Companies solve a customer need or requirement by supplying products or services. This is the basic supply and demand concept. However, going deeper in the supply part of the deal, we see that the customer must receive the product or service at a convenient time and place. Moving goods to distributors, retail outlets, or customer’s houses needs logistics management. There are two aspects to consider here: reducing logistics costs and improving customer satisfaction.
Proposed benefit: Reducing logistics costs
Companies use trailers, trucks, or vans to move their merchandise. These, along with the drivers count as their resources. All these resources carry different costs–primarily time and capacity. Time cost includes salaries, vehicle rent, etc. Capacity cost covers the actual available carrying capacity of each driver (delivery associate) or vehicle.
Movement of goods along primary, secondary, or tertiary legs of distribution involves a collection of these costs. They add to the total freight rates. If the capacity isn’t properly filled–the vehicle has idle capacity or the supply overshoots available capacity and the company has to dip into the spot market to rent extra vehicles–then it would count as a loss or it may push up the freight rates, making the logistics movement inefficient. Similarly, resource time has a direct correlation with the total costs. Moreover, with the regulatory mandates surrounding ‘hours-of-service’ for drivers, time-management for resources has become critical. There is also the consistent shortage of quality drivers which adds to the complexity of the problem.
Schedule and route planning can cut down on these costs. If you have ten trucks, each with approximately 10 tons capacity, putting the total to around 100 tons. You transport furniture parts to distributors across state lines. Your regular replenishment cycles chalk up your total shipping requirements to be around 80 tons. You manually assign drivers and vehicles. But due to some mega-sales event, the distributors now require a total of 110 tons of furniture parts. Now you have to track how many of your vehicles are on the road and how many are free to be loaded. Even then, you have an excess of 10 tons for which you may have to rent another truck.
Tech-enablement: Optimizing vehicle capacity and driver allocation
Field service management technology with logistics tracking features can come to the rescue by optimizing the current capacity using machine-learning enabled algorithms. It would track each of your trucks, their turnaround times, their idle capacity, their in-transit hub points, their loading and unloading time, their possible detention time at hubs or in traffic, and more to suggest the best schedule for all your vehicles to follow. This optimized schedule would also allocate the routes which the drivers are better acquainted with. This would further bring down transit time.
As far as capacity is concerned, the algorithm would optimize it based on the total volume capacity required. Without getting into the nitty-gritty of the core engine, the result would be that you would be able to ship all the 110 tons with the same 10 trucks, managing the timelines and schedules so that across the fleets, optimal capacity is maintained.
Even if the demand requires you to consider extra vehicles, live tracking visibility of all vehicles and drivers would ensure that you no longer have to guess how much extra capacity you need. Add to that the extra time you save on planning so that you don’t have to rent trucks at the last minute at higher rates. It’s not just over-capacity, it would also help you solve under-capacity problems where the algorithm optimizes capacity in a manner that 80 tons are moved by perhaps 7 trucks, saving you the use of 3 trucks/drivers.
The route planning end of the equation would suggest the fastest and safest routes for all your movement so that the fuel and time in-transit cost is minimized.
Optimal capacity and time management helps you to sustain profitability in your operations. It also gives extra edge in the market by keeping the marginal logistics cost on each unit less than competitive standards.
Proposed benefit: Increasing customer satisfaction
Consider that around this mega-sales event, your furniture parts are in quite a lot of demand. Your distributors are stocking up your goods. But they require delivery in preset time slots so as to minimize their own holding and handling costs. It is critical that you deliver in these slots to ensure that subsequent shipments are sent out in a timely manner. You would want to align the schedule and route in such a way that they reach all your hubs at the right time.
Now, suppose you are the distributor or the retailer who wants to speed-up deliveries to the end-customer. With so many mega-sales events in the recent past, customers tend to expect next-day, or in some cases, same-day deliveries.
Route planning along the secondary and tertiary leg of distribution requires heightened last mile delivery management. You may pickup from single or multiple points or drop-off at single or multiple points. The complexity of last mile deliveries increases with increase in the volume of endpoint nodes. The higher the volume of goods moved, the more difficult it is to manually plan last mile deliveries efficiently. Errors or delays at this end directly affect customer satisfaction.
Tech-enablement: Route planning for faster and better deliveries
But manual planning isn’t your only option. Machine learning-driven route planning engines track live traffic, multiple customer (or retail) locations and preferred delivery time-slots, incoming pickup or return requests, delivery associate capacity, their localized knowledge, among other things to devise the perfect schedule and route for on-time deliveries.
Live tracking of resource movement gives you complete visibility of your operations and instant notifications covering every delivery status update and any delay or detention. It adds to the agility of the last mile delivery system bringing down the reaction time in case of any eventuality. Secure delivery validation with instant customer feedback ensures error-free and happy delivery experience.
Technology has the power to not just cut costs but boost business and increase customer retention. This is the way the world is moving and you, with your about-to-boom furniture parts business, should jump on the wagon and zoom to the top.
Dhruvil Sanghvi, CEO and Co-founder of LogiNext, is the youngest tech business head in Forbes India 30 under 30 (2017). He has led LogiNext to international renown for tech-optimized delivery schedule and route planning. LogiNext has been recognized as one of the fastest growing SaaS company for logistics and field workforce optimization.
Before initiating his journey as an entrepreneur, he performed as a consultant to many Fortune 500 companies such as Ernst & Young and Deloitte. He still plays the role of a masterful mentor, honing and guiding young entrepreneurs on their individual journeys.