Positive disruption: getting to the bottom of big data

What is Boobook?

Nicola Huyghe:With the customer analytics side of the business, our clients ask us to analyse data provided by their customers to make an informed decision. We analyse the data and translate it into strategic insights. The second part is personalisation and that has different components. When we do the analysis it gives us lots of interesting numbers and we have to make sure we translate the analysis into a story. We produce very powerful visuals – charts, PowerPoint presentations, and dashboards so that clients can look at the data from different perspectives.

What type of challenges do you solve for businesses?

Most challenges are related to what we call customer segmentation. We ask the question: “How do we approach different types of customers in the best way?” We then identify the needs and target people so that they’re more susceptible to our messages. We also work on product development. This involves supporting companies by advising them on what their new or optimised product or service should look like. We look at the kind of features that benefit consumers and trigger their interest.

When a client approaches you, have they already identified their business needs?

Some know what they’re looking for, but that’s the minority. Then we have businesses who have a specific need that hasn’t been fully translated. For example, clients would come to us and say, “we need to do some pricing analysis because our price is probably too high”. Then once we start talking with the client, we realise it’s not a pricing issue. It could be that they need to approach the customers in a different way or position a product differently. Pinpointing exactly what the issue is or how we approach it is something we discuss with the client. We also have clients who, with the rise of big data, ask us to create insights from data they’ve collected. It’s very rare that we go to a client and they know exactly what they need.

You recently said you don’t like the term big data. Why is it that?

It’s a bit of a container word, plus it scares off companies. It makes them think they don’t have sufficient data to engage in big data analytics. Also, you can have a lot of data but if it’s not of good quality or it’s not related to the business question you’re looking at then you’re not going to really do much with it. It’s extremely relative and what’s big today is not big tomorrow anymore.

What does good data look like?

I think good data can help you to solve a specific problem. For example, if you want to look at the impact of changing your pricing strategy but you have data that isn’t related to pricing, you won’t be able to do much with it. You need reliable data. It doesn’t have to be 100% reliable but you need to have at least some level of trust in the data. Good data is also scalable over time, especially when you start thinking about continuously looking at your customers or predicting what they want to do. When you look at data, you never just look at what we have today, but what we have tomorrow.

BLH: What does a successful data driven company look like?

In the broadest sense, they use information they collect, or collected in the past, to base decisions on. It doesn’t mean that every decision they make has to be based on data. I think decisions should be based on a combination of facts and also the expertise gained over the years. Sometimes I conduct an exercise where I ask people what they think is going to happen, and a lot of people are wrong because their gut feeling is wrong. But you can have the same problem with data as well. If you only base decisions on data, you might become too theoretical. I think decisions should always be checked with what you’ve seen in the market.

What are the main challenges stopping companies from using data?

There are two sides of an organisation, the bottom side and top side. The top side is senior management who haven’t been making decisions based on data. Sometimes I say we are a generation too early as the people at the top are not always ready for data-led decisions. The other side of the organisation is the IT layer. Data tends to sit in the IT department purely because they own the data but IT people are not “insights people”.

The other challenge is the lack of sufficient data. Some companies think you need lots of data to do something with it and I always say start with what you have, and gradually you can add to it to improve your customer knowledge. Don’t wait until you have all the data because by that time your competitors will have run away with your customers.

What are your tips for understanding larger data sets?

People sometimes make the mistake of starting with the data. You have to ask, “What question do I want answered? What are the three things I want to convey?” Of course, you have to analyse your data, but you have to analyse it from the perspective of, “I need to find the answer to those three questions”. Think about what you want to tell your audience. What are the three conclusions? What numbers or what visuals do you need to back up that conclusion?

Why is storytelling important?

I love numbers, but the majority of people I talk to (business intelligence managers, CEOs, marketing), they don’t know much about data and to be honest they don’t really care. What we do with the data and what we’re going to do with it goes beyond numbers – It’s a story. It tells you what you need to do with your company to improve. Numbers on their own say very little. If I tell you that your Net Promoter Score is plus 50, would you know if that is good or bad? A number on its own doesn’t tell a story.

How can insights lead to innovation?

The majority of analytics is carried out as a result of a business question. If a client wants to change their strategy or wants to move into a new market, you conduct the analysis to support that decision.

The Fitbit for example, tracks everything and the healthcare industry uses the data to see how healthy or not healthy a person is. Also, it’s not very common, but you can now have chips inserted underneath your skin to measure all kinds of health statistics. I would call that predictive healthcare as it will raise an alarm if your blood pressure goes too low, for instance.

Is there a specific skill set for a data analytics expert?

I don’t think you can survive with only an analytical expert. You need different skillsets and different people. One person can have different skillsets but not all the skills you require when you want to become data-driven. The three most important skills to me are having business insight, knowing how tell a story, and being a statistician. But it’s very difficult to find that all in one person. Within Boobook we have analysts, we have insight research people and we have a visual designer. There are overlaps – an analyst will have business insight but it’s not their core strength.

What does the future hold for data and analytics?

In the near future I think it’s going to become a core expertise within every organisation. Before, only a few people used data or outsourced it to companies. There’s always going to be outsourcing but I compare it to a little bit like human resources. I might be wrong but years ago I think human resources was not a core part of an organisation. You know you had someone who took care of new employees but now it’s an important strategic element of an organisation. I think analytics is going to be the same.

At Blue Latitude Health, our business is based on developing rich insights to solve complex healthcare challenges. Get in touch with hello@bluelatitude.comto find out how we can help you achieve your goals.