Up-to-Speed.

The Latest in Advanced

Manufacturing

by Jayson Myers

It’s time we update the meaning of manufacturing

Jayson-Myers-2It’s long been recognized that you have to measure something in order to improve it.  Accurate real-time measurements stand at the heart of good business planning, operational control, and continuous improvement for any manufacturer. 

Today, advanced technologies are allowing manufacturers to collect, analyze, and use data related to products, processes, business and logistics systems faster, more easily, and in greater volume than ever before.  Data has become the critical resource driving advanced manufacturing in the 21st century.  It is the ability to collect, communicate, and analyze data, and transform data into new solutions – and new sources of business revenue – that is enabling game changing improvements in productivity, process efficiency, and customer value for manufacturing companies and across value chains.  It is what drives innovation.  Ultimately it is what defines the potential for manufacturers to differentiate themselves from their competitors, build partnerships, and grow.

Digital technologies and data driven innovation are revolutionizing the business of manufacturing.  Companies are measuring their productivity and overall business performance differently.  But, when it comes to measuring the performance of the manufacturing sector as a whole, whether in Canada or elsewhere, the data that come from public statistical agencies are woefully behind the times. 

Our economic statistics are geared more to the business structures of the 1970s rather than to current realities.  Why should we care?  Because a distorted view of manufacturing can be misleading if companies are trying to benchmark against industry-wide data.  It can also lead to misguided policy decisions by governments that may downplay the importance of manufacturing because the statistics they use do not give them the full picture.

I was asked recently to provide some benchmark data summarizing Canada’s manufacturing performance over the past 20 years.  When I looked at the data available from Statistics Canada I had more questions than answers.  Here are some of the ways that our economic statistics paint an inaccurate – and usually a very negative – picture of manufacturing in Canada.

First off, there’s the definition of manufacturing itself.  To be counted as a manufacturer, it’s not good enough to produce something tangible.  The main source of value (usually measured in terms of employee activity) needs to be involved in producing goods.  Sounds reasonable.

But, today, there are fewer and fewer people actually working in production.  More and more companies generate value through the services they provide to customers – engineering, technology, logistics, to name a few.  A production-based definition becomes even more complicated when companies have the flexibility to produce a variety of goods and services for different types of customers.  It’s becoming increasingly difficult to categorize a company as a manufacturer when companies themselves define their business in terms of production, innovation, and customer service.  Our statistics should capture the whole array of business activity a company is involved in, rather than trying to fit it into narrowly defined areas of activity.  It takes up to two years, when more detailed data are released about buying and selling across the economy as a whole, to discover that our statistics understate the value of manufacturing output by about 12 percent. 

The lack of an enterprise or a supply-chain view also narrows our definition of what manufacturing is all about – and understates the importance of the sector.  The networked structure of a modern manufacturing enterprise where production and services are being undertaken by a number of different companies instead of being concentrated in one business unit, means that much of the sales, jobs, and value added that were once recorded in manufacturing are now being tracked in the services sector. 

When defined as the business of goods production, the contribution that manufacturing makes to the Canadian economy has shrunk from 16 to 11 percent over the past 20 years.  However, the supply chain around manufacturing has grown to almost 45 percent of total economic activity.  Manufacturing is an even more important anchor of value creation for the Canadian economy than ever before.  It is the ultimate integrator of technology and services.  There are fewer people working directly in manufacturing, but many more people working in jobs related to or supporting manufacturing. We need to make sure we get the full picture of what’s going on.

Another problem arises when statistics report “real GDP” as a measure of value added. I don’t know any company that measures their output in terms of real GDP – more likely in terms of sales or value added calculated as the difference between sales and input costs.  The reason for calculating a “real” number is to adjust for price changes.  Fair enough.  But, price increases reflect more than simply inflation.  They may also occur because customers are willing to pay more for enhanced products or services. 

Tracking Canada’s manufacturing productivity performance can be a dismal job.  It looks like we’re in a downward death spiral.  By not being able to differentiate between value and inflation, price adjusted numbers do a better job in measuring volume growth than enhanced value driven by customization, innovation, and differentiation – the specialty of smaller companies in particular, which by the way, make up most of Canada’s manufacturing businesses. 

When current dollar statistics are used to track manufacturing performance, a much brighter – and I think a more accurate – picture of Canadian manufacturing emerges.  Take profit margins for instance – an indicator that all companies use to measure business performance.  It turns out that Canadian manufacturers are on average more profitable than their US counterparts.  That’s impossible to explain based on “real” calculations of output.  I hate to say it, but it’s a good example of when what is “real” for economists is totally unreal from a business point of view.

There’s one more problem when it comes to using statistics meant to measure the performance of manufacturing as a whole.  Macro statistics include the impact of plant openings and closures.  They can be distorting if treated as a measure for benchmarking individual company performance. 

Canada has lost a number of large-scale manufacturing operations over the past several years.  That’s one reason why our productivity, investment, and employment numbers have fallen.  But, macro statistics mask the productivity improvements and growth of companies that remain.  Bottom line: It’s important to know what numbers actually mean before using them to benchmark performance.

Maybe that’s the real lesson when it comes to using economic statistics.  Handle with care.  We need new definitions and new ways of measuring manufacturing to keep up with the changes shaping modern industry.  It makes more sense to base those on how companies actually measure their own performance rather than on how economists assume the economy is run.