It’s all well and good for me and load of other companies who work in data to sit here and tell you that you need to be using data in your organization. Big Data is the latest business buzzword, and while the benefits of it can be immense, convincing yourself or your boss to start implementing it into your bottom line can sometimes be a bit of an uphill battle. But, data is important. In fact it’s critical for your business. And it’s you attitude to data, more than any other indicator (like size of Hadoop cluster or number of data scientists employed) that will determine your successful use of it.
So what do I mean by attitude to data? I think the best way to illustrate this is by looking at this case study…
Case Study: Tesco vs. Safeway
In 1993 Tesco and Safeway were two of three major players in the UK supermarket arena. And on the surface they should be the same: they both sell food at relatively similar prices and they owned pretty much the the same amount of the market. But today, you won’t find a single Safeway in the UK (they sold off the last of their stores to Morrison’s in 2003) and Tesco is the world’s 3rd largest retailer (behind only Walmart and Carrefour) with $96.8 billion in revenue.
So what happened? How did Tesco succeed where Safeway failed? The answer – as you’re about to find out – is data.
A little industry background
To find out what went so wrong for Safeway and so right for Tesco, we need to take a little journey back to 1993. Now I know that was a long time ago, so here are a few images to jog your memory about what the world in 1993 was like…
This is the Mac you were using… 
….we still trusted this guy…. 
…and this guy was Top of the Charts
1993 also happened to be a big year for super markets. It was the year when the price war between the current players really hit it’s peak and the margins on food prices came crashing down. It was how retailers chose to deal with this new era separated those who would survive from those who wouldn’t.
Let’s return to our case study.
Safeway
When Safeway began to feel the sting of slipping margins, they called in McKinsey Consulting. The consultants promptly put their heads down, and revamped Safeway’s marketing strategy and store layout to the tune of £15m. One of which was this, frankly ingenious marketing campaign – spin the plate.
To combat slipping margins, Safeway chose to focus on price discounting and new in-store technology – bouncing from one failed strategy to another. During the course of their 17 troubled years in the UK, Safeway had four failed takeover talks with Asda and merger discussions with nearly every other leading supermarket chain. In 2003 it was finally bought by Morrisons and by 2005 the name Safeway had disappeared from the UK entirely.
Tesco
On the other hand Tesco chose to handle the decreased price margins in a wholly different, and at the time radical, way. In 1993 Tesco decided they needed to understand their customer better. They began committing heavily to data. They partnered with Dunnhumby – a company which they later bought – and as a result, launched the now ubiquitous Tesco Clubcard system.
Their Clubcard program allowed them to collect a massive amount of data on the buying habits of their customers. This massive amount of data and combined with a powerful analytics system allowed Tesco to store and more importantly use the information they collected on their members.
Armed with this information, they began a system of data-driven retail which they implemented into every aspect of their value chain, from supply to sales and service.
And it worked.
Tesco’s market value skyrocketed from £4.7 billion in 1992 to £29.9 billion in 2011. And indeed, in the age of Big Data they are still leading the industry. They currently collect data from 16 million Club Card Members through a program which relies on a 100 terabyte data warehouse and a suite of sophisticated analytics and data modelling software.
What is all this data for?
Tesco use the data collected on customer buying habits to send them personalized discounts for items they might like and ones they currently buy. For example, If you currently buy Tesco brand milk, they may send you a coupon for a more upmarket brand of milk – if they can get you hooked on that brand, you’ll probably buy it regardless of whether or not it’s on offer – thus up-selling you on their products.
They can also use buying habits to predict when they need to restock items, a program which in the last 5 years has allowed them to save an average of £100m a year through a reduction in wasted stock and ensure 30% fewer gaps on shelves during promotions.
Tesco’s virtual store in Korea
It’s not all about internal data either, Tesco have pioneered the use weather data save £6M in wasted stock in the summer alone. Their most recent program allows them to highlight promotions to individuals on their website by correlating Clubcard data with other data including payment methods and social networking information; letting them offer cheaper products to price-sensitive customers and luxury products to wealthier customers.
They’re even trialing a virtual store in Korea, where customers can buy goods off an electronic board with offers on it using their mobile phone – shopping is then delivered to the home or office.
In a market where winning customer loyalty is increasingly more difficult, Big Data has enabled Tesco to usher in an era of mass personalisation.
That’s all great for Tesco, but what does this mean for you?
Practical uses of data
From an industry point of view it doesn’t matter what you do, in the next 5 years you will have to compete on data. And as you can probably see from the Tesco example, quite a few people already are.
But, how do you make it work for you?
The first thing you need to do is launch a club card right? NO!
If we go back briefly to our case study, Safeway actually launched their ABC card at around the same time as Tesco launched the Clubcard. They were able to collect data on their customers, they just weren’t listening to it or using it effectively.
Now, obviously a club card isn’t right for everyone – it’s about what the club card represents. You need to think about what, for you, will help you understand your customers, your market, and the factors that affect that.
All businesses have touch-points with their customers, their competitors and their market. The thing you need to ask yourself is: How can I collect this data and analyse it to help my business?
You might think you’re already doing this because you have BI department. But if all your doing is using existing resources to collect and analyze data, it isn’t enough – you need to be thinking about data in a fundamentally different way.
The real reason Tesco has succeeded where Safeway failed is not simply their use of data, but their attitude towards it. Everyone at Tesco understands this data analysis is the key to its success, and that these processes have to be created, innovated, and tried out. They evolve and morph constantly, with more pieces adding to the data collection and customer relationship channels as necessary.
Get yourself a CDO
One of the best indicators of a businesses attitude towards data is the organisational structure. Where does the person who is responsible for data sit? Data is a fundamentally important asset which should sit alongside your IP, your people and your capital. So, if you’re still leaving data to your IT department – you’re doing it wrong.
To use data effectively may require a structural change in your organization. The first thing you need is a Chief Data Officer. A good CDO is a key asset and should be a C level job. They can help you make sure you have a competitive edge with data. Tesco has a whole subsidiary, Dunnhumby which collects and analyzes their data run by Chief Executive Simon Hay.
For most businesses though you just need someone who can blend an in-depth knowledge of the business as a whole with data science, insight, marketing and strategy. Most importantly they need to have credibility across the organization – it is vital that the whole leadership team sets up this role to succeed.
At a high level a chief data officer is responsible for 3 things:
- Insight – the end point is that aha moment, the insight from the data that gives you a competitive edge. This is what you are aiming for.
- Analysis – to get there you need good analysis, this is the process of breaking the data down, sifting it, grouping it, cutting and slicing it to understand it better and begin to identify trends.
- Collection – and all of this relies on collection. If you get this phase wrong then no amount of $ spent in analysis will help you to gain insight.
Where is all this data coming from?
If your CDO is thinking ONLY about sweating out the data w/in your organization you should probably fire him. Data needs to come from everywhere. Don’t limit yourself to data that is inside your organization or that you are familiar with.
Collect data that scares you. Maybe it’s useful maybe it isn’t – but you’ll never know unless you collect and analyse it. Don’t be afraid to experiment with different data collection methods and analysis. Try new things, collect and analyse the data and then try something else.
The most important thing isn’t that you get the data collection perfect, it’s that you start now.
The trend of using data is well and truly in play. A data strategy takes time and commitment. If you react late in the marketplace, you’ll be behind your competitors just as Safeway was in ‘95. The real benefit of data is that the more you gather the more you can react and the more benefit you get overtime.
They key is to act now, because you may never recover from the data deficit.
This post is based on an online webinar I did for BrightTalk.