Accessing, translating, forecasting – data analytics
Food chain EAT was looking to open more branches. Its financial systems were made up of SQL databases and Excel spreadsheets. In the past, for each branch opening, new tabs were added to the spreadsheets, with more rows and columns, requiring highly manual processes for each planning cycle. This was suitable when the business launched in 1996 with one branch, but the system lacked the sophistication to analyse the data to support its growth plans.
EAT realised it needed to evolve its finance department to keep up with business growth plans. With more than 110 branches, 200 products and 10,000 ingredients, EAT has a high volume of data at its fingertips. As EAT continued to grow, it became clear that storing this data in Excel wasn’t practical for forecasting and recording, for example, the costs of each product line or how well products were selling.
With the aim to have the new system launched by the start of the new financial year, EAT found a data analytics solution that was able to offer the level of detail that could show the costs of every ingredient of each product, sale and branch.
EAT decided to make the investment to replace its whole system with an intuitive front end that employees could easily operate. After building a system that could replicate the reporting of its current system, EAT set about improving the forecasting and reporting capability, which meant adding functions to calculate costs of sales – breaking down products into ingredients, then ingredients into costs – and assigning these to each branch.
With its data analytics system in place, EAT can compare budgeted costs with actual costs. It can do this at a product, ingredient and branch level, and it can do this on demand. EAT now has a clear view of what drives its profitability, which has led to reducing the company’s running costs. And it has a system that can expand with growth and help drive strategic business decisions.
What data analytics means for employee retention and attraction
Companies that use data analytics are innovative employers, as they recognise the value in giving employees the right analytics tools. For employees, having data analytics tools at hand frees up processing time and provides employees the ability to translate key data trends into actionable innovative solutions that can improve the business’s bottom line.
Case study source: https://www.anaplan.com/customers/eat-case-study/