Managing 200,000 active SKUs, 200 categories, 20 departments and a host of variables in a complex, ever-changing environment - a typical supermarket business challenge - and a merchandiser's next big win might lie in unlocking timely, useful and actionable insight from this maze. Oh yes, its possible!

While everyone's thinking about empowering retailers with better BI tools and technical features, there is a different business centric approach that some are taking thats creating a new wave and significant market traction; they are pre-building what retailers do (with their eyes closed) into their solution, so that they can do all they were doing with a horizontal BI and yet have the time and the power to take it to the next level. They call it retail BI.

These solutions contain an extensive collection of retail KPIs available for tracking business and accessible through a wide range of pre-built reports and analyses; and it can be adapted or extended to suit a retailer's specific needs through a complete set of BI tools and features.

How did they do it, you ask? Well, they got retailers to build it - a collective brainchild of some of the best practitioners from successful retail & consumer goods organizations in collaboration with an outstanding BI/DW technology team. The result - a BI solution that speaks the retailer's language - a BI solution with best practices guaranteed.

So how does one take a grocery retailer's BI to the next level? Let's talk about their business - a highly competitive, time-bound and margin driven environment where merchandising and operations managers have to manage sales, merchandise, inventory, service levels and at the same time look out for revenue and profit maximization opportunities using category management tactics - pricing, promotions, assortment and shelf presentation.

On top of that, fickle customer preferences, increasing competitive pressures, decreasing loyalty, and unstable gas prices make the task even more challenging. One has to be constantly on ones toes to leverage that small but ever present demand that moves them ahead of their competition. They want their customers to have a better experience, offer new products and choices, deploy engaging marketing programs, and offer better value through accurate pricing and promotions; While at the same time keep costs down, inventories low, service levels higher, logistics on time, and stock outs low.

Managing complexity isn't easy when you don't have enough time, resources and most important of all - the right information & insight at the right time. That's where the power of retail BI comes in. Retailers need to integrate their analytical information into a business framework that is complete and comprehensive, yet presented in a simple, intuitive and actionable way. The biggest value of a retail BI business framework is to make a retailer's decision-making environment simple yet holistic!

What does a retail business framework for food/grocery retailing mean? For starters, it should have the ability to track weekly sales and margin trends, compare performance for same stores, GMROI and transaction size per sale, analyze merchandise trends, performance of private label vs. national brands, drive category assortment decisions by measuring category profitability, assortment and brand contributions, price-performance, promotion lift and promotion effectiveness; and inventory productivity. It's metrics and analyses should also guide supplier relationships, which is critical to better operational execution. At the store level, it should track store execution performance, shrinkage and damages, labor costs and productivity.

From a technology performance standpoint, food/grocery retail generates terabytes of data - sales transactions, purchases, and other supply chain transactions on a large set of SKUs, suppliers, customers, stores, DCs and other entities/events. The DW-BI architecture now needs to take into account high transaction volumes, requirement for sub-day level grain of reporting - often at the SKU level, in addition to the inherently cross-functional nature of analysis.

This environment needs a powerful, yet responsive BI/DW solution; one that is able to pull insights across strategic and tactical business contexts in a broad range of hierarchies, attributes and facts like financials, stores, regions, merchandise, customer, inventory, price, promotions, new product introductions, markdowns, loyalty, distribution, logistics, plans and targets.

If you've had a bad experience with the length and complexity of a BI deployment, we don�t blame you for that. When you are thinking about a better BI investment, consider this - You buy a horizontal BI software, but that takes a couple of years to build, months to get used to, and of course more months to refine and stabilize for business use. Every time you have a new set of requirements, you go through the whole cycle again. Frustration spins out of proportion! ROI has no meaning anymore!

That's where retail BI comes in - retailers can get going in less than half the time and cost it takes for their current BI/reporting solution options. In the same time, their business users would have realized far more from a lesser investment. Don't believe me? Email me at ajith.nayar@manthansystems.com to know how fortune 500 class retailers have benefited from upgrading to a retail BI solution.

