In simplest terms, productivity is the ratio of output per unit of input.

Almost every conversation about change includes a promise of greater productivity.  In simplest terms, productivity is the ratio of output per unit of input.  While the equation is for calculating productivity is straightforward, as we have discussed, deciding on which outputs from an organization or process to count is never straightforward. The decisions on the input side of the equation are often equally contentious.  Three critical decisions shape what measures will be needed to supply the inputs used to calculate productivity.

Deciding which inputs lead to an output that is important. Arguably, every ounce of effort, raw material  and capital within a company is ultimately needed to deliver the organization’s products and services. Yet while calculating the total labor or capital productivity might be interesting to stockholders, it provides very little value for making process improvements within the organization. Framing the question or decisions is the critical first step for deciding which work leads to an output that we want to measure.  For example, we can use the pencil manufacturer described in the output essay. In order to deliver a pencil to market the overall value chain would include purchasing and logistics for raw materials, personnel functions for hiring, management, manufacturing, warehousing, shipping, research and development, marketing and sales (see Pencil Supply Chain to get a hint of the complexity of the supply chain for raw materials in a simple wooden pencil). If the manufacturer wanted to tune just the labor productivity of the assembly process for classic #2 pencils, the organization would need to only measure a small slice of the overall value chain. It begins with determining the output to measure, which leads to the which inputs to measure.  Begin all productivity exercises with some form of Value Chain Mapping that shows how an organization transforms raw materials into a product and then delivers that product to its customers.  Develop value chains so that the organization can get a full understanding of the process to see how they can generate the greatest possible value for the organization and the customer.  Once you understand the flow, it is far easier to improve the whole or parts.

Which components of overhead should be part of productivity calculations.  Overhead represents costs and effort that can’t be easily traced to an output.  Using the pencil manufacturer example, the effort and cost for the maintenance personnel that sweep the plant on a nightly basis or middle and senior management are often considered overhead. Many software development organizations include only direct labor and costs when calculating productivity .  Another “normal” practice is to apply a uniform allocation of overhead to each project.  Both of these scenarios can and do cause significant distortions.  For example, a troubled project often consumes significant amounts of management time and oversight (more input) than a well-run project requires (less input).  More input for the same amount of output yields lower productivity. Allocation is an easy process but it is regressive.  Allocation impacts the projects that are least reliant on non-direct labor and cost more than projects that are more reliant.  In the scenario where one project implemented an application that leveraged an internal server farm used by several applications while another leveraged the cloud for processing, allocating the server costs across all projects even if they did not use the servers, would distort capital productivity.

Sourcing refers to purchasing work and/or components for a product from an outside vendor. In the scenario where our pencil manufacturer has outsourced forming the wooden pencil barrel to an outside firm labor, productivity would increase because the process would use less internal effort. In this scenario, the increase in raw material will reduce raw material productivity. The question would be whether the improvement in labor productivity is better for the company than a reduction in raw material productivity.  In software development, firms often reduce the cost of work while moving labor effort off an organization’s books, thus obscuring overall productivity.  For example, an organization that outsources technical design, coding and development related testing can only measure the labor productivity of the work they retain control over, therefore if they are measuring labor productivity they need to understand that it is only a partial picture.  This realization often shifts the data needs from labor to raw materials or capital. The decisions an organization wants to make to focus on the cost of raw materials rather than “labor” productivity or some combination of the two.

Deciding what to measure is the second step in unwinding the complexity of the productivity equation.  The inputs in the productivity equation are related to outputs and the decisions that will be made with the information. The decision you are going to make based on productivity will guide you to whether you will need to measure effort, cost of raw material, overhead, physical plant or the cost of outsourced work.  Each will tell a different story about the efficiency of the transformation of an input into an output.