Some forty years ago, most retailers struggled to keep count of their sales and inventory as they expanded. These were the times when the first tentative steps were made towards adopting the ever-improving computing abilities. A case in example is Wal-Martโs leasing of an IBM 370/135 computer system in 1975 to maintain inventory control for all merchandise in the warehouse and distribution centers and to prepare income statements for each store. These were the first building blocks towards integrated IT architecture connecting stores to warehouses, home offices and vendors that are a staple now for any large retailer. The dilemma that faces these retailers is not a lack of data but an explosion of it.
Walmart today receives 100,000 footfalls in its US stores, in a week(!). Even in the online space, it is estimated that Amazon will receive almost a billion visits this year. Each of these visits culminating in a transaction is recorded and stored in a warehouse and triggers a heavy-duty replenishment and forecasting system, tracked for unusual sales patterns and sometimes is the first domino falling and culminating in a production cycle at the supplierโs end.
The challenge most retailers face now is in extracting insights from this data beyond this replenishment chain. Analytics, backed by robust data management, has the capability of burrowing into these mountains of data, too gargantuan now for any human effort, and of discovering patterns invisible to the statistically-unaided eye. It offers these retailers the capability to transform their businesses.
A few of the capabilities that analytics offers for retailers are:
โข Better demand management leading to higher fill rates โข Better ROI by carrying the right assortment and balancing the inventory with demand โข Profit maximization by optimizing pricing and promotion strategies โข Optimizing the marketing spends for maximum ATL and BTL impact โข Localizing the global retailerโs proposition to realize stores of the community โข Identifying and retaining their best customers, and tweaking their overall proposition accordingly
But with only a tentative understanding of the range of capabilities now at their disposal, and a shortage of skilled analysts and knowledgeable champions, most retailers remain marooned and overwhelmed in the sea of this data. The reason which has impeded these retailers from taking the full benefit of these capabilities has been that analytics has still largely been relegated to the IT division as a data warehousing and management issue, rather than a strategic weapon. The result has been that published MIS reporting and basic ad-hoc business intelligence have been mistaken for true analytics capabilities. Traditional managers are still suspicious of suggestions of building strategies around analytics. Many managers are still to digest the fact that todayโs businesses are bigger and more complex than ever, and yet remain more accessible than ever in the vastly improved data management and analytics capabilities in the recent years.
The question that begs to be asked is why these managers have failed to keep pace with these developments. Partly, it is the inertia and fear that accompanies paradigm shifts that upset traditional patterns of work. (A reason why web-based retailers, who are closer to emerging technologies, have embraced analytics far more fully than their traditional counterparts). Citing a few personal experiences, these managers are skeptical about the claims of this revolutionary technology, believing them to be greatly exaggerated. Their own understanding of applied statistics in management being tenuous at best, the few pilots commissioned are trusted to internal IT teams or IT vendors, whose own understanding of analytics is restricted at most times to business intelligence. The few analytics vendors who could have bridged this gap, in turn, have only a nebulous idea of the actual challenges faced by todayโs retailers and leave the senior management they meet more unconvinced about the application of analytics to their business beyond tactics. In the end, it becomes a self-fulfilling prophecy. The retailers, molded in the traditional school of management, are late to adapt to analytics, and trust it only to the level of useful but not strategic information, advised by team and vendors with incomplete understanding of applied analytics or the retail business or, many a times, both. And yet there is an urgency among the retailers today that the seats on the express train they are too skeptical to take might be taken by someone else. The customer is no longer a single community but many communities spread across geographies, disparate in culture and habits, and expanding everyday. The competition is no longer the store across the street, but comes in many channels as spectrums, mobile and web, expand. More new products and lines are being introduced every month. Realizing the shortcoming of traditional methods of management that has ignored the tremendous potential of analytics, these retailers have adopted a me-too strategy, mimicking the more successful retailers, who have been invariably early adopters of analytics, but only half-realising its full benefits.
The opportunity is there for the taking. A whole pie waiting for teeth to sunk upon. The retail landscape, ever-expanding and mutating, shaped by new-age competition defying traditional retail channels and practices, with bankruptcies multiplying, has shaken many retailers out of their inertia. Worried over sustaining the competitive advantages to survive, they slowly turn to the alchemy of analytics, to turn the data trapped in their servers to insights worth their weights in gold.
The time is ripe for analytics men, but for that they would have to move beyond their own traditional mindset of solution-providers to business consultants. To develop a robust understanding of business along with analytics and fit solutions to challenges rather than the other way round. To become the alchemists these retailers await.
Interested in a career in Retail Analytics? Explore Jigsaw Academy’s Retail Analytics Course.
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