Digital integration

Digital integration (DI) can be used in manual, mechanical and automated facilities. Vendors of DI systems say that it can take six weeks to a year to implement. Timing depends entirely upon the technology and data systems already in place. A robust system requires at least 1,200 data points from multiple systems. Even a million-dollar business can remove a week per month of data entry, freeing up limited staff time for higher value work.

Recent DI projects in the food industry suggest that a DI system may help a lean team find another 6–20% more savings than was possible without the system. This is especially important when savings are hard to identify and quantify. An effective DI system relies upon scrubbed data to point to opportunities based on what is measured. Metering systems capture data, people must sort out the useful data so that a DI system produces useful information for analysis. Well-sorted data makes it possible to investigate and measure opportunities and key performance indicators (KPIs). Automatic data capture and sorting eliminates the need for a people to do the data entry. For those who recall the transition from hand-entry ledgers to Lotus (the precursor to Excel) the savings and human error reductions linked to manual entry is the same.

Integrating systems

Activity-based costing, product recall, Energy Management Information Systems (EMIS), inventory, shipping, finance systems, quality assurance (QA), payroll and Enterprise Resource Planning (ERP) are all systems that can be integrated. The integration of these systems makes it possible to develop KPIs that target synergy between business functions such as sales, finance, accounts receivable, purchasing, warehousing, human resources, production and maintenance.

Field observation

A lesson learned from advanced manufacturing is that bar codes and hand-held scanners automate record keeping on the production floor and in the warehouse. The key is to identify the touchpoints where records are generated by one click of a hand-held device or sensor instead of multiple keystrokes and a physical paper trail.

Digital integration vendors

There are many DI vendors operating in Canada. They range from Siemens to smaller domestic companies such as JoinCaddy and Canvas Analytics. All three work with the food processing sector. Be advised that it takes six weeks to a year to undertake a DI project. The time it takes depends entirely upon having the data resources to integrate. Metering, inventory tracking, shop floor production, human resources, QA and procurement systems all matter. Automation and digitized metrics from input to process to output provide the data points required to feed a DI system. It will take time to scrub and analyze what is important for the measurement reporting you wish to see.

Digital twinning

Digital twinning is possible with DI. A digital twin of your facility allows your maintenance, engineering and operational managers to identify maintenance priorities in real time to model improvements and upgrades comparing new equipment specifications to existing equipment. This prognostic tool eliminates weeks of analysis and calculations required to stay on top of maintenance or to assess replacement equipment. It also supports the data analysis for calculating greenhouse gas (GHG) impacts of equipment, processing lines, inputs and outputs.

One of the actions suggested earlier in the guide is to use McMaster’s School of Engineering Practice and Technology to make a digital map of your facility. Not only does a McMaster study provide the foundation for a digital twinning tool, the engineering students who work on your digital mapping project could help with your DI, digital twinning and KPI upgrades.

Another suggested action is to investigate the Energy and Power Innovation Centre (EPIC) at Mohawk College. EPIC provides a wide range of energy adoption services to small and medium-sized enterprises (SMEs). It is a resource for manufacturing and agri-food sector companies who would like to adopt energy technologies that can reduce operating costs throughout their manufacturing processes and/or de-risk the adoption of new technologies. Mohawk College students also work on McMaster’s digital mapping teams.

Operational and environmental key performance indicators

A DI project is the time to update operational KPIs. Effective KPIs reflect the progressive contributions of teams, reflecting positive communication and teamwork between departments and production units.

At the business level, KPIs should reflect integrated performance. Managing performance through a manufacturing facility contributes to overall efficiency. It is important to focus on operational KPIs where performance management is the goal.

Operational KPIs link benefits from productivity and efficiency business functions. Some operational KPIs can be public, such as on-time performance, workforce retention and workplace safety. These three KPIs support social licence with customers, community and the workforce. The others are more sensitive, but critical to making your day-to-day and longer-term decisions.

Environmental KPIs are also social license KPIs. How efficiently you use utilities, how much waste you reduce and how effectively you convert energy and ingredients into consumables speaks to lower carbon manufacturing. Where these inputs are reliably measured and available as data, a DI system can make the various calculations of these KPIs very simple. For example, inputs can be measured as:

  • cost per package, per kilogram of finished goods and per dollar of revenue
  • volume of input per package, per kilogram of finished goods and per dollar of revenue
  • direct carbon-equivalent weight per package, per kg, per dollar of revenue and per year

Field observation

Social license refers to the acceptance of a community to a company or organization. The term is used to describe the corporate social responsibility of a corporation based upon legitimacy (playing by the rules, credibility (providing clear and true information to consumers and regulators)) and trust of consumers.

Examples of effective key performance indicators

Gross margin

Gross margin (GM) is a measurement of the difference between the cost of goods and the selling price. This is done at the individual product level, production line level and overall business level. GM will vary between products.

