Jeremy Harford, Managing Director of MESTEC, explains the five reasons why your manufacturing KPIs fail to improve factory performance.
By all accounts, times are tough for UK manufacturers. The CBI’s recent industrial trends survey reports that factory output fell during the last quarter at its fastest pace since 2009. Manufacturers continue to struggle with a range of issues, including weak market demand, global trade and Brexit fears; some even report that recent localised flooding and mild weather have hit production.
There will always be outside issues over which you have no control; a state of affairs that makes it even more important to ensure that what you can control has a positive outcome for your business. For many manufacturers, that means looking to identify and improve their key performance indicators (KPIs).
However, manufacturing KPIs are not always a panacea for improved factory performance. We talk to many people in production management roles, and while some of them can quote reasonable KPIs, they still struggle to improve overall performance. Why is that?
Here are the top five reasons why KPIs sometimes fail to improve factory performance:
It’s too hard to gather the data
In order to calculate KPIs you need to have the right data. For example, if you don’t know how long it takes to complete a task, you’ll never be able to calculate two of the key manufacturing metrics – overall equipment effectiveness (OEE) and overall labour effectiveness (OLE).
Without the right systems in place, it can be difficult to gather the basic data you need. If you depend on paper-based timesheets, then you also rely on shop-floor staff or supervisors to collect the data: a process that is labour-intensive and prone to inaccuracies. Even small variations in source data can lead to big error margins when aggregated over multiple tasks, staff and production lines.
It’s too hard to calculate meaningful KPIs
On shop floors where manual labour represents a significant proportion of the manufacturing costs, OLE assumes more importance as a KPI. However, in our experience, it is rarely tracked in detail because it is difficult to calculate. To calculate OLE you need to consider three components: utilisation (direct hours vs attendance hours), performance (actual speed vs standard speed) and quality (per cent labour hours lost to rework or scrap). Manually analysing detailed data for all of these components is time consuming and error prone.
Most manufacturing operations can come up with overall labour effectiveness (OLE) figures for the entire organisation or particular departments, but aggregated figures don’t help to identify which teams, operators or tasks are underperforming. When it comes to most manufacturing KPIs, the devil really is in the detail.
(Click on image to enlarge)
Our data (and KPIs) are out of date
If all you do with your KPIs is present them at your monthly production meetings then it may not matter that the information you use is out of date. If, however, you want to use KPIs to improve your operations, then having up-to-date figures will open up many more options for improving productivity and reducing costs.
For example, having real-time information that identifies where and why products are failing tests will enable you to identify the root causes and address the problems immediately, avoiding the costs associated with scrapping or repeatedly reworking products, or even worse, shipping defective products to your customers.
We don’t know how to make KPIs visible
A picture is worth a thousand words. Likewise, using high-impact graphics that are clearly displayed on a real-time dashboard screen on the shop-floor will ensure that you communicate KPI trends far more effectively than using tables of numbers in multiple spreadsheets or pieces of paper pinned to a notice board.
To get to the root causes of issues, it must be easy to drill down from the headline KPIs into the key operational data, such as labour and materials costs, yield and failures, and so on. Only by enabling easy analysis of data will you encourage the use of KPIs as a basis for improving manufacturing productivity and efficiency.
Our KPIs aren’t actionable
Having KPIs that you can do something useful with depends on addressing all of the points above. To ensure KPIs are actionable, you must have accurate, granular data that you can easily collect in real time. You must be able to take that data and use it to create the KPIs that are relevant to your processes. Sharing up-to-date KPI information at an appropriate level with your staff – including production operators – in a visually meaningful way will enable them to take action either to put something right or to support a process of continuous improvement.
Satisfying all of these criteria depends on having a factory recording and analysis solution that automates shop-floor data collection and analysis. MESTEC provides manufacturing solutions that measure and transform factory and labour productivity. Our software enables you to easily collect the data that you need to track KPIs, giving you access to the level of detail you need to inform decision-making, and embark on a journey of continuous improvement.
We offer our manufacturing system ‘as a service’ for a low monthly fee based on the number of terminals you need, which makes it affordable and easy to budget for. Typically, we can get a factory up and running within a week.
Ready to find out more?
Please contact us as we would be delighted to discuss your manufacturing challenges and demonstrate how our rapid, low-risk solution could bring major cost savings and performance improvements to your business.
You might also find these posts useful:
You might also find these posts useful:
- 6 essential KPIs for world-class factory performance
- Six root causes of poor labour productivity
- Five must-have features for your next shop floor data collection system
- How to turn small batch manufacturing from problem to opportunity
- Five reasons why your manufacturing KPIs fail
- Essential features for Advanced Planning and Scheduling (APS)