Analytics is the science of understanding the relationship between dimensions (example – one or more of time period, menu items sold, wait staff, etc) and measures (example – one or more of covers sold, portions served, revenue earned, etc.)
Traditional systems have reported on such relationships, but inadequately. For example, they have not been able to demonstrate the impact of important non-quantifiable dimensions like weather, events, reputation, etc.
This is the technology domain referred to as 'big data'. One characteristic of big data is that it is unstructured. Traditional systems have not been capable of handling unstructured data. The ability to analyse relationships between, both, structured and unstructured parameters on business results is the purpose of 'big data analytics'.
Restaurant data is not measured in terabytes (a trillion bytes or a trillion units of computer data) or more, as is typical of 'big data'. So let us skip the reference to 'big' and focus on the merits of data analytics. The elimination of reference to 'big' is also good because it eliminates the need for large & expensive computing resources to analyse data.
Contemporary data analytics can demonstrate relationships between rainfall, snowfall or heatwave and menu item popularity, helping restaurants to plan raw material purchases based on weather forecasts for the new few days. The technology can be used to understand impact on pax count of recurring or similar events. An understanding that can be used for labour planning and optimization of labour cost.
These are just a few examples. One thing they share in common is that they all have the potential to contribute tangibly to profits. It is time, already, that restaurant owners and managers discover the power or data analytics.
To view an example of restaurant data analytics, contact us at firstname.lastname@example.org. and ask us to demonstrate Power Touché to you.