Distribution Optimiser & Sales Enhancer - Identifying Opportunities through internal data Quintes Analytics Private Limited http://www.quintes.co.in

Quintes Analytics Private Limited http://www.quintes.co.in The Opportunity - Identifying Opportunities Using Internal Sales Data Companies generate/collect data on distribution, servicing, sales, promotions, retailer schemes, display and merchandising etc. Companies can benefit immensely from studying the available internal sales data However, the internal sales data are not fully leveraged for various reasons Lack of resources/time, Absence of a data management and interpretation team Lack of focus, Lack of trust in quality of data, Poorly organized and unclean data etc Quintes Analytics analyses the internal sales data and other available databases and provides inputs at actionable levels to sales and trade marketing teams It is time to ‘Look In The Mirror’!

Quintes Analytics Private Limited http://www.quintes.co.in Identifying ‘Actionable’ Opportunities * : Example of databases that could be used. Not mandatory. Available data would be used. **: OPTIONAL; To evaluate returns on investment; could be calculated internally by client Population, Infrastructure, HDI etc. Consumer Panel Retail Sales & Causal Media Consumer Tracks Other Studies Internal Sales Data Internal Financial Info. For Specific Schemes** External Data* (Examples) Key Internal Data Sources Inputs to Sales & Trade Mktg. By Product By Channel By Sales Team/Person By Store By Region By Distributor

Quintes Analytics Private Limited http://www.quintes.co.in Advantages and Limitations

Quintes Analytics Private Limited http://www.quintes.co.in Aspects of client database analytics Location/ Geography (Districts, Tehsil, town/village) Direct/ Indirect Coverage (Distributors, Wholesale, Lines) Store Classification/Segmentation (Channel, Frequency, Competition) Network/ Logistics (Routes, Hubs, Sales Areas) Product Assortment (Range, Must-stocks, Rules) Product Classification (Segment, Brand, Price Point, Age) - Sales - Promotions - Distribution line Order Placement Delivery New Launches (Select stores) Tertiary Sales Database

Quintes Analytics Private Limited http://www.quintes.co.in Data Organization - The necessary first step and a key enabler Clean robust data, meaningful dimensions/ characteristics/ aggregation with crisp and actionable scorecards are the key to a successful sales data system Evaluate/ enhance the design and quality of existing sales database Develop a scalable data-warehouse - inspect, cleanse, transform, dimensionalise Build links to external databases through key identifiers Integrate data across multiple distribution lines Derive/ review existing result metrics/ dashboards

Quintes Analytics Private Limited http://www.quintes.co.in Store Segmentation and Optimization Classify stores in actionable groups for specific activities e.g. new launches, promotions, activation Segmentation could be based on various factors (region, size, channel, range of products etc.) Identify Top Performing Stores Study variation in performance post classifying stores based on Region, Channel, Store Size etc. Design coverage, servicing, merchandising, promos and other activities based on profile of store groups

Quintes Analytics Private Limited http://www.quintes.co.in Product Distribution and Performance Identify distribution width/ depth opportunities Arrive at distribution norms, SKU range and ladder for brands Manage/ predict stock-outs and returns (reach right, reduce net returns) Key SKU to focus on for distribution expansion Increases sales by 7% by offering the right range Store*SKU expected result in Out of Stock Store*SKU expected result in net returns

Quintes Analytics Private Limited http://www.quintes.co.in New Launches and Product Changes` Identify target stores for new launches Evaluate execution and performance Study cannibalization, positive impact on portfolio Identifying Right Stores to Target for New Launch Benchmark performance against internal targets/benchmarks/external benchmarks

Quintes Analytics Private Limited http://www.quintes.co.in In-Market and Store Level Influencers % Inc. Sales from different promo types/other activities Key Promotion Types that have yielded expected returns Promotional impact is likely to differ by region. Modeling can be done separately by region/channel etc. Key Promo Types for Each Region

Quintes Analytics Private Limited http://www.quintes.co.in Company Distribution Planning and Expansion Identify need for increasing distribution based on factors like: Company reach vs. Category reach Overall penetration of key SKU among existing stores New and Repurchase Store Trends (number & volumes) of key SKU Establish store groups (region * channel * store size etc) to focus on Identify key brands and SKU to drive distribution, in direct (by store group) & wholesale Identified for expansion based on current performance, potential of region*store group and potential for key products

Quintes Analytics Private Limited http://www.quintes.co.in Company Distribution Planning and Expansion Evaluate total reach - direct & indirect Analyse direct distribution - coverage and cycle Validate/ augment existing distributor locations Improve efficiency of sales route plans Coverage evaluation at micro-levels, with recommendations for expansion and route plan efficiency.

Quintes Analytics Private Limited http://www.quintes.co.in Sales Forecasting Short-term forecast for category & select products, for budget plans Augmented forecast using macro-economic and other industry data Link forecast with internal sales data to derive gaps/ share Carve the impact of seasonality/ temperature (if-any) GDP, IIP, Inflation, Money, Deposit Ratio Sales Trend (Time Series)` Distribution, Trade Spends, Competition Weather, Seasonality Right Model Identification Parameter Estimation Diagnostics / Accuracy Forecast Results / Scenarios Brand Sales Category Sales Level Horizon Technique Growth What-If’s MAPE LB, AvP OLS MLE

Quintes Analytics Private Limited http://www.quintes.co.in Sales Forecasting Sales forecasts could be based on external agency data (retail audit)/internal data Key SKU with high growth forecast Identify key segments/brands driving growth Key SKU: Store segments driving growth (Region*Channel*Store Size etc.) for each

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