We are witnessing dramatic changes in the food and restaurant industry creating a new ‘norm’ overnight. Coronavirus confinement means consumers are taking advantage of delivery and takeaway options, and benefiting from the obvious time/cost savings.
We have no idea when restaurants will be opening, but after at least 2-4 months of eating at home, families are already finding that cooking together is not just a safer option, but also fun. With the convenience of delivery, the pleasure of home cooked meals and fears of second wave infection, it will likely take some time before people are eating out again.
Due to these changes the industry will naturally become more cost effective, develop better controls over inventory and production, and will improve food tracking. Overall, keeping losses to an absolute minimum wherever possible. Delivery will be a standard service for every establishment.
We will probably never go back to our pre COVID-19 ‘normal’ dining habits.
The aim of this post is to help managers in the food industry efficiently manage their business operations in light of these changing times. This is a terrible crisis for food chains but it can also be an opportunity to restructure systems for more efficient and environmentally friendly operation. If you are one of those managers whose livelihood depends on this sector, then please, keep reading.
We’ve compiled 9 strategies for profit optimization in the food industry and I’d like to invite you to be honest with yourself about if, and to what extent, you apply these principles.
1. Financial Controlling
The US Government has created a $349B program for SBAs offering unique loans to small businesses (500 or fewer employees). Loans are based on 250% of the borrower’s average monthly payroll cost for the preceding year (provisions for seasonal employers are included), up to $10 million. Collateral requirements are waived, and the ‘credit elsewhere’ requirements (which have slowed down the process) have been waived as well. Loans are forgiven if used for payroll costs, mortgage interest or rent/utilities.
This program can be a huge help and I suggest applying for it. Even if you can re-open your restaurants soon, much stricter control of finances is absolutely essential.
First and foremost, comes measuring profit. You probably know the overall profit figures from your accounting system. Fine-tuning your reports will require more detailed information: first cost per shop, per shift, per day or time of day, product group or product level. Costs mean not only raw materials and wages but also service costs, overheads and non-productive employee wages.
Do you have a detailed profit report for a given product group, for a given day shop by shop? If you can compare these performances you can then optimize and discover hidden issues, or opportunities. If you’re running a restaurant, do you have profit-analysis on your waiters or tables? You can oftentimes increase profits with something as simple as furniture rearrangement.
To implement meaningful financial controls, however, you need controlling and food industry experts. They can help explore and identify the appropriate KPIs for maximum effectiveness.
2. Raw Material Support
You likely have dozens of raw materials in your shops and you’ve probably set minimum inventory levels in your ERP system. Still, if the consumption of a given product suddenly jumps, employees will find empty shelves and impatient customers.
Predicting future demand for short shelf-life products is one solution. Artificial intelligence technology can deliver over 90% forecast accuracy based on past data patterns correlating with economical, meteorological, geographical and calendar time series. This technology combines deep learning, correlations, and classical regression methods. If you can predict your future sales you can easily alert purchase managers if, and when, raw materials are likely to run low.
3. Food Waste Reduction
About one-third of food produced and packaged for human consumption is lost or wasted. Prediction technologies are now tackling this global issue with growing efficacy. By underproducing your customer finds empty shelves at the end of the day, by overproducing short shelf-life products, your waste becomes your loss.
A powerful AI system helps you accurately predict future sales, while minimizing waste and maximizing revenues. Prediction is particularly important in the food industry because of expiration dates. If you can predict just a 1% increase in sales then you can decrease waste (a 1% improvement could mean thousands of dollars in weekly savings). Additionally, 8 – 10% of greenhouse gases are related to food lost during harvest and production or wasted by consumers (Intergovernmental Panel on Climate Change report).
4. Performance-Based Pay
Financial controlling, KPIs and predictions are all done in vain if employees are not effective, actually generate the waste or are simply underperforming. Managers aren’t able to continuously babysit employees—although it would be nice. A realistic solution could be a sophisticated payroll system where employees are paid on a sliding scale, based on revenues they have contributed. Typically, we do this for collaborators, where the group’s salary depends on sales performance. This works quite well because hardworking people in the group naturally manage less productive individuals because they know their wages depend on them. Creating such a system assumes a good financial controlling system and a consultant with specific industry experience who theoretically develops KPIs, which we can then set up in a BI system.
5. Price Sensitivity Analytics
Price Sensitivity Analytics (PSA) is an approach that uses consumer survey feedback data to determine a range of acceptable and optimal pricing. We want to identify what’s called the ‘equilibrium price’ If you have enough past data you can do this without surveys. This is done by dividing the percentage of product/service purchased by the percentage of change in price. A good BI tool can suggest which product’s price you can raise without losing sales, and which prices you need to lower to sell (much) more.
6. Shopping Cart Analysis
Based on transaction data it’s easy to identify what products customers are buying together, (shopping cart) and this can help sellers recommend related products, or upsell. If we have additional data on customer behavior, it can also be considered in our analysis (what to recommend alongside a hamburger to a boy under 10, for example). Shopping cart analysis also comes in handy when introducing new products or retiring an old product.
7. Raw Material Cost Prediction
By analyzing commodity prices and forecasting their change, purchasing costs can be optimized. Often other costs associated with raw materials (such as shipping, storage, etc.) are the biggest savings found in these analyses. For example, in a downtown NYC restaurant, optimization of a storage area can mean significant savings.
8. Planning
By putting in the work and gathering all the above-mentioned data, KPIs and dashboards, we’ll then have a foundation for dynamic planning. Imagine this: Next year you expect a 10% increase in profit for the chain, shop managers can then plan for period and product groups based on past data. Using an appropriate BI software, planning managers can transfer the actual plan for the current period (week, month, quarter, year) against previous years’ data trends and simply multiply it by 10% (e.g., 12 in 2017, 14 in 2018, 16 in 2019, then BI proposes 18 for 2020, and this could be increased by another 10% to 20). This is a very quick way of planning that breaks down the finest details. Planned KPIs and real time data can then be adjusted.
9. Alerting
Sophisticated alerting and notification system — this is how you get business intelligence to truly work for you, and how you can evolve an automatic control system.
If the system learns that a trend won’t meet the planned profit target for that period, it will send an alert to the manager/owner. And if the BI system is set up as above, it can include the cause of the difference in the alert, and suggest what needs to be changed in order for the profit target to be reached again.
Visualization is likely the sexiest feature in BI software, yet it’s only the tip of the data iceberg. If you need automated control in your business, then you need a dynamic business intelligence system. And if you truly want the most out of your data, learning more about dynamic planning and alerting is fundamentally linked to success. In times like these, with so much uncertainty and speculation, being proactive instead of reactive can make all the difference. We need only look at COVID-19 responses in countries like Germany and South Korea as prime examples.
We sincerely hope these 9 tips pique some ideas and strategies for managing this crisis. How will your business navigate the new food service industry landscape?
We serve businesses in the food industry and more by helping them make the most of their data. How can we help you? DyntellBi.com