A deluge of data doesn’t necessarily mean it is useful or well applied. It’s easy to drown in data and many of us struggle to know what data really matters and what is just noise. Simon Hedaux offers some solutions for making better use of the information
There is a lot of data around these days. Global data volumes are now measured in Zettabytes – that’s one byte with a massive twenty-one zeros after it. And, the average smart phone holds more data than a 20-year-old laptop.
Businesses have made giant strides in how they use customer data. Companies like Tesco and Boots have created game changing insights from their loyalty card data and even monetised sharing that data with big suppliers. Yet, despite the progress in customer data application, there has not been similar progress in how businesses measure their operation.
Operational measures are often high level, giving a top line view through measures such as stock turn, salary to sales percentages, margins and colleague churn. It’s really not very different to KPIs that were used 50 years ago. Given that sluggish productivity is a feature of the UK economy, and many others globally, it might be reasonable to expect more progress to be made.
Productivity measures that are in place are often output measures, such as a scan rate for a colleague on a till and case rates for colleagues handling stock. While these can give a useful indicator of when a colleague’s performance is out of line with their peers; they do not give any indication of why there are differences and what the optimum rate is to balance speed and quality. It’s no good being super speedy with cases of ripe fruit, or delicate china and damaging the stock as you go.
So, if you do want to use operational measures to make better decisions in your business and to find the opportunities in your operation; what can you do?
Process measurement started in the middle of the 20th century. Often known as time and motion study, it was first applied to production lines. It is often associated with the super-efficient car factories in Japan yet was first widely used in manufacturing in the US. Several different study techniques were developed to create actionable insights that quantify wasted time, identify productivity improvement opportunities and provide insights on root cause of problems.
B&M is a company that used an external team to improve its productivity as although they were on their way to becoming one of the UK’s fastest-growing variety retailers, some of their processes hadn’t kept up. Studies from the external team showed that a disproportionate chunk of time was spent refilling shelves; they were using customer trolleys to move items from the stock room, and although it was a method that had served them well in the past, it was starting to cost them in terms of colleague hours as stores became busier.
Along with other tweaks to manual systems they’d begun to outgrow, it was recommended that they introduce new, more efficient stocking equipment plus options for pricing and ticketing technology. The process measurement data showed just how many hours all this could save.
Quiet periods at tills and counters can be hard to avoid, and they can have a significant impact on your overall efficiency. Measurement to quantify down time is always insightful for businesses.
Screwfix, for example, has separate till areas for trade and retail customers, looked after by colleagues trained to serve one or the other. Measurement showed that, at times, the trade sections were busy while retail was empty and vice versa, but because of their division of skillsets, colleagues weren’t able to switch over and help out.
Screwfix HQ was surprised by the amount of downtime it caused, and although there’s no quick fix –recommendations were to either multiskill colleagues or introduce more digital kiosks – the quantifiable data they were given will help inform decisions around their long-term strategy.
Travelodge also had an issue with quiet periods in hotel receptions. The hotel chain wanted to investigate whether there was a way to reduce downtime, when no customers required help. It was discovered that teams in different locations had developed their own methods for filling that time, from finding small jobs they could complete in situ to spending short periods away from the front desk. Data gave HQ the information they needed to trial different approaches and inform their customer strategy.
You might not have heard of Parkinson’s Law, but chances are you’ll know the proverb that defines it: ‘work expands to fill available time’. It underpins research into clients’ efficiency. If a team are performing at a less than ideal speed, it’s a sign they’re not busy enough, and it could be costing the business money; that’s why I recommend using pace measurement is in studies.
Firing on all cylinders, giving it their all, performing at full capacity – however you put it, a pace rating study is about clocking the effort your team members are putting into a task, by assessing whether they’re completing it slowly, hurriedly or at an optimal speed. Pace measurement doesn’t just help to build an accurate picture of efficiency, it also indicates contributing factors and opportunities.
A pace dip is often seen when people aren’t getting enough direction from their managers, there aren’t enough supervisors present to motivate teams, or there are too many team members on a shift. And it can have big consequences. Whenever colleagues are taking longer than necessary to complete a task, you’re having to over-invest your salary budget to get the job done.
Pace measurement at B&M and Wilko showed that although they benchmarked well to similar businesses for overall efficiency, pace rating studies highlighted areas of work that fell well below expectation – and how tackling underlying issues could save them money.
For both retailers, there were signs that colleagues were using stock replenishment as a way of filling time, and consequently, identified significant opportunities to pick up the pace. It was a particular issue for Wilko in the evenings, when supervisors were thinner on the ground and there was less of an obvious need to move on to another task. An inconsistent pace performance across different stores was also revealed indicating a possible influence of leadership and differences in rota planning.
Time and motion measurement across multiple sights also provides rich insights into consistency – or lack of it- across the business estate. Ironing out process variance and identifying best practice are typical outcomes of these detailed operational measures.
Operational efficiency data collection and measurement can provide meaningful insights into the operation and quantify opportunities to improve productivity and efficiency. The challenge is to know what to measure and how to interpret the results – and that is perhaps why operational data utilisation has not advanced in recent times. It takes a combination of time and motion measurement know how and operational understanding to connect the data to value adding insight. In many businesses there is a productivity manager sitting on a gold mine of meaningful measurement and productivity opportunity insights. Go and find yours – they’ll be pleased to help you make better data driven decisions.
Simon Hedaux is Founder and CEO of Rethink Productivity, a productivity partner which helps businesses to drive efficiency, boost productivity and optimise budgets. For more information see https://rethinkproductivity.co.uk/