Sales channels (retail, direct-to-consumer, food service and industrial may all have different GMs based on selling price and the weight of marketing costs. Direct-to-consumer has high order fulfilment costs and retail has high marketing costs. A low GM (below 32%) will stress cashflow and profits. Food service and industrial products tend to have a lower cost of sales and are priced accordingly, where a lower GM of 25–32% may correspond to a similar profit level to retail sales on products with a GM of 40%. Products that are bought, cross-docked or inventoried and sold may only require a 20% GM. Finished goods that consumers pay for before receivables are due may be very profitable with a 10% GM.

The total output from a facility must be weighted by product type and sales channel. The combination of takt time analysis, activity-based costing, EMIS and product costing models undertaken in the input stage and the process stage provide the granular baseline data for this KPI. DI can then be designed to compare the baseline to actual performance.

The following KPIs benefit from the completion of output actions.

Overall equipment effectiveness

Overall equipment effectiveness (OEE) is a measure of the potential capacity of a facility’s equipment versus actual performance. This can be measured at both the production line (this can include facility functions such as found in shipping, receiving and warehousing) and overall facility performance. OEE indicates how fully a business function is being used.  

OEE is a general indicator of operational performance. DI makes tracking the impact of power quality (PQ) improvements and ERP easier. Between PQ and ERP, some food processors have seen a 6% (or higher) improvement to OEE. A rule of thumb developed by Brad Zarnett who founded the Toronto Sustainability Speaker Series suggests that a 1% increase of OEE on $1 million worth of product contributes $25,000 to $35,000 in additional GM. This calculation can be used to correct overhead absorption rates for processing lines, validate capacity for new business and validate LLOYD Factor corrections.

On-time performance

On-time performance is the measurement of order fulfillment to scheduled shipping date. This is different than and may impact on-time delivery which when failed may result in lost sales, late or short order delivery penalties. Excessive overtime may also be an indicator that the shop floor has problems achieving scheduled production. Emergency orders, changes in orders, inventory problems and unscheduled downtime all contribute to failing to meet on-time performance.

Cost variance control associated with on-time performance includes:

  • elevated spot shipping rates for “emergency” ingredient or packaging shipments
  • demurrage costs for carriers who must wait to load or miss traffic windows that result in late delivery charges and penalties
  • unscheduled overtime, which also increases overall utility use and may trigger an additional sanitation cycle
  • unplanned downtime from equipment failures linked to PQ issues
  • lengthened cash-to-cash cycles absorbing operating lines of credit preventing the cashflow required for new business (for every $10,000 tied up in slowed receivables over the course of a year, you will likely have to pass on $15,000 in new sales when credit lines are tight)

Cash-to-cash cycles

Cash-to-cash cycles measure the velocity of money from the time a purchase for inputs is made until a customer pays for goods. This KPI involves:

  • the terms, conditions and on-time receipt of purchases by procurement
  • the ability of QA to ensure ingredients and packaging meet product specifications
  • the ability of maintenance to avoid unscheduled downtime with pro-active maintenance
  • the ability of operations to process within the narrowest practical window
  • the terms and conditions achieved by sales
  • the velocity of customer payment achieved by accounts receivable
  • the ability of finance to measure this KPI work with the team

The operational portion of a cash-to-cash cycle should not be overlooked. From procurement to receiving, to the shop floor to warehousing and to shipping, the velocity of product flow defines an operating line of credit for making goods to sell. This is different than the line of credit required to finance your customers’ payment behavior. In an industry where retail customers require 90-day and 120-day terms, the cost of borrowing for an operating line can be a concern.

A manufacturer who can reduce the operations side of the cash-to-cash cycle equation by 5% or 10% will cover their cost of extending credit to retail customers an extra 30 days. Sometimes this is the cost of business. Where operational efficiency improves on a 30-day cash-to-cash cycle, that 5–10% provides flexibility to build an operating buffer, free up cashflow for minor capital improvements or make and sell more product.

Worker safety

Worker safety is important as a KPI because:

  • the Workplace Safety and Insurance Board’s rate structure rewards safe workplaces, and lower premiums translate into a lower cost of labour
  • no business owner, human resources manager or plant manager needs the stress of a Ministry of Labour, Immigration, Training and Skills Development investigation or the heightened inspection associated with a serious workplace accident
  • unsafe working conditions can increase turnover
  • most workers see a safe work environment as an incentive to keep the job
  • it engenders trust, or social license, in the community and for sales

A growing number of retail and food service chains expect their branded and private label suppliers to check many boxes to earn a listing. Your manufacturing safety record is one of those boxes where a well-designed KPI is as transparent for human resources, retention and recruiting as it is from the plant floor to sales.

