7 things to ask yourself about supply chain planning

We’ve compiled a list of seven questions to help you evaluate your current supply chain situation and to determine if there is anything you should look out for. If you find any of these to be all too familiar, you might have to put aside some time in your calendar to review your supply chain planning.

How does your organization optimize the supply source on an order level? Do you always select the most used route or just trust the planner’s instincts? In many companies, unit processes are well optimized, but there is an enormous unused potential for optimizing the supply source.

If you have multiple factories or logistic resources to choose from, you have different supply routing options. Selecting the cheapest route requires knowledge about routing master data, production capacity and inventory levels, and summarized costs for each option. Once this data connects to the planning tool optimization capabilities, you can reduce the cost of each delivery. This type of optimization can also reduce emissions by promoting local deliveries, help utilize stocks in smart ways, and benefit from the currency changes and taxation rules.

However, minimizing costs should not harm profitability. In the long run, customer experience is the safest way to guarantee profitability. For this reason, it is a widely used strategy to always deliver on time even if doing so requires more expensive supply options. However, select the more costly supply option only if the alternative would be a late delivery. To have high on-time delivery rates, you need to have a plan that takes into consideration lead times and capacity restrictions. This should result in a method that the supply organization can reliably execute.

Physical supply chain capabilities may set limitations on rush orders or last-minute changes in production. However, in many cases, it is not the physical that limits your capability to react. The difference between delivery and disappointment is how agile your supply chain is in handling different kinds of orders. Typically, operational boundaries are already set by the time an order is accepted or a production sequence is changed when receiving non-standard orders.

The question is: why do these last-minute changes remain incomplete? Because it takes too much time and work to recalculate everything when these changes occur. So, in these scenarios, time really is money. Every order missed, due to insufficient time, could potentially be delivered by increasing your service level and reducing safety stocks through advanced planning and simulations.

Let’s say you have to calculate whether you can meet demand. You must take into account: how much stock you should have, how much you can supply, and what is your actual capability to respond to orders with your present manufacturing and logistic resources. When doing this, is your first instinct to take the averages of previous orders and play around with them in a spreadsheet like MS Excel?

If the answer is yes, then you are dealing with a “black box”. You put something in and something else comes out, but you have no idea if it is based on the right numbers. Meaning, once you have your plan, based on the averages, you can’t be sure if it will precisely match the orders. So, what then? You’ll probably have to add some slack to be safe, maybe some extra days because of the unknowns, until you’re adding a little bit of extra on everything: lead times, wait times, quantities, delivery time, safety stocks, and so on so you don’t disappoint a customer if a problem arises. Needless to say, that will weigh down any supply chain.

Do you have to manually input production results or sales changes? If you are keying in values instead of getting them automatically from real-time data, your information is probably already outdated by the time you type it in. The level of detail you receive is also too coarse to get a picture of what is actually happening. Consequently, the quality of reporting and communications with stakeholders suffers as a result. You also can’t fix problems if you don’t have the time to respond to them and most dire of all, if you do not even know they exist.

A proper supply chain planning system receives information from many sources, slashing across the silos – from salespeople to factory production. What are the sales figures? What orders are in? What are you producing at the moment? This data should be readily available and everything should flow to a forecasting system that can correctly predict what tomorrow’s situation will be in real-time.

There are things that are impossible to prepare for. However, these should be exceptions rather than a typical day at the office. Your organization already has the knowledge to see into the future. You just need the right tools. Harness the knowledge provided by sales orders for forecasts. Your manufacturing, logistics, and purchasing departments can likewise provide information on resource availability.

The next step is to create simulations of how your supply chain responds to different situations and scenarios. What if you get a huge order that needs to be completed in a few weeks? What if a client goes bankrupt? Using scenarios, you can resolve problems before they occur and not get caught unprepared. This approach is a game changer, not only for supply chain management but also for the whole dynamic of your enterprise’s business model.

If a single person is in control of your entire SCP, you are putting all of your eggs in one risky basket, and forcing that person to overcome major challenges day after day. There are three things to start with in order to reduce personal dependencies and to improve planning processes.

1. Establish a planning process by forming a communication link between sales and production scheduling.
2. Establish your numbers in terms of financial and scheduling evaluation metrics – and simulate, visualize, and evaluate them.
3. Respect you enterprise strategy. Cooperatively establish business rules for what you are trying to achieve with your supply chain optimization, so that everyone is on the same page.

If you are producing to stock, then you need to understand how much is needed in addition to what has already been ordered from you. The best information available to prepare for the future is the forecast. Forecasts are imperfect but they are based on something much stronger than a gut feeling – your salespeople’s tacit knowledge. Your salespeople hold a vast amount of hidden information on what orders the future holds based on the real situations customers and consumers are in.

Your success largely depends on what occurs outside your company’s walls. However, sales forecasts are often not taken as seriously as they should be, because they are based on people’s assumptions instead of historical data. A sales forecast might even be in a completely separate process than the production pipeline, which adds to inaccuracy and complexity. Using last year’s sales as forecasts is like using last year’s weather to know if it is going to rain today. It is indicative but not exact. With the right simulation and optimization tools you can use all of the forecast’s data to ensure that your supply will meet demand as precisely as possible.

This is a typical SCP structure consisting of parallel and/or successive chains. The supply chain is an abstract expression of physical processes. In supply chain planning, which is based on finite capacity, you have to model and optimize everything from warehouses and logistics to production and the purchase of raw materials.

This white paper goes through several obstacles and deficiencies one might have in their supply chain planning process. If you recognize your company in these listed points, a good place to start is to evaluate what the strategic goals of your supply chain are, and to go through this simple checklist:

• What are your business objectives regarding your supply chain?
• What would your ideal supply chain planning (SCP) process be like?
• How would your SCP handle the issues you are facing?
• What do your present SCP systems consist of?