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Supply Chain & Logistics Optimization

With Globalization and advances in transportation technology, supply chains are getting more complex with ever increasing demands on them.


The global supply chain can be divided into supply chains of logistics, logistics services, sales, and distribution/transportation. All of these supply chains are interconnected and require a comprehensive approach in order to understand and manage them.


In WINNOVIA, we help organizations design and implement effective supply chain management operations and processes. We provide industry analysis, training and consulting services, as well as tools and guidance to organizations on the use of these tools and techniques in the supply chain management.

Choice-Based Conjoint Analysis

To uncover consumers’ preferences and uses that information to help select product features, assess sensitivity to price, forecast market shares, and predict adoption of new products or services. Conjoint analysis works by breaking a product or service down into its components (referred to as attributes and levels) and then testing different combinations of these components to identify consumer preferences.

Marketing Mix Modeling

Marketing Mix Modeling is a technique which helps in quantifying the impact of several marketing inputs on sales or Market Share. The purpose of using Marketing Mix Modeling is to understand how much each marketing input contributes to sales, and how much to spend on each marketing input.

Marketing Mix Modeling helps in the ascertaining the effectiveness of each marketing input in terms of Return on Investment. In other words, a marketing input with higher return on Investment (ROI) is more effective as a medium than a marketing input with a lower ROI.

Prediction Modeling

Organizations are turning to predictive analytics to help solve difficult problems and uncover new opportunities like:


Detecting fraud. Combining multiple analytics methods can improve pattern detection and prevent criminal behavior. 


Optimizing marketing campaigns. Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers. 


Improving operations. Many companies use predictive models to forecast inventory and manage resources. 


Reducing risk. Credit scores are used to assess a buyer’s likelihood of default for purchases and are a well-known example of predictive analytics. 

Routing Optimization

Truck routing optimization is a key component in the Supply Chain Optimization area. When truck routing optimization is well done, it can drive immense efficiencies of scale. 

WINNOVIA provides expert solutions in Route Planning and Optimization  with planners able to visualize optimized route plans, perform mid to long term capacity planning through achievable sales target scenarios and drive efficiency and productivity by cost effective ways keeping the customer happy.


  • Retail & Wholesale

  • Manufacturing

  • Marketing & Communications

  • IT & Telecom

  • Pharmaceutical

  • ​Financial & Professional Services

  • Architecture

  • Design & Engineering 

  • Energy

  • Resources & Infrastructure


Using operations research mathematical models to study real problems that companies may face, whether in reducing expenses or achieving the highest possible profits, especially during downturn conditions.

Operations research can be used to solve the following problems:
1. Organizing human resources and optimizing the use of the workforce.
2. Designing production and assembly lines in factories with the aim of reducing cost and speeding up production.
3. Choose the optimal route in terms of speed, safety, cost or from all these aspects combined to deliver goods from factories to distribution points or to customers.
4. Reducing queues, such as queues in government centers or private institutions.

Marketing research models used to answer questions like:
1. Testing the appeal of a new product
2. Understanding product deletions
3. Portfolio optimization
4. Assessing the impact of changes in product design
5. Pricing optimization
6. Understanding psychology: purchase hierarchies
7. Understanding psychology: preferences for attribute levels
8. Product optimization
9. Computing brand equity
10. Market segmentation

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