Sent to you by Joe via Google Reader:
http://www.infosysblogs.com/retail-cpg/2009/09/how_significant_is_business_in.html#more
I then started to dive deeper into those focus areas and analyzed how BI can assist companies in improving customer satisfaction and loyalty
http://www.infosysblogs.com/retail-cpg/2009/10/how_can_bi_improve_customer_sa.htmlHaving analyzed one of the most important external stakeholders, let us now look at the other key stakeholder who is positioned at the upstream of the supply chain – the supplier. What are the challenges faced by organizations in the food industry on sourcing and procurement? Are there opportunities to do better? What is BI's role in this?
SKU Rationalization
Food distributors typically carry a large amount of SKUs – probably in hundreds of thousands which cannot be fathomed by a retailer or a CPG company. And a good portion of those SKUs might not be as profitable as other SKUs and in fact bring down the overall margin considerably. How do you decide which SKUs to carry and which SKUs to discontinue?
Analytics can provide the visibility of item profitability location-wise, region-wise and company-wide. Using MDM as the backbone, analytics can also provide visibility to alternative SKUs if the company decides to discontinue a particular SKU. Of course, you cannot base your judgment purely on the profitability of a particular item. You might carry an item for a strategic reason and decide to carry it irrespective of its profitability. But in general, BI can provide the platform for the sourcing organization to recommend optimized SKU list. They will get lot of push back from the sales force, but powered by the data provided by BI, sourcing team should be able to justify discontinuance of certain items.
Strategic Sourcing
In lot of organizations, sourcing decisions are taken at the local level and corporate does not have too much influence into the whole sourcing process. This results in too many suppliers to manage and a lost opportunity of better price through large scale buying.
BI can provide visibility to all the purchase data across the company which will help the sourcing team get visibility to the volume. Using that ammunition, they can trim the number of suppliers (after careful analysis) and negotiate hard with the short listed suppliers for a better price. The suppliers will also be inclined to lower the price if guaranteed a higher volume. So, it is a win-win situation powered by BI
Forecast Accuracy
After the decisions on what SKUs to carry and the corresponding suppliers, the next challenge is how much to order? Forecast accuracy is a huge challenge for any company and it gets magnified based on the size of the company. Some of the forecasting tools that are available are very robust. But they can be only as good as the data they get as the input. If it is garbage in, then it is garbage out. Availability and accuracy of relevant information are very important for accurate forecasting. Though BI cannot directly play a role as the data required for forecasting has to come from transactional systems, but it does provide the mechanism for checks and balances to ensure that the forecast is accurate. Using the rich history of data in the data warehouse, powerful analytics tools can be built to verify the accuracy of the company's forecasting mechanism and processes.
Inventory Visibility
Accurate forecasting in isolation will not answer the question of how much to order. Visibility to inventory data across various warehouses is extremely important. Without the visibility to inventory data, there is every opportunity for over order or under order. Under order situations will lead to dissatisfied customers whereas over orders will result in wastage/shrinkage as well as increased inventory carrying cost. BI acts as the frontend to provide the desired visibility at the appropriate time for the procurement teams to make intelligent decisions.
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