Are these seven deadly sins plaguing your supply chain in India?

The emergence of new digital and analytic capabilities, combined with significant policy changes and rising customer expectations, mean companies in India need to upgrade their supply-chain processes. Here are seven outdated, but all too common, practices that companies need to watch out for — and change.

Having your planning team forecast demand. With the advent of machine learning and neural networks, having demand-planning teams churn out numbers based on statistical models is not good enough. The best forecasts are now created from advanced analytics engines that crawl the web for digital signals, take into consideration crowd-sourced data, and can explore correlations with more than 2,000 data sets to estimate future demand. Leveraging such data can improve forecasts as much as 10 per cent to 20 per cent. 

Running a monthly sales and operations planning (S&OP) process. In today’s dynamic markets, meeting once a month is not nearly enough: If a particular assumption changes, chaos can set in. Leading companies have instead moved towards a circular planning loop. That means setting up a central team to track and coordinate events — the same way a control tower manages flights. This team gets live feedback of events, such as supply disruptions, and then reacts in real time. Setting this up is not easy, but companies that do it well have seen improvements in service levels consistently.

Relying on a hub-and-spoke network. With the advent of India’s goods-and-services tax (GST), most companies re-examined their network model and perhaps closed a few depots. That is not enough. This policy change was the once-in-a-blue-moon opportunity for all departments (from sales to manufacturing) to come together and reconsider their entire supply-chain strategy. GST implementation presented the opportunity for Indian companies to finally innovate their distribution network and create segmented supply chains for different product groups that have different demand and supply patterns. This meant not each product needed to be stored at each hub and connected depot or ‘spoke’ — and multiple handlings and inventory pile ups can now be avoided with networks tailored for each category.

Treating domestic trucking as a per kilometer variable cost. Historically, due to the fragmented and unorganised nature of the market, most Indian companies have not looked at trucking strategically. They have outsourced it to third-party vendors and treated this as a variable cost based primarily on the distance travelled between plant and depots/warehouses and capacity of the truck. The better approach is to treat trucking more like machinery — that is, to see trucks as a fixed cost that need to be used intensively. This concept has been demonstrated by e-commerce players in India who run trucks close to 15,000 to 18,000 kilometers per month, two to three times as much as other sectors. This “sweating the asset” mindset shift could lower transportation costs by 10 percent to 15 per cent. The key to do this is a robust digitally enabled tracking of the loading, unloading and transit times through a 24/7 control room coupled with a well-coordinated dispatch and receipt planning analytical engine. 

Staffing supply-chain teams with domain experts alone. Supply-chain teams typically have centered around experts who understood specialties such as warehousing, logistics, or planning. Now best practice is to blend supply-chain practitioners with analytics experts, such as data scientists, in order to leverage the data generated through every transaction and uncover inefficiencies across inventory, service and cost in different nodes of the supply chain — for example, by analysing the usage of last mile trucks and creating a dynamic routing algorithm , a company was able to realise a forty per cent drop in last mile costs. 

Procuring off-the-shelf digital solutions and tools without clear business rationale. Many companies that embark on massive and all-encompassing supply-chain digitisation programmes have struggled to define and eventually realise the return on investment of such efforts. Companies that have done well have picked specific use cases that can be cracked by digital and analytics such as the ones we have discussed above example, better demand forecasting, end-to-end closed loop planning, with impact that is linked clearly to a business objective such as improvement in cost by 10 per cent, or maybe, service levels increasing by 15 per cent. 

Treating your suppliers as vendors and not as partners in an eco-system. At times, it is more pragmatic to partner with a start-up to build a routing algorithm for your trucks, for example, rather than trying to code it internally. Companies that are able to build an eco-system of partners across the supply chain have usually seen benefits, such as getting to market faster, cutting development costs, or just having access to talent and expertise. To do this, companies need to move away from traditional vendor management processes of having annual contracts, standard ‘request for quote’ (RFQ) processes and quarterly performance reviews toward an ‘eco-system management’ of a set of partners across the supply chain that feel joint ownership to improve your efficiencies. Examples include joint investments with reputed transporters to ensure dedicated capacity in customised trucks that will improve costs, taking a stake in a logistics start-up to co-develop business solutions relevant to you or even collaborating to create an open platform that facilitates all partners in the eco-system to thrive and build on each other’s efficiencies and scale.

Indian companies need to see their supply chains are sources of value—and then take action to unlock that value. To do so requires them to innovate rapidly, and eliminate traditional, but stale practices. 
The author is a partner of McKinsey & Company



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