“Application of data in the enterprise”
By: Leon Clarke
Tags: Payments, Startup, Fintech, Data, Data Science

“Application of data in the enterprise”

“Data are just summaries of thousands of stories — tell a few of those stories to help make the data meaningful.” — Chip & Dan Heath Leon Clarke Dec 17, 2020·5 min read

Take for example, Liverpool football club.

Before Klopp arrived at Liverpool, as manager, the Director of research, Ian Graham assessed every attempted pass, tackle and shot Dortmund players (Klopp’s former club) had made the season before. He fed this information into a mathematical model and evaluated each Dortmund match, assessing each player’s performance in every game.

What Graham found was astonishing — the difference between the mathematical model and reality was huge. Dortmund finished 7th that season, but the model predicted that they should have finished 2nd. Fortunately for Liverpool, Graham concluded that Klopp wasn’t to blame. His team had had no luck! In a 90 minute game of football, where the margins are fine and there are less than 3 goals per game — every little helps, and luck can and does play a relevant part. What was also interesting was that Graham had never watched a Dortmund game — his insights were based on data alone.

So given this, how did Graham get buy-in to be able to use his data insights to benefit the Liverpool team?

Ian Graham and Jurgen Klopp had a chat. After his initial experimentation with Dortmund players, Ian Graham showed Klopp more analysis he had performed. His data set was based on tracking the progress of more than 100,000 players from around the world. The data assessed each attempted pass, tackle and shots on goal for these players. Klopp could march to the beat of his own drum, listening to his “popular players playlist”. After that conversation in 2015 Liverpool won a surprising 2 trophies in Klopp’s first season, an amazing achievement after their years of drought.

This enabled him to overhaul the Liverpool team, buying high quality players at discount prices, based on data:

Name: Mohammed Salah

Birthdate: 15 June 1992

Birthplace: Basyoun, Egypt

Other clubs: El Mokawloon (2006–12), Basel (2012–14), Chelsea (2014–16), Fiorentina (loan 2015), Roma (loan 2015–16, transfer 2016–17)

Bought from: Roma

Signed for LFC: £43.9m, 22.06.2017 (Started 01.07.2017)

Liverpool debut: 12.08.2017

Debut goal: 12.08.2017

Salah’s ability to cross the ball and shoot attracted the attention of Liverpool manager Jürgen Klopp who paid a new club record fee to bring him to Anfield. Salah scored in his first preseason game at Wigan and went on to exceed all expectations. The sensational Salah scored 44 goals in his first season, the second-highest total of any player in the club’s 120-year history. He was voted the PFA Player of the Year, Football Writers’ Footballer of the Year and Premier League Player of the Year. Salah also claimed the Premier League Golden Boot, netting 32 goals in 38 games. Breaking Alan Shearer, the premier league legend’s 15-year record.

Their data-driven culture started from a simple conversation.

In business, to cultivate a data-driven environment C-level executives need to buy-in to it.It is also imperative that they engage with the process of change, and that they have involvement in aligning the data found within their companies real world interactions, to key company initiatives.

So — how could you create this buy-in and alignment? Agree measurable objectives both with the C-Suite, and with the grassroots of the company — those on the front-line with your customers.

At my previous company, we had a product that let merchants store their customer card details in the Vault. The Vault is a one-stop shop for storing, accessing and updating card information for merchants. This product makes it possible for merchants to comply with PCI-DSS without liability, and with less cyber-security expense.

For those getting ready for Christmas, this product is based on a similar concept to that of buying a “bird in a bird in a bird” — it is a “product in a product in a product”.

So, what is the Account Updater and why did we use it as a key measure of whether we were achieving a data driven culture?

Account Updater is a generic term for programs such as Visa’s Account Updater or MasterCard Automatic Billing Updater that are offered by the credit card networks to automatically update subscription customer card data when cardholder information changes or goes out of date.

For subscription companies like Spotify it is important to have the ability to automatically charge Chris’s card every month so that they can collect fees. Chris’s card expires, Account Updater will automatically update a new card expiration date from Chris’s bank, without Chris having to go in and change his card details. Chris gets an uninterrupted customer experience, Spotify gets uninterrupted cash flow. Everyone is happy!

So, how do you use the data gathered in this process (in a customer secure, and GDPR compliant way!) in order to create tangible value, and, what would you use as an OKR, — a goal-setting tool used by teams and individuals to set challenging, ambitious goals with measurable results.

Objective (O): Create standalone products. If a merchant only wants to use a specific feature on the platform, we want this to be possible — Productise! Result 1 (K,R): By the end of 2021, we should be able to offer merchants at least 2 standalone features.

We recognised the value of one piece of data, the Account Updater, and then used that knowledge to create new products that we could charge for. And then we measured that data going forward, to check that we had achieved the required goal — and if we hadn’t, we wouldn’t know why and where any problems lay.

Vanity metrics were removed from Dashboards — they gave us the incorrect impression that we already had a data-driven culture. Goodbye to knowing the number of merchants that had logged onto the platform. Unnecessary tools were decommissioned — Hello to a new drawing board. We started developing an ethos where output was both meaningful and value-adding. It wasn’t going to be a smooth journey — we were using data to gain insights for the first time, and that meant working in an agile manner, and being able to constantly solve the problems that inevitably cropped up.

Data can be liberating, but, it’s important that all stakeholders in the organization view it in the same way. When you first introduce data insights to an organisation, it may act as a wedge that can divide the enterprise into split camps of allies and adversaries, as data-driven cultures drive accountability and transparency right across an organization. This is why it is important to nurture a positive mindset shift for all employees before starting a data-driven transformation. It can only be achieved with C-level executives supporting the change, and being clear on the benefits that will ultimately filter through to all employees.