Supply chain planning is essentially about making decisions in the supply chain.
- How accurate is our forecast for sales; based on this how much we should plan to sell and produce?
- How much materials/components do I need to order from suppliers?
- Is my capacity having a constraint? What trade offs we need to make?
- Where should I put inventory in the supply chain? Nearer to Customer or nearer to supplier?
- What will happen to my customer service if I accept this large order?
- What level of profitability will I generate?
- Do I need to invest in more manufacturing capacity in three years? If so, where?
- Do I need to increase my distribution footprint?
- Will I require more suppliers?
- And many more strategic and tactical decisions are required in order to manage supply chain operations smoothly.
To make these decisions, we require information from various data sources. The issues with data sources are – their latency, accuracy, and granularity. Sometime the data availability is also an issue and we resort to Guesstimate! So, for improving our planning decision accuracy, we need to have timely availability of data, more accurate and granular data, and a robust method of analyzing the data to arrive at decision. This is becoming more and more complicated with Globalization of supply chain, focus on off-shoring, advent of ecommerce and Digital capabilities in entire eco-system.
The starting point often for most organizations is sales and operations planning (S&OP). However, after having this high level of decision making on Demand and Supply plans, when it comes to daily execution level decision there are many misalignments. Consequently, organization focus on S&OP becomes less and it is not seen as adding much value. Over a time, S&OP decision making quality is lowered. So. what is required is a strong alignment between their S&OP decisions and their operational planning decisions that drives sales and operations execution processes (this is called Sales and Operations Execution (S&OE).
Since Execution processes are broken from the overall S&OP plans, the gaps emerge between manufacturing execution priorities and Sales execution priorities. In fact, is becomes literally a daily fire fighting situation for the organization.
Typical symptoms and outcomes of this break in planning process are –
- Late deliveries or expedited deliveries with premium freights
- Higher inventory levels
- Impacts on supplier performance due to Bull whip effect of changing plans.
- Lower productivities of machines and workforce.
- And off course Business performance in terms of Revenue / margin leakages.
The root causes for this misalignment are – data latency, accuracy, and planning algorithm robustness. The solution is to get all the data on a unified platform and build robust algorithm. This is what we call Digital Supply Chain planning. As per Gartner, the definition is ‘The use of digital technologies such as cloud, big data, RPA, AI and/or ML to improve or transform the quality of the planning decision making in the supply chain.’
In next article we will go in depth of Digital Supply Chain Decision model and business benefits.