Business sustainability is often affected by the volatility of supplies and changes in demand forecasts. One of the key reasons for this is that planning is done around past data, and dynamic parameters are often not factored in. Supply chains of businesses generate huge variety and volumes of data. The recent Covid lockdowns of economies in different parts of the globe put a spotlight on the supply chain of essential commodities. Upon lifting the lockdown, ensuring production, stocks, raw material supply, transportation and customer demand were closely aligned and could be achieved by those companies who had already invested in digital platforms. Supply chain analytics came to their rescue and helped them meet the demand.
Supply chain analytics is no longer seen as a post mortem analysis of internal efficiencies alone, but has sprung into prominence owing to the necessity of blending the external parameters with internal data for key decisions to be made that have had a huge bearing on business continuity and innovation. All types of analytics – descriptive, prescriptive, predictive and cognitive – could be applied to help solve problems, mitigate risks and predict future scenarios based on internal and external data, driving innovation and responding to customer needs in a timely manner.
Critical functions such as inventory and operations planning, sourcing, manufacturing, storage and warehousing, logistics and sales are connected with one another through a well-planned supply chain analytics system and can transform the performance of the supply chain. Supply chain analytics cuts across functions and disciplines, and the insights highlight inter-related trends that help in internal and external risk assessment, scenario building for stock-out situations, identifying pockets where expenses can be contained and alternate models for safeguarding profitability.
One of the key factors preventing organisations from responding quickly is the presence of a number of diverse systems connecting various vantage points where data is collected or transformed and the lack of integration between multiple systems and touchpoints through which data flows. It is imperative to build 24/7 connectedness with all internal and external stakeholders including transportation and warehouse operators through tightly coupled automated systems that provide real time insights for decisions concerning movement of raw material and finished goods to the locations of demand. Dynamic insights drawn from customer analytics need to be superimposed to arrive at viable plans for production planning and distribution.
In India with many of the companies manufacturing consumer goods having scattered factories in multiple locations, hundreds of distributors and thousands of retailers, planning and forecasting are even more complex. Real time flexibility has become extremely important to cut down inventory carrying costs, demurrage or avoid overstocking and rerouting products from original destinations to new destinations. Thus businesses have been able to see a direct correlation of investment in supply chain analytics with the reduction in working capital and the growth in business as supply chain has become their lifeline in these complex times.
The writer is chairperson, Global Talent Track, a corporate training solutions company