The retail industry has diverse sub-segments - food, non-food, speciality merchandise (which in itself is diverse), catalogue, convenience stores and wholesalers. Each of these segments have unique needs in terms of analysis and decision support. For example, color-style-size analysis has no meaning for a food retailer, and a DSD performance by vendor report will find no place at an apparel retailer.

Therefore, what's needed is BI that is specific to the type of retailer. For example, BI for Fashion Retail or BI for Mass Merchandisers.

Know any solutions that do this? I know of one - it's easy to find out!

Retail Analytics has at its core the process of taking data from multiple sources of the retailer’s business cosmos and churning business intelligence that enable performance improvement. The key result areas of a retailer evolve with the maturity of the retailer as well as the industry.

Consequently, the focus areas where retail analytics can make a tangible impact also evolve during the lifecycle of the retailer. Retail analytics cannot be not viewed as a black box that should be taken or left alone. The retailer should identify its analytical requirements to ensure fast, efficient and cost-effective decision-making, based on the stage of evolution that the retailer is at.

In essence, analytics is only an enabler that the retailer can leverage to meet its objectives - “make more customers buy more and make them more comfortable with the retailer.”

Over time, as the retailer matures, it progresses along several stages. We can analyse the lifecycle in four phases:

• Start-up


• Expansion


• Maturity


• Decline / overdrive

Each stage requires a corresponding jump in organizational complexity - disciplines become departmentalised, motivations of people become different, contrarian points of view are dulled and decisions bog down. Hence the role of a function that helps “make sense of it all” becomes more conspicuous. That role is played by retail analytics.

Retailer’s Business Landscape
The key decision variables for a retailer are based around five major factors: suppliers, customers, competitive landscape, external factors (economy) and internal operations.

Success of a retailer is dependent on how it is able to analyse its dependency on these factors at various stages of growth and focus on preparing itself for the change.

The key decisions variables and the growth drivers are different at each stage of organization evolution. Hence appreciating the varying growth drivers and focused analytics to best-enable decision making around these drivers will result in maximizing ROI on analytics. The key focus areas and how specific retail analytics can address these during the various stages is elucidated below.

Start-up phase
During the start-up phase a retailer needs to analyse competitive landscape including the range, pricing and positioning in customers’ minds.

Based on the analysis the retailer needs to identify and validate the positioning that it needs to establish in the consumer’s mind. Consumer analytics (purchase behaviour, segmentation & positioning) is the key to success at this stage.

Expansion
Once the retailer has successfully built a market position with its first few stores, it aims for an accelerated growth in the segment. The focus is on building top-line by expanding to multiple geographies and maintaining operational profitability.

The retailer needs to fine-tune its positioning in the market-place by analysing the location-specific consumer behaviour. Demand forecasting, location specific consumer purchase behaviour analytics and ensuring product mix are the key analysis that the retailer should focus on at this stage of its growth.

Maturity
Once the retailer has grown to a considerable size and has significant market presence, externalities play a pivotal role in its growth. The focus at this stage is ‘turf protection’ and maintaining profitability. Significant investments are required to ensure operational efficiencies.

The analytics needs are highest at this stage, as the retailer needs to take a macro (plan across channels and geographies) and micro (local market customisation) perspective at the same time.

Decline / Overdrive
With size the retailers tend to lose their nimbleness and agility to respond to market dynamics – mainly changing demographics, emergence of new channels and stiffer unforeseen competition. At this stage the retailer runs the probability of declining market share.

The retailer needs to reinvent itself at this stage by rethinking its fundamentals, primarily positioning and choice of format & channel mix.

Conclusion
Understanding the retailer’s lifecycle superimposed on its business landscape will help define and prioritise the evolving business intelligence needs of the retailer. Once this is understood, the retailer can then best utilize key driver-specific analytics to achieve performance optimisation and thereby the business objectives.

To get a better handle on how analytics can change your organisation positively, visit the ARC website

I hope to start posting as soon as I have calmed my nerves and collected shareable thoughts.

For starters, we are Manthan Systems, the engineers of ARC - the integrated retail business intelligence suite.
www.arc-bi.com.

Watch this space!