3SC’s supply chain practice gives scalable, sustainable and system driven value through advisory services that optimize, digitalize and improve the supply chain end to end. Big data is certainly enabling better decisions and actions, and facilitating a move away from gut feel decision making. But as more reliance is placed on algorithms, data and analytics, the question of trust is emerging as an important consideration. This again emphasises the need to really trust in the analytics to be confident in decision making

Predictive Analytics – What will happen?

We model the ecosystem and simulate scenarios to predict likely future outcomes. Our Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models used, are to analyse current data and historical facts in-order-to better understand the customers, products and partners and to identify potential risks and opportunities for a company. We use number of techniques, including data mining, statistical modelling and machine learning to help analysts make future business forecasts.

  • Demand Side Attribute Profiling
  • Demand/ Sales Forecasting
  • Supply/ Component Forecasting

Prescriptive Analytics – How can we Optimize?

Designing global supply chain networks is a complex process. There are various inputs to the process where many decisions must be made keeping the best interest of all stakeholders in the chain. Companies have to answer many questions before finalizing on the design. Where to locate new service facilities (e.g. plants, warehouses), how to allocate procurement and production activities to the various manufacturing facilities and how to manage the transportation of products through the supply chain network in-order-to satisfy customer demands. Isn’t simple, right? Relax! We do the difficult part and simplify it for you. We at 3SC project / simulate how alternative risk management strategies will impact the client performance. While designing your supply chain, we provide solutions to ensure maximum optimization. We prescribe actions to take for optimising performance outcomes

  • Network Design and Optimization
  • Inventory Optimization
  • Last Mile Design and Optimization
  • Warehouse Optimization
  • Load and Equipment Optimization
  • Pallet and Packaging Optimization

Descriptive Analytics – What happened?

How many different segments of buyers are we dealing with? Where are they, and what do they look like? How do high value customers differ from barnacles? What are they interested in? At times we may use terms such as profiling, segmentation, or clustering, and they fall under descriptive analytics. Usually, the underlying data is a count, or aggregate of a filtered column of data to which basic math is applied. Descriptive statistics are useful to show things like, total stock in inventory, average dollars spent per customer and Year over year change in sales. Common examples of descriptive analytics are reports that provide historical insights regarding the company’s production, financials, operations, sales, finance, inventory and customers. We describe the ecosystem under consideration using data to identify trends by:

  • Standard reporting
  • Ad hoc reporting
  • Query/drill-down
  • Dashboarding, visualization