Sever planning from the spreadsheet

“Spreadsheets are the classic way of planning, but it only takes you so far.” Plex Systems’ Ara Surenian identified the changes needed to fix supply-chain issues moving forward.

Manufacturing execution systems from Plex Systems, a Rockwell Automation company, will have more emphasis on the development of supply-chain solutions, said Ara Surenian, vice president of product management at Plex, who spoke at ROKLive in Orlando, Fla. Current and long-time supply-chain issues are influencing the roadmap for future supply-chain-planning products, he explained.

Plex’s 7^th Annual State of Smart Manufacturing Report was important in helping the company further understand the importance of supply-chain planning, Surenian said. “Modularity is definitely something customers and companies are looking for,” he said. “They’re looking for solutions that address the need when the need arises.” Plex has begun breaking out more modular components for quality management (QM) solutions, application performance management (APM) and supply-chain planning. “The study reinforced that the strategy and approach we’ve taken makes a lot of sense,” Surenian said. Modularity is leading to a higher level of adoption, he added.

According to the report, the three most critical challenges facing manufacturers are the shortage of skilled workers (41%); risk mitigation/cybersecurity (39%); and supply-chain disruption (35%). The issues with supply chain are also compounded, he said. In addition to the pandemic, issues such as the war in Ukraine, as well as port and canal traffic jams, are further influencing supply-chain problems.

The need for a supply-chain solution to help address these issues becomes critical for breaking out of spreadsheet management, Surenian said. “Spreadsheets are the classic way of planning, but it only takes you so far,” he said.

The survey also looked at the current use of supply-chain-planning software solutions. Seventy-eight percent of respondents stated they are using a supply-chain-planning software solution; 70% said that their supply-chain-planning systems still rely on spreadsheets and manual processes; and 38% are actively shopping for improved solutions.

Typically, companies are doing a portion of supply-chain management, such as forecasting, in a software solution, but they then pull that data out and drop it into spreadsheets to do the scheduling, Surenian explained.

“The need for a holistic solution that brings all these pieces together is critically important,” Surenian said. “It’s really about building something that connects end to end from demand to supply and execution.” Plex has started introducing some supply-chain products this year and will continue with additional offerings over the next two years.

To use a holistic solution, Surenian said, demand planning should start with a forecast. “The more accurate the forecast, the better,” he added. That forecast then translates into a master production schedule (MPS). “From there, that plan can be optimized, can be leveled, to utilize paths to more effectively understand that there are constraints that can undermine the ability to meet the sales plan as defined, and then, once that’s reconciled, explore those requirements through the materials to see where there’s potential shortages and then iterate from there,” Surenian said.

With this digital thread, the new Plex supply-chain solution can incorporate input from sales, planning, marketing and finance to identify the working capital objective. “Then that plan flows through and it takes you all the way down to the finite schedule and connects right to the machines. That’s our vision,” Surenian said.

Without accurate demand predictions, inventory and capacity issues will arise. If the supply plan is disconnected from the demand plan, this can lead to material shortages and other constraints. “Connecting all these pieces together is critically important,” Surenian said.

Proper supply-chain planning connects an organization to its customers and suppliers to define the who, what, when, where and how of inventory to best meet the organization sales and service objectives, he explained.

Plex will introduce a number of supply-chain products this year and next year to address many of these issues. In the first quarter of 2022, it released the Constrained Capacity Production Leveling application to provide a closed-loop process from planning to production. Later in the year, Plex will introduce a machine-learning capability to assist customers with expanding their forecasting abilities.

In 2023, Plex plans to release a standalone Finite Scheduling solution, which will expand constrained view plans to a future state. “Finite scheduling looks at multiple optimizations, but it’s more looking at that finished goods level, the point of where you’re producing the goods and understanding whether you have the capacity to meet the demand that your sales team has projected,” he said. “The ability to now get that machine data against those jobs that are earning and look at the actual rates, the actual setup times, completely changes how you look at scheduling. It’s no longer an estimate, but it becomes real.”

Typically, when more uncertainty or disruptions exist, especially with labor shortages, manually scheduling all that is difficult, Surenian said. “Folks are looking for a tool that they can add to whatever enterprise resource planning (ERP) or manufacturing execution system (MES) they have,” he said. “We’re able to drive higher forecast accuracy, which will help establish a much more stable material planning system. We can optimize that schedule based on a constrained schedule, and, in doing so, especially as you bring in finite, have higher levels of much more predictable execution.”

The supply-chain planning application will run two parallel processes—the sales and operation planning (S&OP) or integrated business plan, as well as executing the current planning cycle. Machine learning will greatly improve this process, Surenian said.

The first release of the machine-learning component will collect the sales history of an item by customer and by location. “So, we take that entity and have time-series historical data set off weekly buckets. That data set will then go into the machine learning,” Surenian said. “It’s establishing and trying to understand, based on the sum and aggregation of all this granular item location and customer data, which of those attributes are significant,” he said. For example, in retail, apparel production has many components—color, size, style and seasonal attributes. Machine learning can understand which of these tags are most significant in the modeling. Next, the solution will introduce a call for related data, such as price changes or events, such as the pandemic, sales promotion or any event that might influence demand.

Overall, a 1% improvement in forecast accuracy will lead to a 0.17% increase in revenue and 1 to 2% reduction in inventory. Technology and automation are driving the next generation of manufacturing, Surenian said. “Inventory requires an understanding of who you’re selling to, what you’re selling, how much you’re selling and where you’re going to ship it from,” he added.