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Case Study: Data Analytics - Retail Demand Forecasting


Market Equations provides Predictive Analytics & Modeling solutions to companies worldwide aimed at providing and promoting a Fact based decision-making culture in all organizations. We collect, analyze and interpret data to uncover interdependencies and hidden truths through an integrated process. Simply put we deliver Actionable Intelligence. Intelligence that translates into a positive marketing message that works all the time.

The company is a large textile manufacturer based out of UK


Requirement:

Demand forecasting – The Company is facing a problem with forecasting its demand from retailers all across Europe.

  • Stock Outs

  • Large Inventory levels

  • Resource time spent in this activity in-house


Therefore the client requires an outsourcing partner to look into the above problem and provide a solution at the earliest.

Current Issues:

The following are some of the issues faced by the company:

  • Huge variety of Lead Times

  • A variety of Minimum Quantities

  • Client received very little demand forecast from its suppliers

  • Lead times are effected by supplier “annual holiday” closures e.g. European August shut down and Chinese New Year

  • 3 of its largest customers in one business unit provide EPOS (Electronic Point of Sale) data. These are the numbers they have actually sold out of the stores. This is valuable information but client rarely have time to consider the relevance of the numbers. Etc...


Market Equations offers Predictive Analytics and Modeling solutions to organizations worldwide to assist them with their decision support requirements.


Information Storage:

The data relevant to stock forecasting, stock control etc is stored in a centralized dedicated server. However, the issues lies with the organizing the data based on need.

Solution:

As each product needs to be considered independently (although an effort was made to cluster products into groups) the following routine was to be followed with each product:

  • Analyze Past Sales History

  • Look at any Seasonal Variations

  • Consider the potential minimum re order quantities and determine if they would give an excessive stock commitment

  • Determine if there have been any extraordinary usages (perhaps a special order item for one customer)

  • Determine how many customers are now purchasing the product (and any new customers who have the potential to adversely effect the item)


Current Status:

Due to the complexity of the project, a proper assessment of these however requires a deeper understanding of the client’s requirements, budget, and the level of commitment to the project. For example, to do the job properly the problem of such nature can take a long time to completely develop, validate, and deploy the tools; and that too depends on putting together:

  • a team of right mix of talents with deep skills and vast experience in appropriate areas of specializations

  • right type of software/technologies to build the tools. We think therefore an initial consultation session should be arranged with the top management of the organization. Such business logic consultation can be done in various formats but we would prefer a 2-day on-site visit by a team of ME consultants composed of 2-3 experts.


ME built a strong relationship based on mutual value with the client and currently is in discussion with the company to automate their Finance department. Number cannot be disclosed due to confidentiality but to provide a preliminary understanding the Company claims to save at least 30% through their commitment to this effort.

(References will be provided on request only.)

Explore how the Market Equations Consultative Approach to decision making works wonders.






Outsourcing Market Research and Statistical Data Analytics to India can help you achieve cost and time efficiencies, high quality and access to a vast pool of intellectual resources. You will gain competitive advantage by outsourcing Business and Market Research support services, Survey design and programming, Data Processing, Survey Data coding, Cross tabulation, Charting,High end Statistical Data Analytics and Reporting on specified templates.

 
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