In the Flow with Keith Carter

In this month’s “In the Flow” interview, we sit down with Keith Carter – a Senior Visiting Fellow at the National University of Singapore – to take a closer
look at how companies can harness the power of big data and modern business intelligence strategies. Keith is author of the book Actionable Intelligence: A Guide To Delivering Business Results with Big Data Fast! and has more than 20 years of professional experience in consulting and supply chain management.

Let’s start by talking a little bit about big data. Everyone’s talking about it – governments, newspapers, companies. What does it mean?

Big data means nothing. Many people take a different view on this. They say, “What do you mean ‘big data means nothing’? You have to have the data.” No. It’s not its bigness that’s important. You have to have a question. And after you get some data to answer that question, you get an even better question. So what big data is about is that we can ask really good, interesting questions and get facts about the answer in ways that we’ve never been able to in recorded history.

There are two aspects to this. One is that it has been a long time since people have all pretty much spoken the same language. A hundred years ago, most of the world was speaking their own tribal languages around the world. That was a barrier in a sense. Now we have these devices that let us share. The other aspect is that from a data capture perspective, there’s so much data that we previously weren’t capturing about the world around us in a way that we could process it, store it, reprocess it and so on.

What I mean by that is that we don’t appreciate how much data we process as humans. This is the exciting prospect of big data. In elementary school we learned about probability. If I take a coin and flip it a thousand times, a million times, equally weighted, heads and tails, what’s the probability that it will be heads or tails? 50 percent, right? If I flip it a billion times, has the probability changed? No. In fact, it’s even closer to 50 percent.

Big data is about this: we now have the systems and technology so that when we flip the coin, measure the impulse, measure the amount of flips just as it gets to the apex, know whether it is heads or tails, and as it begins to come down, measure the flipping and just before it actually reaches, we can tell: heads. That’s big data. We had to capture much more data, but instead of the probability, now we can predict. We had to have much more data to do that.

How can businesses harness this?

Big data can help us answer questions like who is my next best customer, what will they buy, where will they buy it from? All of those things before were based on soft anecdotal evidence, maybe log files written down and discussions. “Oh, the last customer I saw today was from that part of town and they did a savings transaction.” And of course, there wasn’t enough computing power or processes in place to look at every single branch and ask all of the supervisors that same question. Some banks and some organisations were better than others. They would make sure at the end of the day that everyone would give a report. But it was still based on the best that the salesperson could provide.

Now, with a camera we can see how many people came in, what they went to look at, we can tell when they go to pay. We can connect data. We can know if they came back before. All these pieces of information, all these data that are now available on computers and people are trying to figure out what to do with it.

Never before in history as we know it have we had so much data, and as a result the potential to create so many interesting jobs. The challenge is that these are new jobs. These are for people who are very hungry. These are things not where you can have a very structured plan of this is what you’re going to do. No one knows what to do; they’re finding out what to do. The value hasn’t been unlocked yet, and that’s why it’s so valuable. So then you have to look back and say, “Have we instilled the right capabilities? Are we ready to handle: ‘Here’s the data, tell me what it says.’?” There’s no structure.

So big data is not about data. It’s about questions, and behind those questions there is curiosity. If you ask the right questions, the answers will show up.

I think I’ve crashed every database I’ve ever touched. I always query too much, I run something and then crash. But then: reset, wait a little and it’s back. When you start to ask the questions, you’re going to find that maybe you go to a place where you don’t have the data. Find out faster, if that’s the case. You find the gaps or you realise maybe that the way you capture the data is no good.

In the book I talk about SWAT: strategic business question, wrangle the data, analyse it and take action. For business, SWAT has to be fast. The customer comes in to look at your product. How do we shop today? We go into a store and look at a new product, and then the very next place we look is our own big data device – our phone. Why is this big data? Because I have the whole world here. I can’t read the instructions? I use Google Translate to see what it says. I take a picture and see what the other products are. I go to Amazon and see the pricing. Can I ship it plus everything at a discount? Can you imagine doing that 20 years ago? With smartphones, our options are endless. We as people, as consumers have already well adapted to using big data, but businesses and schools are far behind.

Maybe they are asking the wrong questions.

Right! They don’t ask questions. I see you every day, you keep coming, I keep selling, finished. It’s like the coffee shop that will never increase its prices even though Starbucks has gone to $7 for a cup of coffee. The same person is there at the coffee shop selling coffee for 50 cents, while over at Starbucks it’s $7. You can argue, well, Starbucks has air-conditioning and maybe the seats are nicer, but $7?

