In a race to fortify their supply chains, leading manufacturers are realizing value from digital transformation beyond the factory floor. Data and analytics, artificial intelligence (AI) and machine learning (ML) offer necessary insights to optimize operations and mitigate risks. However, a large number of companies are stuck with glaring technology and process gaps that need to be addressed before they can truly capture the full potential of Industry 4.0.
Manufacturers say the top hurdles to digital transformation are a lack of expertise (60%), lack of resources (46%), limited budget (43%) and ineffective change management (42%), according to research from LeanDNA. Many rely on enterprise resource planning (ERP) systems and business intelligence tools to gather information, but are missing the piece of the puzzle that unlocks actionable insights.
Here’s an important reminder: Digital transformation isn’t necessarily rebuilding the technology stack from scratch. Rather, it can mean leveraging data and harnessing insights from existing systems and investments. By adding emerging technologies to existing enterprise IT investments, the manufacturing industry will have the tools needed to enable a true digital transformation of the supply chain. To start, companies need to polish their data, prioritize actions, and boost internal and external collaboration.
By aggregating and analyzing data from ERP, MRP and MPS systems, manufacturers can gain visibility across their supply chain and see the potential impact on their factory operations processes from planning to purchasing to manufacturing. Historical data views can also improve how information is leveraged by providing individual buyers with a view of changing demand so they can effectively interpret the context behind exception and action messages and confidently resolve issues, for example. Combining and normalizing data across manufacturing sites that are usually separated by disparate, disconnected systems further unlocks potential remedies to inventory issues.
Despite the current supply chain challenges, leading companies from aerospace to automotive to industrial products have improved on-time delivery for customers globally by digitizing their supply chain infrastructure through advanced analytics. These companies have moved away from outdated spreadsheets and siloed efforts of planners, buyers and suppliers, to modern, cloud-based analytics software that provided insights needed to adjust inventory, improve cross-functional collaboration and increase on-time delivery.
Once data across systems and sites have been amalgamated, basic and advanced analytics can help buyers sift through the unmanageable noise of ERP messages, e-mails and daily emergencies to isolate and prioritize the most impactful insights and actions that will most affect business results. Being able to identify and resolve critical shortages that prevent production from moving forward is key in today’s shortage economy. Similarly, identifying SKUs and component parts that have the highest monetary impact helps procurement teams to prioritize their time. In addition to prioritizing daily actions, the right solution can also help buyers and planners intelligently review and improve order policies and parameters that can lead to bad data and bad actions.
A Collaborative Workflow
Having a single, up-to-date view of how material supply and demand are being managed to optimize working capital and improve on-time customer delivery is key to having teams work efficiently together. Many teams’ daily workflows rely on reacting to old, static data from earlier in the value chain all while operating in their own separate silos. Instead, planning and procurement can work in unison to optimize production, improve cash flow, reduce costs and mitigate risk to on-time delivery. Collaboration is not only necessary internally within manufacturing organizations, but also with suppliers. Another commonly untapped opportunity is increasing visibility and cooperation across manufacturing sites within the same organization. This enables cross-site analytics where shortages and excess inventory can be seen across sites, suppliers and different systems. By doing so, manufacturers can improve alignment, minimize excess inventory and even find creative solutions to problems, like identifying needed parts at their other sites to address shortages for parts with long supplier lead teams or expensive expedite fees.
While today’s supply chain challenges span the globe, they are not new. Innovative strategies and technologies are successfully being leveraged to improve operational execution to ensure you get the right part, to the right place, at the right time. While the short-term journey may be difficult for many companies, these challenging times are driving innovation that will be critical in the years to come.
Richard Lebovitz is founder and CEO of LeanDNA.
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