Times they are a-changing and there is now a role for it in the sector
Is data the new gold? No, it is not. It is old gold that has been deep buried in wholesalers’ systems for years. It is the extraction and exploitation of the data that is new. This issue of Better Wholesaling Insight is a veritable feast of all things data and digital. A subject gaining in importance and column inches across our industry. This is why data companies such as b2b.store, TWC and Circana want to collaborate with you. To help unlock the power of your data. Wholesale is a simple business. You buy at one price, sell at another and make a turn in the process. Keep the costs tight and profits will flow. Let’s not complicate it. What gives with all this data stuff?
Here is a data story. In 2002, Oakland Athletics was an under-performing baseball team in the American League West. A small-town outfit on a limited budget. General manager Billy Beane was becoming increasingly frustrated with player recruitment. He was never able to attract even half-decent players in the recruitment draft and so perpetuating the culture of loss and mediocrity. Beane knew that he somehow had to break out of this cycle of failure. His panel of senior scouts using their best judgment was not coming up with the right player picks. By chance he met Peter Brand, a Yale economics student, and a mad keen baseball aficionado. Brand’s deep knowledge of the game had prompted him to devise a statistical data model to identify player performance and value. He called this “Sabermetrics” and, after many attempts, Brand convinced Beane to adopt his method for player evaluation. Beane and Brand identified and signed undervalued players and after a poor start to the season, Oakland went on a surge to win the league against all odds.
This quickly came to the attention of John W Henry, the owner of the major league baseball team in Boston, the Red Sox. He adopted the Sabermetrics system and, in 2004, Boston won the Baseball World Series for the first time since 1918. It just so happens that John W Henry led the Fenway Sports Group (FSG), and when they bought English Premier League football club Liverpool in 2010, Henry immediately introduced the data-driven approach to player evaluation at the club.
Football is a simple game. All you need is a ball and a couple of objects to define the goals. The game can be played anywhere and the team scoring the most goals wins. This is its universal appeal. No need to complicate it. Goals are the only statistics that matter right? Yes, and no. Under FSG’s ownership, Liverpool FC has taken the lead on a digital approach to player acquisition, performance and game time. This gives the coaches serious competitive advantage. For example, those little black vests you see the footballers wearing contain GPS trackers so that coaches can analyse the movement of players throughout the game. Liverpool employs a data scientist and large data team, which has contributed to an upturn in success over the past five years. Unsurprisingly, all Premier League clubs now employ data teams. They are regarded as an essential part of the management team.
So, what does give with all this data stuff? Elite sport is a multibillion-dollar industry where small margins make a significant difference. Results are all and everything. Simply put, data = information = knowledge = insight = performance. As EY online reports, many businesses consider data to be central and core. Data benefits business – from providing real-time intelligence that empowers private businesses to make better commercial and strategic decisions, to ensuring they run their operations more efficiently, and it doesn’t stop there.
Data also enables organisations to analyse past performance and make insightful predictions about future trends. Take German e-commerce retailer Otto, for example – when it looked for ways to reduce their volumes of product returns and unsold inventory, it used a combination of artificial intelligence and analytics to analyse historical transactions so they could more accurately predict future orders and automatically determine procurement needs from vendors. The outcome? Products were delivered faster, returns were reduced by over two million items a year, and surplus stock declined by a fifth. A massive uplift of financial return on activity.
In wholesale, it is accepted that it is more fruitful to focus on retaining existing customers rather than going hunting for new ones. Yet wholesalers continue to invest in salespeople who tend to morph into quasi account managers and glorified order-takers. What if some of that resource was diverted to employing a Peter Brand-style customer file data analysist? Taking a digital approach and deep dive into the customer records. So, who are the most valuable customers and how is ‘valuable’ defined? Most certainly, wholesalers know their top 100 or top 10% of customers by turnover. But do they know their top customers by profit or net contribution, and if delivered to, do they know the net profitability by customer?
I would argue that delivering high volumes of low-value bulky products such as bottled water or toilet rolls is not as profitable as supplying lower volumes, but higher-value and physically smaller items, such as toiletries or cleaners. The mix of sales is a key dynamic in a delivered operation. The data analyst would identify those customers under-indexing across the profitable categories prompting the business to take action to broaden purchasing into those sectors. The business may also need to put in order riders to mitigate against unprofitable activity.
And what is revealed if the customer file is sorted by order frequency? Clearly this will vary by customer type, but if the customer is, say, a retailer and not shopping at least weekly – they are not using you as a primary destination. Taking that a stage further, how is ‘primary’ defined? Some drilling down beneath the surface may reveal that while the customer numbers are holding up, there is attrition in the frequency of purchase. It may also discover a trend of reducing transaction values and an erosion in product mix, leading to lower margins.
Looking at trends and patterns, the data analyst will identify those customers who are gradually spending less either on frequency or value. Those customers are likely to be heading for the door: lapsed or lost. Management can step in to initiate corrective action before it is too late. And the converse to this is true in that the analysis will identify those opportunity customers who are on an upward trend and may welcome a management intervention to help them grow sales in a given category and incentives to broaden their purchases. A nudge upwards will get them into the top tier.
There is also the analysis of what the customers are purchasing. Are they buying across the range, the best products for their business, or focusing on single or limited categories? Do they simply purchase promotions, and how do they respond to your outbound marketing? Which marketing channels are working the best? Brochures, flyers, emails, WhatsApp etc. The insight in these areas will guide management to hone their marketing activity and customer engagement.
We all understand the importance of relationships in our industry. Billy Beane at Oakland was conflicted between his intuitive feel and what the data was telling him. As a leader, he had to overcome pushback from his senior scout panel and to find a balance. He came to realise that data works alongside knowledge and experience, and so it is with wholesale. There will never be a substitute for symbiotic business-to-business relationships, but data offers real insights and does significantly contribute to success.
David Gilroy is the managing director of Store Excel
