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October 25, 2006
Retail Analytics: One size fits all?
With the evolution of retail industry, the number and complexity of factors affecting a Retailer / CPGer have grown exponentially. As retailers grapple with ever-shrinking product lifecycles, changing customer behaviour and pressure on margins, analytics driven business intelligence is playing a pivotal role in shaping their decision-making.
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
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Posted by Sam Murphy at 1:00 AM | Comments (0)
October 12, 2006
First blog post
First of all, this is a fantastic blog site. Of all the blog sites I've seen, this to me takes the cake.
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!
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Posted by Sam Murphy at 9:15 AM | Comments (0)
