When will our guests arrive?

When will our guests arrive?

The idea

Have you ever wondered how to reduce food waste and optimize staff planning at the same time?

You believe the two don’t go together? 

Read on and learn how Prognolite makes it happen. 

Why Prognolite?

The head chef would like to know how many meals to produce. The dilemma: Too many purchased and prepared meals result in food waste, too few translate into a loss of revenue and dissatisfied guests.

The restaurant manager would like to know how much staff to schedule. The dilemma: Too many employees generate high labor expenses, too few result in a loss of revenue and dissatisfied guests.

Your benefit

Reduce food waste

Reduced food costs, demand-oriented production based on article forecasts

Optimize staff planning

Deployment of staff at the right time, knowledge retention within the company in case of turnover 

Automate processes

No time-consuming comparison of previous performance, reduced office hours

Use data for strategic purposes

Standardized data from different cash register systems through the use of universal API 

For whom?

With Prognolite, everybody wins

Restaurant
managers

efficiently schedule their employees based on the forecast and thus reduce waiting times. The app facilitates their budgeting and recommends the ideal shift plan.

COO‘s

help their businesses to achieve higher productivity through innovative technology. With the exact forecasts, they improve financial performance and are ahead of competition.

Head chefs

purchase food according to the projected consumption. Thanks to better planning, they reduce food waste as well as food costs. 

Guests

enjoy their dish of choice without long waiting times.  

The product

The core of the forecasting app consists of an algorithm, calculating the turnover and the number of dishes sold for any given period in the future. Prognolite determines the influence of weather, public holidays and trends utilizing automatically imported receipts of the last one to two years. With the aid of sophisticated technology, the tool achieves a forecast accuracy of up to 95 percent!

Influencing factors

All required data is automatically exported and prepared from the respective system (e.g., POS).

Turnover & staff forecast


Article forecast & daily overview


The software calculates the forecasts for one month in advance. Short-term forecasts reach an accuracy of up to 95%.

Pricing

Benefit from substantial savings when it comes to food and staff costs. 

Basic package

Type of forecast

Turnover

Price / month / restaurant

300

CHF

Initiation fee

Gratis


Get an overview

Staff forecast

Type of forecast

Staff

Price / month / restaurant

+ 100

CHF

Initiation fee

500

CHF


Optimize staff planning

Article forecast

Type of forecast

Article

(up to 5 items)

Price / month / restaurant

+ 100

CHF

Initiation fee

500

CHF


Reduce food waste

Savings potential

Sample restaurant

Turnover

1 Mio

CHF / year

Staff costs (50.6%)

506’000

CHF / year

Food costs (27.5%)

275’000

CHF / year


Source: Branchenspiegel 2018 by GastroSuisse

Savings potential

Total savings

CHF / year

Equals 2h per day in staff costs

19’000

CHF / year

50% less overproduction (food waste)

9’000

CHF / year


Calculation:
– 2 hours x 37.00 CHF x 21.75 days x 12 months = 19’314 CHF
– 275’000 CHF x 0.12 x 0.55 x 0.5 = 9’075 CHF
– 12% total food waste; 55% overproduction; 50% avoidable

What others say about us

Fredy Wiesner Gastronomie

Mr. Wiesner, what are your experiences with Prognolite’s forecasts?
The sales forecasts come very close to the actual figures. After being a little skeptical, our managers use Prognolite on a daily basis now. Also the deputies check the projected turnover in the afternoon and let the service employees come in earlier or later accordingly. 

How important is working with the forecasts for your operations?
We provide all managers and deputies with a tool for turnover and staff planning. This offers them security, especially when they are new to the company. We are going to implement Prognolite in all medium and large businesses soon, as we consider the forecasts to have considerable potential.

Why did you decide in favor of using Prognolite?
Turnover and staff planning are of great importance in all our restaurants. Since young or new members of the management initially struggle with planning, we were looking for a tool that supports them in their work and offers them a degree of certainty. As a result, they recognize risks earlier and more frequently, which not least reflects in the savings in staff expenses. 

Daniel Wiesner,
COO Fredy Wiesner Gastronomie

Sinnvoll Gastro

Mr. Feigenwinter, what are your experiences with Prognolite’s forecasts?
We have been testing Prognolite in our hotel restaurant Kaiserstuhl close to the Brünig pass for a few months now. Prognolite helps us to identify how different factors influence our turnover. Thus, we can continuously improve our predictions. The accuracy of the forecast is impressive and, thanks to Prognolite, independent of people.

How important is working with the forecasts for your operations?
The right and optimized staff planning is essential for a restaurant business – and it can be improved even more with the help of accurate turnover planning. Technical support for various planning processes will gain in importance in the future, also to make them more long-term and reliable. 

Why did you decide in favor of using Prognolite?
I am generally open to innovative ideas that provide us with technical support. I see great potential and have noticed that the makers of Prognolite are very receptive to inputs. Hence, I decided to be involved from the very beginning. I am looking forward to further exciting developments.

Simon Feigenwinter,
Co-Founder of Sinnvoll Gastro

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About us

Simon Michel

Founder & CEO

Founded his first company at the age of 18

Roman Lickel

Founder & CTO

15 years of experience in web and software development

Lukas Stolz

Head of Data Science

Became lecturer at the age of 27

Nico Schefer

Head of Business Development

Became restaurant manager at the age of 26

Aurelia Stirnimann

PR & Business Development

Wrote her Bachelor thesis on food waste mitigation in the Swiss restaurant industry

Maximiliano Luchsinger

Data Science

Applied machine learning techniques to optimize staff planning at the Zurich Airport

Jonathan Gerber

Data Science

Completed his Bachelor assessment year among the top 5% of the university

Valon Fejzullahu

Software Development

Was involved in multiple software development projects for a large bank

Press room

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