So then the question becomes: when do we begin to ask the right question? Of the customers who come to my kopitiam, which one is price insensitive, so that I can raise my price to $2? Which one drove in with a Mercedes to Tiong Bahru Market and would nonetheless choose to go someplace else if I raised my price to 60 cents? How can that be? Which one is the Japanese customer who is just so interested in trying out Tiong Bahru Market and is willing to pay? There are differences.

Some people will say that’s unfair. Well, airlines do dynamic pricing all the time. Amazon, Alibaba – they all do dynamic pricing. Who’s out there in the street protesting? No one. So now I have a taxi uncle who comes in versus a Japanese tourist. Should I do dynamic pricing? Why not. Why do I have to display my price on the board? Why not just as you swipe your card, then I charge. The bus charges me like that. I have no idea whether I’m going to 70 cents, $1.25. When do you know how much you’re going to pay?

That’s challenging the paradigm of old business models.

Absolutely, of old business models. But I have to tell you: would I pay $3 to the lady at Tiong Bahru Market who’s there with her husband at 5:30am cranking out really the best yinyang that I’ve ever had in Singapore? Yes I would. But I’ve tried to pay them that much and they wouldn’t take it. The model is so different. Even at Starbucks they’ll take a tip after you’ve paid $7 for your coffee!

Starbucks is all about data. They know their customers, they know how much they’ll spend, they track when you use the wifi, they track what you buy. They have the app that you can order on and they’re tracking what you order. And on and on. They’re using so much data. And did they lose money? Did they go out of business? No. They are publicly listed and doing very well.

The coffee uncle – he’s 50, 60 years old – whose son is there, no help. He could do the data. Listen, let’s make sure you don’t have too much coffee at the end, let’s measure how many cups you actually use, let’s analyse. There’s a good amount of data that the coffee uncle also has. Do they capture it? Do they have a question? No. The reason that they don’t have any data in the first place is that they don’t have any questions about the data.

But you know what they know that’s really big data? When I walk in there, they do facial recognition on me and they know what I want. They also do behavioural recognition on me and they know that I’ll pay. There’s a lot of data that they are processing. And they don’t just know me. They know this one and that one. They really do manage the data, and the question they ask themselves all the time is who is this customer, how can I serve them, how can I keep them happy. Those are really good questions, but they’re not taking it further to really understand it even more.

Right now the conversation in Singapore is all about supporting SMEs. Where can they start, whether that’s collecting data, asking questions, etc.? What is your advice to all those struggling business owners out there?

Someone said something very good to me. He said that business owners sometimes forget why they opened the business. At first, they open the business because the customers had a need. And the customers loved them not because of who they were, but because they satisfied that need. After a long time, the business owner got confused and began to think it was their brand, it was their relationship, it was their business that the customer liked. No, it was always and only what they had and how they sold it.

So SMEs need to think back to their entrepreneurial roots and say, “Oh yeah, I need to sell something that people want and have it there not when I’m open, but when they want it.” I had a client once who said to me, “Keith, I need a consultant who is there at my time of need.” That implies that the consultant has what she wants and is also there at the right place and at the right time. Those three things.

So if on Facebook a customer says that they just ran out of tissues or that they are so hungry, here comes Deliveroo, replacing the market. Or if everyone keeps complaining that at 5pm they can’t get a taxi, here comes Uber or Grab with private cars because the structure, the relationship between the driver and people who were there was forgotten. Lee Kuan Yew set up the taxi here in Singapore in a very special way. He said, “I want it to be the first great impression of visitors to Singapore.” That implies that it’s available with a smile. That’s been lost. At 5pm, 6pm, that’s lost.

So people don’t even look at the data. The data is right there – you don’t need to have big data for this. You can have it just to prove a point and show how many people are standing here or there and no one is moving. Yes, those are good facts. It’s the second level. If I were to solve the first issue, the capacity issue, then it would answer the second issue of where does the capacity need to go. Fine, that’s where you use big data.

But I challenge that SMEs and others – all of us – need to ask ourselves: are we using the data that’s right in front of our face? I don’t need big data to know that I charge 50 cents and Starbucks charges $7 and there’s somewhere in between there that I should increase my price to because my coffee went up, my rent went up, my driver went up, my car went up. That’s not big data, that’s just not being afraid.

Thank you for your insights, Keith!

While there has been plenty of hype about big data in recent years, Keith highlights that the key lies in asking the right questions.

Modern technology allows us to collect huge amounts of data more quickly than ever before. However, if we do not think critically and ask strategic questions
that address the heart of our business problems, all the data in the world won’t be enough to help us thrive. And the first step to asking the right
questions is not being afraid of the change that these questions might bring about.

For even more insights from Keith Carter, check out the full interview transcript at: In the Flow with Keith Carter_full transcript.pdf

Check out also his website at


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