Standing out from your competitors is harder than ever, but analytics may be the way to steal in front

It may seem as dry as toast, but reams of data may hold the secret to a successful business. Take the case of British supermarket chain Tesco. Its loyalty card scheme, Clubcard, was set up in 1995 with the aim of getting to know what its customers wanted. Since the introduction of the card, Tesco has outperformed the UK supermarket sector every year and risen to the number one position in the market, according to Giles Pavey, head of retail analysis at Dunnhumby, Tesco's customer insight partner.

The Clubcard scheme is a powerful mechanism for collecting information on customers, rewarding customers for shopping at Tesco, and maximising return on marketing budgets.

Customers who shop at Tesco earn points at a rate of 1 per cent per euro, which are then returned to the customer in form of vouchers. Since its inception, about £2 billion (€2.86 billion) worth of points have been given back to customers.

The direct mail results of this scheme are impressive, with the coupon redemption rate ranging from 20 to 50 per cent, compared with the industry average of between 1 and 2 per cent.

Moreover, the increased amount of data now obtainable through the Clubcard scheme enables Tesco to send out nine million different combinations of specifically targeted coupons each quarter, choose the correct product ranges for different stores and target customers for bespoke marketing.

Through this personalisation, Tesco has built itself a unique selling point and differentiated itself from its competitors.

Tesco isn't the only company to use its data to enhance its business model. Hilton Hotels utilised its data to calculate that a 5 per cent increase in customer loyalty equals a 1.1 per cent increase in revenue the following year, and as a result made customer retention one of its key business priorities.

Put simply, mining information through analytics allows firms to differentiate themselves from rivals who sell similar products at similar prices. Companies that find a way of doing this stand a much greater chance of success, according to Thomas Davenport, professor of information technology and management at Babson College, Massachusetts.

What is less well known, but becoming increasingly obvious, however, is that analytics could, for now, be the answer.

"At a time when firms in many industries offer similar products and use comparable technologies, business processes are among the last remaining points of differentiation and analytics competitors wring every last drop of value from those processes," says Davenport.

Utilising analytics to advance your business doesn't mean hiring a bunch of geeky maths graduates and giving them a free reign over your database. Lots of companies have lots of data. The important thing, according to Davenport, is to ensure you have an end mission and know what you want to get out of your data analysis.

While many organisations are today embracing the idea of analytics, Davenport is quick to cite a handful of US companies that he believes are doing it well. One of those is financial group Capital One, which has exceeded 20 per cent earnings growth every year since it became a public company; another is Amazon, which now dominates the online retailing market and has generated a profit despite enormous investment in growth and infrastructure.

Another example is Marriot International. Over the past 20 years the company has honed its system for establishing the optimal price for guest rooms, so much so that it no longer needs human intervention to set prices.

However, this is a good time to point out that competing through analytics is not all about technology and data. "Not all decisions should be grounded in analytics," says Davenport, adding that some matters, such as personnel issues, are often better judged by human instinct and anecdote.

It is also important for human beings to be able to override data programmes where necessary.

In August 2005, Marriot's computers were showing an increase in demand for rooms in Houston and all analysis pointed to the opportunity for a price increase. It took human common sense to realise the increase in demand was a result of people being displaced after Hurricane Katrina and that it might not be best practice for Marriot to raise its tariffs for these people.

"For analytics-minded leaders, the challenge boils down to knowing when to run with the numbers and when to run with their guts," says Davenport, adding that there will always be a place for intuition however much analytics progresses.

The levels of success achieved will also depend on the people employed to interpret the data.

"What you want are PhDs with a personality. People with expertise in maths, statistics and data analysis who can speak the language of business and can help market their work internally and sometimes externally," says Davenport. After all, one of the most important parts of successful analytics is ensuring the smooth communication of the findings to those who can then implement them throughout the business.

Analytics is not something reserved just for the business world either. Rudi Giuliani's time as mayor of New York was characterised by a significant fall in crime, an achievement that has been attributed, in part, to analytics that enabled crime hotspots to be identified and targeted with more police.

The trend is starting to filter through closer to home too, with most premiership soccer teams in the UK using analytic systems designed by either ProZone or Omisco to monitor their players' on-pitch actions. Watching this footage back afterwards allows the managers to target training and, in the long run, to ensure their teams are working well together.

One problem with competing in this way, however, is the time and resource it takes to do it properly.

While Jordan Garbutt, business development consultant at ProZone, offers smaller packages to the lower league soccer clubs, for small businesses the opening isn't so easy.

While Davenport insists it is plausible for small firms to be analytically competitive, others disagree, saying that if you haven't already started, then it is too late. For example, at Barclays Bank, its UK consumer cards and loans business spent five years executing its plan to apply analytics to the marketing of credit cards and other financial products as it had to make process changes in virtually every aspect of its consumer business as well as improving the quality of the data on the technical side. These changes cost a lot of time and money, something that many small companies don't have.

Still, with Davenport insistent that this is where the future lies, it seems they are either going to have to cough up or start losing out to larger rivals.

Analytics in sport

With each position in the English Premier League table estimated to be worth about £1 million (€1.4 million), being better than your rivals has never been more important.

While spending money on expensive players can help, as Chelsea proved during the past two seasons, it isn't always the answer and another solution being tested by many soccer, rugby and GAA teams is, believe it or not, analytics.

"People are beginning to realise the importance and benefits of analysis in sport," says Emmett Farrell, a performance analyst at Leinster Rugby Club, adding that it is used by all four provinces and the national team.

According to Farrell, by collating television footage of past matches it is possible to tailor training programmes to suit individual players based on mistakes or weaknesses and even to get a feel for the tactics of a rival team ahead of a crucial clash.

"We can edit a game to just show line-outs or scrums or the movements of one particular player," he says, adding that it has been recognised as improving the combined performance of a team.

The situation is the same in soccer, where most of the clubs in the English Football League use some sort of data analysis in an attempt to improve their game. When Sir Alex Ferguson decides to bring Wayne Rooney off the pitch, it could be because the computer is telling him that Rooney has already covered more mileage than the manager would like him to, given the fact that he is just getting back to fitness.

While this may sound far fetched and over analytical, in the US the manager of a well-known basketball team relied on this sort of data to tell him when his star player was getting tired and used it to optimise his time on the court. "It can be as detailed as counting up how many times one particular player passes the ball to another," says Jordan Garbutt, business development consultant at ProZone, the data collection and interpretation system used by many of the English Premiership teams. "It's the big brother of football."

Hard evidence to prove the benefits of such applications is difficult to come by, but Garbutt insists it is a tool which, when combined with good managerial skills, can significantly improve a team. "It adds weight to what a manager is telling his players to do," he says, adding that one manager recently said he would prefer to have 17 players and ProZone rather than 18 players.

Still, at as much as £100,000 (€142,703) a year for the full ProZone package - including cameras, video equipment and data analysis programmes - this sort of team help doesn't come cheap (the SportsCode system employed by Ireland's rugby teams costs about €15,000).

As a result, it seems the most important thing, is actually the appropriate interpretation of the data.