The Coronavirus disease (COVID-19) pandemic has surfaced and accentuated ongoing supply chain problems. It is forcing companies to recognize their logistical shortcomings and ongoing challenges with reactive problem solving and limited data visibility. It has underscored the need for supply chains to perform dynamic risk management, while opting for technology advances such as use of artificial intelligence (AI) and adoption of machine learning (ML) solutions along with automation to streamline their processes, bring agility within the organization and run their businesses profitably.
For businesses, COVID-19 is known as a “great accelerator” for good reason. It has pushed forward trends and related changes to address these business issues into compressed timeframes, from years to months. For supply chain managers, it creates a time window to take a beat and uncover recommended improvements, explore the latest tech and create strategies to make impactful change for 2021 and beyond.
Making this happen at scale and speed means managers need to prioritize their time, investments and strategies for the next year.
1. Automate at scale.
Handling a supply chain at scale means adding automation to offload some manual tasks and get more out of every process and worker. However, implementing automation the right way requires strategic thinking beyond just throwing in robotic process automation. You need to make informed decisions to put automation to work.
After the pandemic began, firms with automated processes were better suited to the shifts in consumer behaviors and buying patterns. Scaling technology and automation tools is simpler than adding people, and it is simply easier to handle a crisis when you have already built a solid automated foundation. By adding automated tools in the winter of 2020 and early 2021, that are informed by process and operational intelligence, supply chain managers can prime their companies to take advantage of the expected economic rebounds in the summer.
Making the move to deploy intelligence-infused automation across the enterprise provides managers with context-rich reporting for executive leadership so they can work together to manage revenue risks. It adds agility to the supply chain and helps it navigate future threats.
2. Dynamic risk and response management.
A first step for supply chain managers is to spot value leaks. Identify these problems and then take some swift corrective steps. Consider your current operations. Are back orders, missed orders or orders cancelled due to poor service levels, causing you to bleed sales and spoil the customer experience? Is the warehouse stocking inventory at levels that sits for too long, could expire or become obsolete, and therefore adversely impacting the financials? Are items coming to the warehouse late and you are risking significant margin loss due to increased freight or expedited shipping? If you are always in a reactive mode, how do you anticipate and address risks proactively?
What do these questions have in common? On one hand you need live data feeds, on the other hand you need an ability to identify risks rapidly and make decisions for best outcome.
Armed with live data, managers have context to make informed decisions. They are not constrained by outdated information or stored logs, or wasting time running reports to review historical data to see any correlations to current issues. Technology like electronic logging devices and cloud-residing applications can offer real-time shipment monitoring. When this information is matched with data about external conditions, then it is much easier to spot and reduce operational leaks and risks to revenue, margin and profitability attainment. You can change a reactive response dynamically into proactive management, with faster response times and better outcomes. Dynamic risk management, using live data and processes, is an essential strategy for 2021 and beyond as it allows you to keep pace with accelerated change, avoid disruptions and strategize the use of different suppliers as needed.
3. Leverage AI and adopt ML
The pent-up demand for consumer goods in 2021 will put pressures on companies to gain competitive advantages. There are only so many pathways to standing out from the competition. For supply chain managers, artificial intelligence and machine learning tools can provide that edge, by bringing previously unseen or unknown insights from information.
Managers need to understand AI’s impacts on supply chains and various aspects of business- how to best incorporate it to add efficiency and context to various solutions. Leveraging real-time information about inventory levels, back-order problems and shipping cost waste is easier and faster when it comes from AI-infused solutions. They need depth and understanding of the business and process context to help apply rules, manage based on alerts and exceptions and make proactive decisions with a predictive outcome versus fighting fires and reacting to market conditions.
Supply chain managers need these technology tools and plans in place to extract, present, and organize all the live business data streams in a way that can be processed and consumed easily while empowering them with actionable insights, not just a shiny new tool.
Putting priorities into action
Adding automation, AI and the ability to work with live data is a significant undertaking, one that requires the right technology and partners. These technologies alone and without an informed way of applying them will not only be an expensive experiment, but also a bigger lost opportunity. A modern operational intelligence system is essential for this transformation. Pick a provider that can handle data from any source, identify risk dynamically and create automated outcomes. Supply chain managers planning ahead into 2021’s unique challenges and opportunities should consider a partner that provides agility and the power of ML. Such a partner can reduce knowledge gaps, by continuously suggesting ways to make processes and systems smarter, helping navigate to superior outcomes.