While raw material often contributes to more than 50 percent of overall production costs in seafood processing, labour likely feels a lot bigger. Why? Because when things go wrong, it packs an emotional punch. Bottlenecks, breakdowns, paperwork, data errors—we personally experience these problems in our daily jobs in seafood processing. It’s feels unproductive and frustrating.
Workflow digitization in processing plants can literally be a painkiller, alleviating a number of these headaches. In some cases, digitization and automation may eliminate an entire job, especially redundant data entry. More often, it saves time, allowing you to focus on more productive tasks that could improve your bottom line. In my view, saving time, especially that of senior managers and executives, may be more valuable than cutting a low-wage data-entry position.
Welcome to our second article in our series on “ROI of Digital Transformation.” In this post, I’ll focus on how digitization can save time and cut labour costs. I’ll focus on three key areas to search for efficiencies—data management, quality control and production—and provide some tangible examples of how you can measure potential savings in your own operations.
Most people would be shocked to learn how much data is being collected in seafood processors. A typical tuna cannery or shrimp processor collects hundreds of pages of data each day. One of our customers records more than a million data entries per year or about 2 gigabytes of data. Thus, enormous effort is expended managing all this data. Look for savings in these six tasks:
- Collecting: Some savings can occur here, especially if data collection can be automated by electronic devices such as temperature gauges, weigh scales, RFIDs and scanners. However, a lot of data is collected manually in seafood processors, which means key punching it into a tablet rather than writing it on paper. The bigger savings comes after data has been initially digitized.
- Communicating: Digitization can streamline communications, eliminating calls, emails, physically movements and redundant data copying. With integrated software, data can be automatically and instantaneously shared with downstream workers or supervisors.
- Reporting: Most managers spend several hours a day compiling production or QC reports, filling out compliance reports, manually updating inventories on Excel or tracking down data from different departments to do cost accounting. Software can automate reporting and artificial intelligence can even check for errors, saving precious time and reducing stress.
- Sharing: At some point, paperwork from production and QC will need to be shared with accounting, customers and auditors. Large companies often have rooms full of data-entry workers manually key-punching data into Excel, ERP software and external reporting platforms. Most modern software is interoperable, allowing for data to be shared seamlessly from app to app.
- Retrieving: Once daily reports are filed away, they’ll inevitably need to be retrieved at some point for mock and actual recalls, audits and customer requests. The older the report the more painful it is to retrieve it from the archive, which can often be offsite. An electronic recall can be down at the speed of clicking a button.
- Labelling: Data often needs to be paired with physical objects—totes, racks, pallets, boxes, packages—to maintain traceability for food safety. This is often done via handwritten labels and tags. Software and printers can automate this task, and even enable more data to be tracked as well.
In lean manufacturing, a continuous improvement methodology pioneered by Toyota, there are two flows in the production process: physical materials and data. Quality control is really about both. Poor control can lead to material defects and defective data that can drive up labour costs. Digital transformation can help avoid labour costs by strengthening control. Here’s how:
- Preventing errors: People make mistakes. To err is human, after all. Messy handwriting. Copying errors. Careless data recording. Digitization often removes humans from the equation and thus prevents errors from happening in the first place. Think of all the paper tally sheets with rows of numbers, such as weights or temperature samples, manually added up or averaged, incorrectly.
- Catching errors: Digital systems can automate error detection and make errors immediately visible on dashboards. The Japanese call this poka-yoke, (ポカヨケ), a term that means “mistake-proofing.” If errors aren’t caught early, they typically generate exponentially higher costs downstream, causing material and labour waste.
- Fixing errors: Errors can happen in digital systems, especially if they aren’t large enough to be detected as statistical outliers. However, it takes much less effort to correct them with software. Fixing the original mistake will automatically update any dependencies in a database. Compare that to tracking an initial error through numerous paper reports.
One of the greatest advantages of digital transformation is the operational and business intelligence that is generated. Huge volumes of data can be analyzed to understand trends and artificial intelligence can predict problems before they happen and optimize processes. Ultimately, it’s about increasing the productivity of workers by preventing breakdowns and bottlenecks.
- Breakdowns: Downtime is costly. The cost of repairing a machine might be marginal compared to the cost of idle workers and lost production. Digitizing and analyzing data such as machine running times, breakdowns and maintenance can enable predictive maintenance that will ultimately save labour costs.
- Bottlenecks: Lean manufacturing focuses a lot on material and information flows and harmonizing cycle time at each step of production to prevent bottlenecks. Especially with fresh fish, raw material often moves faster than information. Waiting for paperwork isn’t uncommon. Digitization avoids this bottleneck by immediately sharing data with downstream workers. And artificial intelligence can analyze vast amounts of production data to optimize planning and thus maximize the productivity of your labour force. If you’ve ever been in a processing plant with workers just standing around, a bottleneck is likely the culprit.
I’ve identified 11 ways that digital transformation can save time and cut labour costs across the organization from idle cutting line workers to CFOs going cross-eyed laboriously manipulating Excel spreadsheets for cost accounting. Paperwork is painful indeed, but digitization is the painkiller. For all these tasks, actual savings will also depend on the local cost of labour, which varies widely from high-cost North America to cheaper Southeast Asian markets. But the emotional benefits of feeling more productive will be the same no matter your location.
Up next in our series is material costs.
Series: Calculating ROI from Digital Transformation
- Labour Costs
- Material Costs
- Compliance Costs
- Revenue Generation
- Non-Financial Value