Car manufacturers get daily, even hourly, updates on car sales from dealerships all over the country. This data gets fed into sophisticated supply chain systems that then predict how many cars need to be produced based on sales levels and the popularity of an individual model. This is then translated into component parts, and orders are generated to suppliers. Shipping information is sent to FedEx, UPS, and trucking companies, and accurate data is made available to customers about when products will be available. In fact, these systems are so good that it is a rare day when a product is not on the shelf when you want it, in the color and model you want.
But to get to this point, manufacturers have spent over 50 years developing the systems and approaches that makes this complex system possible. Every formal process you have heard of — from just-in-time manufacturing to Six Sigma — has its origin in trying to achieve the goal of efficiently and cheaply making products available you when and where you want them. This whole system is generally called “supply chain management,” and manufacturing firms have almost perfected today’s supply chains. Suppliers and users have established flexible, just-in-time supply arrangements for all kinds of products. Manufacturers can provide enough lead time to suppliers to ensure that only in the rarest of circumstances (hurricanes, earthquakes, and war) will there be any major disruption in production due to the lack of parts or raw materials. Manufacturers have honed their ability to accurately predict the need for parts, and suppliers have put in place rapid and highly flexible tools and processes to make whatever is needed.
The 21st century will see these same processes applied, albeit with many differences, to the supply of skills and talent. Talent is the new scarce raw material, and organizations are just now beginning to elevate the idea of predicting talent needs and ensuring a talent supply to a more central place in their thinking. IBM, Johnson & Johnson, and a few others firms are well along in putting into place the elements of a labor-based supply chain mindset. A recent article in Harvard Business School Weekly is worth a read to see how IBM is approaching this. Any talent supply chain has to deal with several dynamic forces simultaneously. These include the business cycle, changing organizational structure, evolving corporate strategy, technology dynamics, and regulatory changes. It will take more than just the recruiting function or even human resources to create the systems needed for labor-based supply chain management, but recruiters do have a major role to play. In the end, technology, finance, HR, recruiting, training and development and workforce planning will all need to work together to develop these processes. In this article I will lay the foundation and discuss the basic elements of a labor-based supply chain. In next week’s article, I will talk about some specific things you can do to get started. IBM has perhaps devoted the most public time to talking about this, and they have created an approach that works. This approach forms the basis of what I talk about below. They have been developing a labor management system that takes many of its practices from their success in manufacturing. By correlating success to skills and other selection criteria, constant improvements can be made in productivity and customer satisfaction.
Developing a Skills Taxonomy
A labor-based supply chain starts with developing a list of the skills required to meet your customer’s needs. Academics call these lists “taxonomies.” A skills taxonomy clearly defines what knowledge, abilities, and skills employees need to have. These, in turn, make it easier to assess candidates and current employees to see where there are strategic gaps. Technology can be harnessed to warn you when skills are missing or when, through attrition or retirement, specific skills are going below predetermined levels. For example, suppose that your corporate strategy is to supply financial consulting services to a specific industry. The first step would be to determine which skills are needed to perform that service and which are industry specific.
Once this has been completed, you can take stake stock of your current workforce to see which skills they have and which are missing or in short supply. Any skills that are lacking can be recruited from outside or developed internally, hopefully ahead of a crisis, which often leads to hasty hiring or incomplete development. But without any definition of needs, no assessment at all can be made. This often leads to poor decisions, inefficient practices, or employees being asked to do things they are not really qualified to do or to. Very few organizations have skills taxonomies, and even if they do, they are probably not dynamic or up-to-date — or even used at all. A really useful taxonomy is constantly being updated, correlated with success, and evolving as strategy and competition change. By identifying these skill needs, you can also emphasize to workers where they should spend time in development or where to focus development budgets. As your strategic planners look at opportunities, this taxonomy and skills survey can give them the information they need about how realistic or in what timeframe your organization could compete effectively in those area.
Measuring Success and Tracking Progress
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The Competitive Hiring Advantages of Small Businesses
The second step in this process of developing a labor-based supply chain is to put in place measures of employee productivity, performance, and quality. This means that standards have to be developed and measured against on a frequent basis. For service delivery people, the standards may be time, speed, or quality and will probably be a mix of all of these. IBM measures its consultants against all of these, as well as against customer satisfaction. By employing the right technology that tracks these on a regular basis, managers can get early alerts when performance falls below predetermined levels. Performance can be matched against the skills and abilities identified in the taxonomy, and the taxonomies can be updated if a skills are found not to correlate well with success.
For example, two consultants working on similar projects (perhaps even for the same client) may have different levels of productivity and customer satisfaction. By measuring and tracking these differences, and by matching the consultant’s skills to their performance, changes can be made in selection and development criteria. What is emerging is a more quantitative performance management process, based on specifics such as productivity and quality rather than on whether a manager likes you. As talent becomes harder to find and keep, productivity will become a key measure of employee value, as will other quantitative measures. I will address more about how to put something like this is place next week.
The third step is to integrate technology into this process wherever possible. Technology can be used to help attract candidates and to take them through the process of screening and assessing capabilities and skills. It can be used to track and measure success, to keep skills inventories, and to use those inventories for screening and matching. Technology can keep employee portfolios and make them available to hiring managers when they are looking for people with particular skills or abilities, and it can correlate skills to success. If technology is not deeply integrated into the human resources function, no significant productivity improvements are likely to be made. There are too many variables and too much information to be examined and related for a human to cope with. A labor-based supply chain is as much a change of mindset as it is an implementation of process and technology. It is about making a statement that human beings and their outputs can be measured and improved, at least to a greater level than we have ever done in the past. Next week I will discuss some specific steps you can take to being putting a version of labor-based supply chain thinking into your function.