Operations and productivity

Every organization makes something. A brewery turns grain, water and labour into beer; a hospital turns the skills of nurses and doctors, equipment and supplies into treated patients; a software firm turns developer time and cloud computing into an app; a city transit system turns buses, drivers and fuel into trips. Operations management is the design, operation and improvement of the systems that create and deliver an organization's goods and services. It is one of the three core functions of any organization, alongside marketing (which creates demand) and finance (which provides and accounts for money). In most firms, operations employs the largest share of people and controls the largest share of costs and assets, so small improvements in operations can have a large effect on profit, customer satisfaction and sustainability.

This lesson introduces the field. It defines operations management and the transformation process, contrasts goods and services, traces the history of the discipline, explains the decisions operations managers make and shows how productivity is measured and improved. Later lessons go deeper on each decision area: strategy, process design, capacity, location and layout, forecasting, quality, inventory, planning, lean operations and the supply chain. The course builds on the arithmetic and break-even analysis in BUS-110; the MBA course MBA-513 revisits the same topics at a more advanced level.

The transformation process

The simplest model of operations is the input–transformation–output model. Inputs are the resources an operation uses. Transformed resources are what the operation changes: materials (a steel coil becomes car doors), information (an accounting firm turns receipts into a tax return) or customers themselves (a hair salon changes a customer's appearance; an airline changes a passenger's location). Transforming resources are what do the changing: facilities, equipment, technology and people. The transformation process adds value by changing the physical properties, location, ownership, storage, information or condition of what passes through it. Outputs are the goods and services delivered to customers.

Feedback and control close the loop. The operation monitors outputs and the process itself, comparing actual performance with targets for cost, quality, speed and other measures, and adjusts inputs or the process when results drift. A bakery that weighs a sample of loaves every hour and adjusts the divider when the average weight creeps up is using feedback control. Random variation in demand, supplier deliveries, equipment condition and human performance means that control is a permanent task rather than a one-time design decision.

Goods and services

The traditional distinction between manufacturing and services is useful but blurred. Pure goods, such as a bag of salt sold in bulk, are tangible, can be stored and are produced away from the customer. Pure services, such as a counselling session, are intangible, perishable (an empty appointment slot cannot be sold later) and produced while the customer is present. Most offerings lie between the extremes. A new car comes with financing, warranty service and connected software updates; a restaurant meal combines a tangible product with a service experience. Many manufacturers now earn a large share of profit from services, a trend called servitization: aircraft engine makers sell 'power by the hour' contracts, and equipment makers sell monitoring and maintenance subscriptions.

The differences still matter for operations decisions. Because services cannot be stored, capacity must be matched to demand in real time, which makes queuing and scheduling central (lesson 4). Because customers participate, their behaviour introduces variability: one bank customer arrives with a simple deposit, the next with a complex mortgage question. Because services are intangible, quality is harder to measure and depends heavily on customer perceptions. And because many services are produced where the customer is, location decisions for services focus on access to customers, whereas manufacturing locations focus on costs and access to suppliers and markets (lesson 5).

A short history of operations management

Operations management has a long history. Adam Smith's 1776 description of a pin factory showed how the division of labour raised output per worker. Eli Whitney and others promoted interchangeable parts. Frederick Taylor's scientific management, around 1900, used time studies and standard methods to set 'one best way' for each task, while Frank and Lillian Gilbreth studied motion and fatigue. Henry Ford's moving assembly line of 1913 cut the time to assemble a Model T chassis from about 12 hours to about 90 minutes, making mass production the dominant model for half a century.

After the Second World War, statistical quality control, pioneered by Walter Shewhart and spread by W. Edwards Deming and Joseph Juran, was embraced in Japan. Toyota developed the Toyota Production System, the basis of lean operations (lesson 11), which combined just-in-time flow with built-in quality and continuous improvement. Computers made material requirements planning (MRP) and later enterprise resource planning (ERP) possible (lesson 10). Since the 1990s, the focus has widened from the factory to the whole supply chain, to services, which now account for most employment in Canada and the United States, and to sustainability. Today, analytics, automation, artificial intelligence and the disruptions of pandemics, extreme weather and trade disputes are reshaping the field again.

What operations managers decide

Operations decisions are often grouped by time horizon. Strategic decisions, made for years ahead, include the operations strategy, the design of goods and services, process technology, capacity, location and the structure of the supply chain. Tactical decisions, made for months ahead, include aggregate production plans, workforce levels, inventory policies and supplier contracts. Operational decisions, made daily or weekly, include scheduling jobs, assigning staff, ordering materials and responding to quality problems. A useful checklist is the ten decision areas used by many textbooks: design of goods and services; quality management; process and capacity design; location; layout; human resources and job design; supply chain management; inventory; scheduling; and maintenance.

