uses Open Data, which is free for anyone to use. All they did was collect information from Transport for London and other open data sources to help people like me, who are incredibly good at getting lost, get from point A to point B. This app makes my life so much easier and the incredible thing is that they didn’t need to build a database. The data was already out there.”

So, data improves efficiency, reduces costs, increases revenue, enables you to be more competitive and helps your customers have a much easier life. Everything is about making customers’ lives easier and reducing their suffering.

But how can you do this within your own organisation? People are quite fearful about how data is collected, and there are a lot of concerns about how data is used. It’s completely understandable, but there’s a process you can put in place to create a healthy data culture and it’s very simple.

Hogarth’s top tips

1. This first thing you have to focus on is getting engagement, and the best way to get engagement is to focus on your customer. Try to figure out an issue that’s bothering them or that could make their lives happier, and put all of your focus on helping them – and not on your own company. The other thing that I would heavily recommend is to build a culture that is curious and constantly experimenting. The biggest problem that I see with people rejecting data cultures is that they fear they will be told they are doing something wrong. That’s only a problem if you work in a culture that’s very much about blaming others, so you need to get rid of the whole idea of ‘blame’. Be more inclusive and show employees that there are more opportunities to grow.

2. The second aspect is making sure that you’ve got the right resources – the technical resources and the skills base. You need to have the proper infrastructure and computing in order to enable your organisation to get the most from its data. It needs to be secure and accessible, but you also need to make sure you’ve got the people in-house who can actually use the data.

3. Last, but definitely not least, you need to have good data. It needs to be relevant to what you’re trying to explore, it needs to be accurate and it needs to be timely. It’s all very well having data but if it’s not useful for measuring what you’re looking at then it’s not going to be of use to anyone.

Duncan MacRae


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