Data is the new oil (Part 2) - Make sure you're drilling for oil and not gas!
In the first of this series of blogs on data – “Data is the new oil” – we looked at how every business needs data and how by thinking about it from Day 1 you can reap the rewards further down the line.
So now you’ve got started collecting data I want to take things a bit further to show you what good data collection can add to your business. To do that this blog will use live examples from a coffee shop that I analysed recently. I’ve always found that talking about the theory doesn’t really help and therefore want to give you some real life examples which you can practically compare to your own business situation.
Are you drilling for oil in a gas field?
Oil companies think they know where’s some oil. They stick an oil rig on top of it and bring it out of the ground – that simple right? Well not quite and the same is true with data. The oil companies need to make sure they’re drilling in an oil field to collect oil and not in a gas field.
Sounds crazily obvious I know but just in the same way oil companies need to spend time ensuring they’re drilling in the right place you too need to spend some time making sure you’re collecting the right data.
If you’re using data to analyse sales for example, then at the bare minimum you need to collect what you are selling and how much it is sold for. Simple right? Again it’s not always as easy as it sounds. The coffee shop that I was working with for example was collecting that sales data but didn’t quite get it right.
They initially collected the total sale value and the time/date of that transaction. That’s ok if a customer only buys one item in a transaction, like a coffee (because you know that they have only bought one coffee). But what if they buy two or more coffees? By just collecting the ‘total value’ of the transaction you can’t see exactly what they’ve bought.
A transaction value of £10 might been 4 flat whites at £2.50 each. Or 2 cappuccinos and 2 flat whites. Or 2 coffees, a tea and piece of cake or….. you get the point.
Collect the right data from the outset
So what data should the coffee shop be collecting. Say by comparison for example they collected the data in the table below instead:
Date |
Time |
Item |
Quantity |
Price |
Sales No. |
01/11/2016 |
8:52 |
Flat White |
1 |
2.60 |
00001 |
01/11/2016 |
8:52 |
Latte |
1 |
2.10 |
00001 |
01/11/2016 |
8:52 |
Toast |
1 |
0.30 |
00001 |
01/11/2016 |
9:03 |
Flat White |
1 |
2.60 |
00002 |
With this data structure you can see they could now do the simplest analysis:
- They could see how many flat whites they have sold and when they sold them.
- They could see whether people bought just a flat white or a combination of drinks and food.
- They could calculate the average transaction value and the average value of each product within an individual transaction.
There’s another good feature of the table above too. The date and time are in two separate columns. Quite often they are one column and, when they are, a lot of time and effort is spent separating them back out into two columns to carry out the required analysis. By doing it right up front, you save time later on.
If you have data structured like this and have enough data to analyse (probably one month’s worth) then you can do some analysis that helps you make better business decisions.
Collect better data = make better business decisions
For example, you’ll be able to see what days you sell more things on and that will help you work out your staffing levels.
But you can also try things to drive sales on the other days – marketing tactics, discounts etc. The coffee shop that I worked with found that they sold a lot when a football match was being played. But those people didn’t buy as much when they did buy something . So the team then made food/coffee combinations to drive the average sale value back up, all combined with some marketing for those days.
Final tip
It’s worth saying that good till / Electronic Point Of Sale (EPOS) software will do most of the above for you if you have a shop. Just by logging on to the EPOS software in the Cloud, you can download all the data into an excel spreadsheet and then off you go. The software itself though will also give you the summary statistics like turnover, average sale value for time and day without even touching Excel!
But many small businesses won’t have software or tills like this and a simple, well set up Excel spreadsheet will do the trick. To analyse it detail, pivot tables can be very powerful. And before you know it you’ll be making better decisions and hopefully both saving money and increasing sales!
Stu Bennett is a data expert working at the Department of Work and Pensions.
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