Stonegate Pub Company is the largest privately-held managed pub operator in the UK with revenues in excess of £500 million. Employing over 12,000 people, the company’s portfolio encompasses over 600 classic, local and traditional pubs, bars and venues. Stonegate’s Chief Finance Officer is Dave Ross, who shares his thoughts here around data-driven decision making within the organisation.

In 2017 data is becoming even more important. In a retail business, data is everything. Retail is detail, so the more data that we have to understand our customer then that’s how we grow.  The trends that are most important are those that are around the customer and their behaviour. If we can understand the customer behaviour, we can tailor our offers and our prices to meet that demand.

Right now the market is very volatile. The consumer trends are forever changing and you’ve got to not only keep up, but hopefully be one step ahead – and that is very challenging right now. In the drinks-led business there’s a strong trend around key events. So the customer will come out for a key event such as Christmas or Halloween. But this week, for example, with no sport and the weather not great, the customer is decamping and staying at home. We’ll predict where this quiet period will be, which is very important from a profit perspective, because then we can match our costs and our labour accordingly to reduce that risk when customers aren’t coming out.

We listen to the people who are using the data.

Dave Ross

In integrating data as part of day-to-day operations, the barrier is knowing what data you want. Because you can get everything; I can tell you how many cheeseburgers are ordered on a Tuesday afternoon versus a Thursday morning. But is that going to change any decision? It’s about getting the data that is going to facilitate a decision that is ultimately going to make you more money.  

An example of how we’ve turned data into actionable knowledge is our drinks range and the consumer trend of premiumisation – so people choosing to buy Peroni instead of a Carlsberg and that price differential. We were noticing that the pricing sensitivity was so much less in those premium products and we’ve been able to stretch the pricing, thereby gaining more margin.  

We listen to the people who are using the data. We won’t do things just for fun because we enjoy data, because we’re accountants and numbers people. We will talk to the people who use the data: What do they like? What are they interested in? We try and understand the need from our “customers” in finance and then deliver what they need.  

There are always people who will say that their intuition will beat any data-driven decision. And it’s just about learning with those people and saying, “Where is that intuition coming from?” When you delve further, it’s coming from data. It’s things that they’ve seen before. If you can show them it’s data that’s backing up their decision – rather than they’re just making a decision without the data – that helps as well.

There are challenges in with mixing data and people. For example, we used to use a labour productivity tool, which basically showed when a manager put a rota on. It used data to say when drink and food were sold and then it looked at the rota and said where you were under- or overstaffed. To a data scientist, it’s great – just take people off there and put them on then. The data was really easy in telling us what to do, but the people were really reluctant to do it because they didn’t understand it. So without that link between data and engagement with the people, you don’t get a result.  

My advice to CFOs is to talk to your people. It doesn’t take long and you’d be amazed at how quickly they get engaged when you’re saying, “The data is telling us this, and this is why we want to do it”. People want to know why they’re being asked to do something.  

You can have all of the data in the world, but business does come down to people. One of our managing directors describes it as “lots of meteors coming down and knowing which ones to capture”. We have a lot of data, but in the end you’ve got to make a decision. So the question is how do you make the decision and then how do you implement that decision as well.