Operations managers work across functions. Marketing forecasts demand and promises delivery dates; operations must be able to meet them. Finance evaluates investments in equipment and sets budgets; operations must justify capital spending and control costs. Human resources recruits and trains people; operations designs the jobs. Engineering designs products; operations must be able to make them at the required quality and cost. Job titles include operations manager, plant manager, production planner, supply chain analyst, quality manager, logistics coordinator, purchasing agent and process improvement specialist, and the same skills apply in hospitals, banks, government agencies and non-profits.

Productivity

Productivity measures how efficiently inputs are converted into outputs. It is the ratio of outputs to inputs:

Partial (single-factor) productivity uses one input, such as labour hours (output per labour hour), machine hours, energy or capital. Multifactor productivity divides output by a combination of inputs, usually measured in dollars so that they can be added: labour cost plus materials plus energy plus capital charges. Labour productivity is the most widely reported measure because labour is easy to count and wages depend in the long run on output per hour, but it can mislead: a factory that buys robots raises output per labour hour even if total costs rise. Multifactor productivity gives a fuller picture.

Productivity growth is the main source of rising living standards over time. If output per hour grows 2 % a year, output per hour roughly doubles in 35 years. Productivity growth comes from better technology and equipment (capital), more skilled and better-managed workers, and improvements in methods and organization. For an individual firm, productivity improvement means either producing more with the same inputs or producing the same output with fewer inputs.

National statistics agencies publish productivity data for whole economies and industries. In Canada, Statistics Canada publishes quarterly estimates of labour productivity, hourly compensation and unit labour cost for the business sector, and annual multifactor productivity estimates. Canada's productivity record has become a major public policy concern: estimates often put Canadian business-sector labour productivity at roughly 70 to 75 per cent of the US level, and the Bank of Canada and others have warned that weak productivity growth limits wage growth and competitiveness. Explanations include lower business investment in machinery, equipment and software per worker, a large share of small firms, and the industry mix. For managers, the point is that the national gap is the sum of millions of operations decisions about equipment, methods, training and management practice.

Measuring productivity correctly

Measuring productivity is harder than the formula suggests. Outputs must be comparable over time: if the furniture workshop shifts from simple stools to complex rocking chairs, a fall in chairs per hour may hide a rise in value per hour. Statisticians handle this by weighting outputs by value and adjusting for price changes. Quality changes are hard to capture: a laptop today is far more powerful than one a decade ago at a similar price. In services, defining the output is often contentious. Is a hospital more productive if it discharges patients faster, or less productive if more of them are readmitted? Is a call centre more productive if it handles more calls per hour, or less productive if customers must call back?

Good practice is to use a family of measures rather than one. A plant might track output per labour hour, scrap rate, energy per unit, on-time delivery and overall equipment effectiveness (OEE, covered in ROB-440). A service operation might track transactions per staff hour, first-contact resolution, waiting time and customer satisfaction. Measures should be linked to the operations strategy (lesson 2): a firm that competes on speed should measure speed, not only cost.

# Productivity index for a bakery over six weeks, base week = 100
loaves  = [12000, 12400, 11800, 13100, 13600, 13900]
hours   = [800, 810, 805, 820, 815, 812]
cost_k  = [21.5, 22.0, 21.4, 23.0, 23.6, 23.9]   # total input cost, thousands of dollars

base_lab = loaves[0] / hours[0]
base_mfp = loaves[0] / cost_k[0]
print("week  loaves/hr  per-hour idx  multifactor idx")
for w, (q, h, c) in enumerate(zip(loaves, hours, cost_k), start=1):
    lab = q / h
    mfp = q / c
    print(f"{w:>4}  {lab:9.2f}  {100*lab/base_lab:12.1f}  {100*mfp/base_mfp:15.1f}")
growth = (loaves[-1]/hours[-1]) / base_lab - 1
print(f"Change in loaves per hour over the period: {growth:.1%}")

week  loaves/hr  per-hour idx  multifactor idx
   1      15.00         100.0            100.0
   2      15.31         102.1            101.0
   3      14.66          97.7             98.8
   4      15.98         106.5            102.0
   5      16.69         111.2            103.2
   6      17.12         114.1            104.2
Change in loaves per hour over the period: 14.1%

The output shows how an index makes trends easy to read: each week's productivity is expressed relative to the first week, set to 100. Labour productivity rises faster than multifactor productivity here because input costs rise along with output; a manager would want to know why costs per loaf are not falling as volume grows.

Operations, ethics and sustainability

Operations decisions have social and environmental consequences. Choices about job design affect worker safety and well-being; choices about suppliers affect working conditions far up the supply chain; choices about energy, materials and transport affect greenhouse gas emissions and waste. The triple bottom line asks firms to measure performance on people, planet and profit. Many sustainability gains are also productivity gains: less scrap, less energy and less transport mean lower costs. Others involve trade-offs, such as paying more for low-carbon materials. Lesson 12 returns to sustainable supply chains, emissions accounting and laws on forced labour in supply chains.