QA

Key measures to QA include:

  • the volume and value of rejected inputs. This should also include the cost of performing QA analysis and the costs associated with rejecting and returning goods. This is an opportunity to work with procurement on purchase specifications.
  • the volume, value and percentage of finished goods rejected for sale prior to being released for sale. This is an opportunity to work with maintenance, sanitation, shipping, receiving and operations on fixing practices and or equipment that cause product failures. This KPI should also address the time lost to production for fixes, potential revenue lost for lost sales and idled facility/labour time.
  • traceability tracking time. DI improves the transparency and speed of a recall exercise from inputs to outputs. What takes three or four people two weeks to do manually can be done in minutes with a digitally integrated traceability system.

The reason why the costs related to recalls and rejections is crucial is not to deter QA from making a food safety recall. Rather, understanding the frequency and cost of QA events should be included in product costing model calculations and drive preventative, corrective measures that have capital and training implications.

Field observation

QA is a critical part of procurement and manufacturing. Product specifications often include QA sample sizes. It is important that QA has the lead time and resources to test products based on the sample size identified in purchase contracts. A change in sample size invariably changes the statistical results of any test. For instance, size variation in a 200-g lot of material will be statistically different than size variation in a 1-kg lot. The probability of finding undesirable variance in 1,000 samples is higher than finding undesirable variance in one sample. It is always possible to find a problem when one knows how to look for it. However, a QA hold on ingredients based upon tests that do not affect food safety and are outside of testing specifications identified in procurement contracts will lead to production losses that are unsustainable. It takes constructive, cross-functional communication to ensure that QA, procurement and production works as a team.

Product condemnation, recalls and food safety events all occur. Tragic food safety events bankrupt small businesses. Due diligence is proactive, transparent and the legal responsibility of business owners and executives. Simply put, when the resulting cost of QA intervention is a financial burden, your procurement, processing and handling processes may require improvement. The goal of an effective KPI is to help your business, management and staff avoid the critical failures that trigger QA issues as you improve productivity.

QA KPIs that track the related and chained costs of QA-mandated production interruptions, re-work and disposal (the effects) are an important payback consideration for new investments. This type of KPI documents when and where critical failures occur. As these failures are tracked, they can be used to validate costs by a third party ( as may occur in an insurance claim) to the cause.

Similarly, when the chained costs of QA actions persist, it is a direct indication that the cause of a QA issue requires serious investigation.

Employee retention

Employee retention can be a leading indicator of productivity and efficiency. New hires take time to get up to speed. Labour churn can hinder productivity. Consider the cost of training time (or additional supervision time required for new hires) and the cost variance on production when labour churn is an issue. While these may be marginal costs, supervisors and lead hands who spend time training new staff may not have time to do their own jobs. The cost of high labour turnover is often overlooked in automation proposals.

Alternatively, retention, which suggests reliable performance, is a selling feature to potential customers.

Input efficiency

Input efficiency is a measure of the conversion of ingredients, energy and water into salable products. This includes the measurement of:

  • electricity use (by kW and cost)
  • natural gas and other fuels (propane, diesel, gasoline) by volume and cost
  • water use (by cubic meter and cost)
  • wastewater discharge (by cubic meter, cost and sewer surcharge volume and cost)
  • organic waste (by volume and cost of disposal), which should be separated as:
    • pallets
    • waste packaging
    • organic processing waste
    • cafeteria and office waste

Included in this calculation is the replacement cost of the organic wastes that are generated. For instance, 100 discarded broken pallets may have a replacement cost of $27 per pallet. This should be included in the KPI cost calculation. Similarly, the replacement cost of damaged packaging and the average input cost of ingredients by weight needs to be identified as a cost of waste in addition to disposal costs.

This KPI is a measure of the cost of inputs and waste relative to the sales value of finished goods. These have carbon-equivalent coefficients that represent around three quarters of the carbon emissions from a food processing facility. There are coefficients that can be used to calculate the carbon impact of use. The following coefficients will provide some direction and may change over time. Actual coefficients used to calculate lifecycle and carbon offset credits may differ.

Coefficients for converting materials and inputs into carbon dioxide-equivalent (CO2-e) units include:

  • organic waste: 0.84 kg/kg of solid waste (this can also be used to calculate the potential impact of organic solids in wastewater where 10,000 PPM = 1 kg/m3)
  • water: 0.68 kW/m3 × 30 g/kW (based on Maas, 2012 and IESO carbon intensity of electricity, 2020)
  • wastewater: 0.1 kW × 30 g/kW (based on Maas, 2012 and IESO carbon intensity of electricity, 2020)
  • electricity: 30 g/kW (IESO, 2019. This is a weighted average of electricity CO2-e use based on time of use that reflects peak and shoulder use, not off-peak use. The average CO2-e of electricity in Ontario was 19 g/kW. Actual CO2-e for individual facilities should address time of use.)
  • natural gas: 2.2 kg/m3 (Natural Resource Canada. Coefficients for other fuels can be found on the NRCan website.)