By Steve Burton
According to a recent McKinsey report, about 80 per cent of startups that successfully launch products fail to see them through to full scale-up. “For many startups,” its report elaborates, “the challenge is no longer about securing capital—it’s about learning how to restructure themselves as fast as their products or organizations can evolve.”
Scaling up sustainably depends on your ability to make data-informed decisions. Quantity is not the same as quality; understanding big data’s strategic impact and management tactics for food businesses is integral to implementing analytics into operations. The ability to focus on what matters most for your success is key.
What are KPIs? Finding the right metrics for profitability
Metrics, or more specifically, Key Performance Indicators (KPIs) are well-defined measurements that help you monitor, analyze, and optimize operations. The challenge is that there is no one-size-fits-all solution. Food and beverage processors, especially, have unique needs compared to other manufacturing sectors; KPIs are not just metrics for financial success in the food business, they are also necessary for regulatory compliance (for food safety and traceability) and GFSI certifications demanded by customers.
The shift in industry standards towards big data is driving the adoption of automation technologies that can manage data and generate actionable insights. Real-time metrics and dashboards enable data-informed decisions that improve sales and profitability. The same McKinsey report found that 49 per cent of high-performing consumer companies had “completely integrated digital into their operating model for key areas, nearly twice the number of low performers that have. The key differentiator of high-performing companies is that digital activities are embedded in functions and geographies and not siloed in an IT organization.”
A data-driven approach focused on key metrics will allow you to make better decisions for your business. So, what are some of the metrics that you should be monitoring?
1: Know your optimal fulfillment rate
One essential metric that all manufacturers need to track is Fulfillment Rate (or order fill rate) – the percentage of shipments you can send to customers compared to their orders. For example, your customer orders 100 units and you ship all 100, then your fulfillment rate is 100 per cent. If you stockout and deliver 80 units, your fulfillment rate drops to 80 per cent.
Essentially, this metric reflects your ability to meet customer demand. At first glance, you might think that you should aim for 100 per cent. While some companies do achieve rates as high as 99 per cent, there is a good reason that the average is about 80 to 90 per cent. A very high fulfillment rate indicates that you’re storing excess inventory, which eats into your operating profit margins because inventory and storage costs money. Any waste due to expired products flushes profits down the toilet.
On the other hand, a lower fulfillment rate indicates that demand is outpacing your supply. That gap, which is really a crack in your market that makes you vulnerable to competitors, signals an opportunity to capitalize on customer interest. In the US food retail industry alone, lost sales due to out of stock or unsaleable items are valued at $15-20 billion every year. Finding the right balance is specific to every industry, sector, and even business.
Calculating your fulfillment rate is not as simple as logging customer orders and comparing them to shipments. When sales processes an order, they need insight into available inventory (what is in stock or already allocated to other customers) and planned production in order to assess whether or not orders can be filled. In the food industry, manufacturers need to consider additional factors such as shelf life, supplier lead times, and the length of the production processes. Logistics needs to be factored in, too. Unexpected weather events might prevent a delivery, or a customer might reject a short shipment. You need to capture end results accurately and compare them to the original order.
For food manufacturers, calculating fulfillment rates requires real-time data from across your organization. Access to real-time data allows you to communicate and set customer expectations, anticipate problems, and identify real strategies to improve profitability.
Ultimately, this metric maximizes order value – and so does the next one: cost per unit.
2: Leverage actual costing data in real-time
High-margin products are the bread and butter of any successful operation. Can you pull data on unit costs for all your products right now and assess their profit margins? If you could, you will find that some products make you a lot more money than others. And what if the cost of an ingredient just skyrocketed? Can you reassess profitability immediately to adjust pricing accordingly? How long would it take for you to understand the impact on your bottom line?
The growing pains of scaling up your business requires the agility to react quickly to changes outside of your control. Whether there’s a supply chain disruption or a market opportunity, you need real-time visibility into production costs to maximize profitability.
In my experience, the more products a company makes, the lower their margins. Our client with the highest profit margins has only 11 products. Developing one stellar product is tough, let alone trying to optimize dozens or hundreds. Real-time data is invaluable, but analysis can be difficult. With the right KPIs and the right technology, you can pin down this challenging metric to drive your pricing decisions.
Unit cost is calculated with three cost categories (raw materials, labour, and overhead), usually working from “standard” costing models updated periodically by accountants. Even if a more progressive company manages to update standard costing every quarter, that may still lag behind today’s market. It is best to collect actual costing on products at the lot code level, so you need a unified system to connect data from different sources within your organization (especially purchasing, logistics, and production) to gain a complete insight into your costs.
Imagine having the ability to check actual production costs against your models at any time – especially when launching a new product. For small businesses looking to scale, there isn’t much room for error when it comes to product optimization.
3: Optimize your operations with equipment performance metrics
Poor maintenance costs you by lowering profitability and impeding growth. Overall Equipment Effectiveness (OEE) is a collection of metrics manufacturers use to quantify equipment production performance. It can be evaluated at the individual machine or line level. For example, a high-speed production line resulting in 25 per cent discarded or reworked product is a huge problem.
An OEE score is calculated by multiplying machine availability x performance x quality. These can be broken down further:
machine availability = run time v planned production time
performance = (total count/run time)/ideal run rate
quality = good count v units started.
OEE for world-class manufacturers is 85 per cent, whereas most manufacturers score between 40-60 per cent. The challenge is capturing the data you need to make improvements. Newer devices have IoT capabilities that allow them to connect to other devices and receive/transmit data. This allows you to collect data automatically for real-time visibility. A constant stream of real-time data allows you to gauge equipment performance against nominal functioning so you can catch problems early.
With your information all in one place, you can track downtime and trend data to monitor improvement – and leverage maintenance management tools to transform your KPI insights into operational efficiencies.
Smart growth requires metrics, insights, and action
Scaling up with healthy profit margins relies upon access to strategic information and smart data: not just lifeless numbers, but living, real-time context that you can access and use to make excellent business decisions. A low fulfillment rate could signal a problem with equipment maintenance causing production downtime. This could indicate the need to invest in higher capacity equipment or to adjust your maintenance schedule.
Well-defined metrics transformed into insights can be transformed into real action. The next question is, how can you use these data-driven metrics to accomplish your goals?
About Steven Burton
Founder and CEO of Icicle Technologies Inc., Steven Burton is the architect of the award-winning food production management system, Icicle ERP. Through the development of advanced food safety technology based on over a decade of sophisticated software development expertise, Burton has taken Icicle beyond document management and food safety to offer a complete solution for smart automation, improving quality standards, production efficiency, and expanding growth opportunities for all types of food businesses. This article is adapted from Steve’s webinar presentation “Maximizing Margins for Food Production,” hosted by BC Food & Beverage in October 2022.