How to Transform Your Retail Enterprise with Advanced Analytics
How to Transform Your Retail Enterprise with Advanced Analytics
Last month, Parker Avery President Clay Parnell, wrote about key capability areas retail leaders must prioritize as we head into 2023 (“Retail 2023: Back to the Future”). Clay outlined the implications and requirements of enhancing business capabilities across assortment curation, product development, merchandise financial planning, allocation, and replenishment, and he touched on what we call “enterprise intelligence.”
This month, we dive into areas where analytics can augment key business functions and how any modern retail transformation must include analytics to drive enterprise intelligence and meaningful business results.
Optimize Order Fulfillment
Clay spoke about “the last mile” focusing on order fulfillment and how store clustering and assortment planning capabilities can help optimize what retailers offer and where they offer it.
When viewed through this lens, analytics are essential to helping guide merchants with a forward-looking view of demand potential versus relying on hindsight only. The perspective provides an aggregate view of product trends and the total buy required. In addition, leading retail analytics platforms can enable a granular view of product mix and quantities required to meet demand down to specific distribution centers (DCs) or third-party logistics companies (3PLs) and ultimately to the individual store locations.
For buy-online-ship-from-store (BOSFS) and buy-online-pickup-in-store (BOPIS), the paradigm of a brick-and-mortar-centric view is no longer appropriate. The demand must be analyzed and viewed via a trade area lens, considering not just brick-and-mortar demand but also the broader omnichannel demand (wherever it originates). In this view, analytics can predict where and how to best serve customers. This delivers a high service level and helps manage efficiency and sustainability implications.
In the case of BOSFS, a key consideration is to reduce the number of split shipments. Leading retailers do not just predict assortments and quantities by location. Rather, they leverage analytics to determine what basket of products will be purchased together. This next level of analytic sophistication helps retailers to reduce the number of split shipments, enhance fulfillment efficiencies, and ultimately increase margins.
Many existing retail systems can be augmented with modern AI/ML analytics to make them decisively more intelligent.
Analytics can also address the issue of excess inventories while considering markdown implications. There is a strong case to be made for going outside the immediate trade area to service online orders especially given heavy residual inventories caused by broken supply channels and overlapping/missed seasons. Again, analytics can and should be used to optimize ship from locations when deciding where to best fulfill online orders. In this application, analytics help find where the inventory resides and determine where and to what extent inventory is at risk of not selling through. Advanced analytics can predict the cost of a future markdown in that location versus the fully loaded cost to fulfill from that location. Leading analytics platforms will recommend what product to ship from what locations to maximize margin and sell-through.
Enhance Product Development
Clay also outlined the use of spreadsheets and aged, disjointed retail legacy systems to manage the product development process. Product lifecycle management (PLM), product information management (PIM), and digital asset management (DAM) systems are ripe for integration with analytics, particularly leveraging artificial intelligence and machine learning (AI/ML). More specifically, proper use of attribution in these systems is fundamental to:
- Enabling how AI/ML handles product hierarchies
- Producing a demand signal consumable by different functional areas
Stronger focus on product attribution results in better analytics, and ultimately significantly more accurate predictions of demand. Moreover, the relationship between analytics and PLM is circular since a more accurate demand signal drives better insights into what attributes drive consumer tastes and preferences, which, in turn, refines the PLM strategy.
Modernize Merchandise Financial Planning
I once heard that executing merchandise planning without leveraging predictive analytics is like driving a car 100 miles an hour and only looking through the rearview mirror. Retailers can base their planning on a historical view of the same season, or they can plan strategically with a forward-looking prediction of what is likely to happen, considering the current business environment as well as external variables.
Analytics can and should be used to provide a “future fact table” from which to seed the pre-season plan. This approach allows the organization a common vantage point to guide organizational collaboration on where and to what degree investments should be made across product classifications. Similarly, when in-season, the system replaces plan values with actuals while the analytics update the forecast for the balance of the plan. This revised view not only indicates how classifications are performing in-season and the actual sell-through vs. the plan but also guides decisions on where to spend markdown dollars as well as where to release additional OTB funds.
Executing merchandise planning without leveraging predictive analytics is like driving a car 100 miles an hour and only looking through the rearview mirror.
Augment Allocation and Replenishment
Many retailers are still managing allocation and replenishment with older technology. The fallacy is retailers must replace these legacy systems to realize productivity gains from more up-to-date technology. For some legacy systems, this may be true. However, many existing allocation and replenishment systems can be augmented with modern AI/ML analytics to make them decisively more intelligent.
Transform to Enterprise Intelligence
Advanced analytics should no longer be viewed as a nice-to-have or a siloed application for select functional areas, but as a transformational enabler for achieving true enterprise intelligence and agility. Certainly, many retailers have employed at least a basic level of analytics for a while. But these systems are mainly focused on select areas and are highly disparate. For the most part, traditional retail analytics systems simply do not have the ability to promote internal collaboration or drive functional efficiencies.
For those retail organizations who understand that any modern transformation must include analytics, the following are critical tenets:
- Consider all three legs of the transformation stool: people, process, and technology. One without the others will not drive sustainable capability improvements.
- While there is value in ensuring an analytics-driven mindset, the organizational goal of a transformation to enterprise intelligence is twofold:
-
- Alignment: common data, common analytics, common facts
- Collaboration: break down silos and promote collaboration across the enterprise, driving productivity and efficiencies at all touchpoints
Traditional retail analytics systems simply do not have the ability to promote internal collaboration or drive functional efficiencies.
- Focus on your data. Specifically, develop proper hierarchies that help optimize planning and analytics, as well as a core set of attributes that are consistent and complete across all products. Further, scrutinize your transactional data by location and channel and get it in a place where advanced analytics can most optimally use it.
- Reach out to trusted advisors who can help define your retail capabilities roadmap with a clear focus on properly infusing analytics into your business processes and who will help navigate you through your journey.
Retail enterprise transformation leveraging advanced analytics is a journey and not a race. Further, the journey does not need to be taken all at once. Take it at your own pace, one step at a time. Pick your top focus areas, start small, build successes, and rack up wins along the way. The Parker Avery Group has worked with global retailers across all of the areas discussed in this article. Please reach out to us to explore how we can help transform your retail enterprise.
