Five ways data analytics power productivity

Simon Headaux

Productivity is an ongoing challenge for retailers and as Covid forces more changes, there has never been a better time to get to grips with your productivity opportunities.

By ReThink Productivity CEO Simon Hedaux. 

Collecting and analysing data to create actionable productivity insights is essential. These are our top five data analytics tips to power your productivity.

  1. Which measure?

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

Many retailers use sales intensity data, such as dollars per square metre, as their productivity measure. It measures output and is important as part of the set, but it doesn’t help you know if your inputs are right. For example, have you optimised the salary budget and planned hours at the right time? Using salary to sales percentage is a blunt tool unless all your stores are identical.

What’s the right productivity measure for you? Identify the suite of measures that link to your operating model and how it supports delivery of your strategy. If you are differentiated on customer service, find measures that pin down how well you are delivering customer experience. If you are a low-cost operator, look at labour invested by volume of items sold, or the case rate of colleagues handling stock.

A dashboard with a suite of measures tracks your day to day productivity. But how do you make a step change? Work study can help.

  1. How long does it take?

What is commonly known as time and motion study can help you deep dive your processes. By timing multiple instances of a task being completed, the data can be analysed to identify a detailed process breakdown. Data analytics shows up wasted time in the process, for example where a colleague must wait for a system to catch up with them or where walk times within tasks are higher than needed. Activity study creates a timed baseline for your processes. You can make operational process changes and then measure the differences to check you delivered your business case benefits.

  1. How do the 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 retailers remove wasted time from their operation and reduce task time to increase time with customers.

  1. How do leaders spend their time?

A trend within retail has been to simplify instore leadership structures and remove layers of expensive management. A day in the life role study produces data that shows how leaders spend their time and whether there is a clear differentiation between multiple leadership roles. The data analytics provide a robust basis to identify opportunities to right size leadership teams and create the role clarity that is needed for effective leadership.

  1. How are we doing versus our competitors?

Data analysis really comes in to its own when you compare your own productivity measures to others.  It helps retailers gain a powerful understanding of how their productivity measures stack up in their own and comparable sectors.

Data analytics can either create insights that power your business or leave you drowning in a mass of inconsequential numbers. Thriving retailers choose the right internal productivity measures, use workstudy to understand the detail and look at comparator benchmarks to give that all important context.

 

 

About Simon Hedaux

Simon Hedaux is founder and CEO of Rethink Productivity, a world leading productivity partner which helps businesses to drive efficiency, boost productivity and optimise budgets. For more information see https://rethinkproductivity.co.uk/

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