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Four ways data analytics can power productivity

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Four ways data analytics can power productivity

From competitor research to evaluating your processes, crunching data correctly can jettison time-absorbing resources and propel your franchise’s operations

From competitor research to evaluating your processes, crunching data correctly can jettison time-absorbing resources and propel your franchise’s operations.

Productivity is a challenge for the global economy. McKinsey, in its article entitled Solving the productivity puzzle, attributes the productivity slow down to the end of the 1990s productivity boom, the financial crisis after-effects and the fact that digitization has not yet delivered on its promise to transform how we work.

Business and markets have never been more challenging, yet all the change brings opportunities, which means there has never been a better time to get to grips with your productivity opportunities. Collecting and analyzing data to create actionable productivity insights is key – here are my top data analytics tips to power your productivity:

1: Decide what to measure

We all know that having the right KPI is essential to understanding your business and to generate the right focus and behaviors from your leadership teams.

Many businesses use a revenue intensity measure, such as pounds-per-square-meter, or even just weekly sales as their top-line productivity measure. They are great output measures and important as part of the set, yet the challenge is they don’t help you to know if your inputs are right. For example, are you spending more salary than needed to achieve sales? And, is your operation efficient?

Just moving to a salary-to-sales percentage as a productivity measure is a blunt tool and yet franchise partners need a guide to work to.

What’s the right productivity measure for you? Look at your operation and find the suite of measures that link to your operating model and how it supports delivery of your strategy. If you are differentiated on the service you provide, find measures that pin down how well your outlets are delivering great service, like customer experience measures. If you run a quick-serve business, include measures of the time from orders being placed to when they’re fulfilled.

Whatever mix of operational measures are right for your business, always look at them in the context of the relevant quality measures that will form part of the agreement between the brand and franchisees.

2: Look into the processes within your operation

What is commonly known as time and motion study can help you deep dive into processes within your operation. By timing multiple examples of a task being completed, the data can be analyzed to identify a detailed process breakdown. This matters because you create an evidence base that shows the parts of your process to focus improvement efforts on – or even better eliminate. Data analytics also show up wasted time in the process, for example, where a colleague has to wait for a system to catch up with them or where walk times within tasks are higher than needed.

This activity study creates a timed baseline for your processes. You can make operational process changes and then measure the differences. This is important as it can be easy to make changes that don’t deliver the process reduction that you expected.

For a franchise business, you need robust operating procedures to help you deliver a consistent product and service experience. Making sure those processes are as slick as possible adds value for the whole business.

“Collecting and analyzing data to create actionable productivity insights is key”

3: Look into how your team spend their time

A useful technique called efficiency study looks at the whole operation, capturing data on what colleagues and customers are doing. This data analytics creates a detailed picture of how much time is spent with customers rather than on processes and how well the available colleague resource matches the customer flow and demand.

Insights from this study help businesses remove wasted time from their operation and release time from tasks to increase time with customers. One organization, with over 400 U.K. company-owned and franchise partner stores, has used analysis to reduce time on essential tasks and eliminate significant wasted time in the business. This resulted in an increase in the proportion of time staff spends with customers by almost 40 per cent over a period of seven years. The company is now growing revenues and increasing productivity measures.

The study also helps operators spot where they are not keeping up with customer demand and identifies colleague time that can be moved from quieter times to drive sales and increase productivity. When doing efficiency study analytics, it is also useful to get a perspective on the variance between outlets.

4: Look at how you compare to your competitors

Data analysis really comes into its own when you compare your own productivity measures to others. It helps retailers and hospitality brands gain a powerful understanding of how their productivity measures stack up in their own and comparable sectors. There is nothing quite like seeing data analytics that show your business is way off the pace to focus senior leaders on powering productivity. Or knowing that you are currently best in class and others are very close behind you.

Data analytics can either create insights that power your business or leave you drowning in a mass of inconsequential numbers. Businesses that are thriving in today’s turbulent world choose the right internal productivity measures and use work studies to give a wider perspective – they also look at comparator benchmarks to give that all-important context.

ABOUT THE AUTHOR

Simon Hedaux is the founder and CEO of Rethink Productivity, a productivity partner that helps businesses drive efficiency, boost productivity, and optimize budgets.

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