The FMCG/CPG industry has been around for a long time. But times are now changing, the traditional way of distribution planning, which relies entirely on human intelligence, is no longer good enough to cater to the ever increasing demand. This results in delivery inefficiencies and increasing costs. Many firms also lack ground level data on sales, sales executive performance, SKUs, etc. These data points can potentially help companies strategize on-ground sales better and also in deciding potential locations for warehouses, manufacturing plants, and hubs.
Human dependency: A lot of FMCG companies depend on human resources to plan the distribution. This plan does not consider on-ground situations and leads to delayed deliveries, higher costs and a lack of efficiency.
Lack of on-ground insights: Since the planning is manual, the execution is left entirely to the on-ground personnel. Right from the performance of the sales executives, various SKUs to delivery of goods, there is a lack of data. This ultimately results in strategies based on tribal knowledge rather than data-based insights. Since FMCG companies are so huge, on-ground data and insights from sales personnel rarely reaches the top management.
Lack of new-age technology: The traditional intuition-based way of functioning is ingrained in the system. With changing times, FMCG firms are now tying up closely with E-commerce and Modern Trade Retail firms who are more tech savvy. FMCG firms are now transitioning to a more tech-based supply chain management.
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One of the largest frozen desserts manufacturers in India reached out to Locus Consulting to optimize various legs of its supply chain.
Locus helped the company improve the efficiency of its refrigerated logistics deliveries, reduce operational costs and shift from a traditional ad-hoc distribution planning to a scheduled one. Locus’ deep-dive network analysis resulted in the company figuring out the ideal location of its new cold store and manufacturing unit.
The customer reduced human dependency in the planning process of distribution using Locus’ solutions. This resulted in reduced number of vehicles required and cut costs, while increasing in-full deliveries.
Locus also helped the customer with a sales heat map, SKU performance tool, and performance-based scorecard. Overall, the customer saw improvement across all legs of the supply chain.
Locus DispatchIQ: The algorithmic route planning and optimization software, generates optimized routes using Artificial Intelligence (AI), thereby enabling the riders to deliver more with less time. This results in increased vehicle efficiency and better compliance.
NetOpt: NetOpt is Locus’ proprietary machine learning-based algorithm, that replicates a company’s end-to-end supply chain from bottom-up and creates a digital twin. This digital twin is then used to analyze, tweak, and optimize the network of a given supply chain for location intelligence, optimized inventory holding costs and value chain flow of the product.
Grading SKUs: An interactive visual tool, which can help gauge the performance of SKUs.
Sales Heat Map: Locus’ heat map helped identify best-performing districts and laggards in the target area and sorted the districts into: Immediate Focus, Secondary Focus, Neutral Potential, Low Focus, and Best performer districts.
Interactive Dashboard for Admin control: This tool gives better visibility of the ground resources and their performance.
FMCG
Rank sales executives on experience, skills, and preference, among other parameters
Ensures more time spent in-store than on the road, thereby leading to increased sales
Control Tower Application - Take into account outlet level constraints, product category, sales, historical data to ensure lower mirror beats, and right mapping of outlet to sales executive
On-ground realities like traffic, outlet timings are taken into account to plan daily dynamic route planning
Suggest optimal vehicle mix to ensure on-time delivery and also save costs
Reduce dispatch planning time and also accommodate on-demand requests in real time
CASE STUDY
CASE STUDY
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