Leading Indicators for Industrials: ISM PMI, Capacity Utilization, and Beyond

Introduction

Industrials investment bankers operate in a world where the economic cycle dictates deal activity, valuation, and client behavior. Unlike healthcare bankers who track FDA approval calendars or TMT bankers who monitor software spending surveys, industrials bankers track macroeconomic indicators that signal where the economy is heading and, by extension, where industrial earnings and M&A activity are going next. The ability to read these indicators accurately and translate them into actionable advice is what separates competent industrials bankers from truly exceptional ones.

This article covers the seven most important leading indicators for industrials banking, explains what each measures, why it matters, and how bankers use it in practice. For interview preparation, you should be able to name at least three of these indicators and explain their relevance to cyclical valuation.

The Institute for Supply Management (ISM) Manufacturing Purchasing Managers' Index is the most widely followed leading indicator for the industrials sector. Published monthly, it surveys purchasing managers at over 400 manufacturing companies about new orders, production, employment, supplier deliveries, and inventories.

ISM Manufacturing PMI

A monthly diffusion index based on surveys of purchasing managers at manufacturing companies. Readings above 50 indicate expansion in the manufacturing sector; readings below 50 indicate contraction. The index is composed of five sub-indices with different weights: New Orders (20%), Production (20%), Employment (20%), Supplier Deliveries (20%), and Inventories (20%). The PMI typically leads GDP by 1-2 quarters and is one of the earliest available indicators of economic direction.

The PMI's value comes from its timeliness and its forward-looking nature. The New Orders sub-index is particularly important because it leads the headline PMI by several months, providing an even earlier signal of demand direction. When the New Orders sub-index drops below 50 while the headline PMI is still above 50, it often signals that contraction is approaching. Conversely, a recovery in New Orders while the headline PMI is still contracting suggests the trough is near.

For context, the ISM Manufacturing PMI registered 47.9 in December 2025, marking the tenth consecutive month of contraction for US manufacturing. The index then expanded to 52.6 in January 2026 and held at 52.4 in February 2026, signaling the first sustained expansion in over a year. This transition from contraction to expansion is exactly the type of inflection point that industrials bankers watch for, as it signals improving conditions for capital goods companies and potential M&A activity acceleration.

The Federal Reserve publishes capacity utilization data monthly, measuring the percentage of potential output that is actually being produced by manufacturing facilities. This indicator is critical for understanding both the current state of industrial demand and the potential for margin expansion or compression.

Capacity Utilization Rate

The percentage of total productive capacity being used by manufacturing, mining, and utility facilities, as measured by the Federal Reserve. The long-run average for total industry is approximately 79-80%. Readings above 80% suggest tight capacity and potential pricing power for manufacturers. Readings below 75% indicate significant slack and likely margin pressure. For industrials banking, capacity utilization helps calibrate where a company sits in the earnings cycle and is a key input for through-cycle normalization.

When capacity utilization is high (above 80%), manufacturers have pricing power because customers face longer lead times and fewer alternative suppliers. High utilization also signals that companies may need to invest in new capacity, driving equipment orders for capital goods companies. When utilization is low (below 75%), there is excess capacity in the system, prices fall, and equipment investment dries up.

For industrials bankers, capacity utilization serves as a reality check on corporate earnings. A manufacturer reporting record margins alongside an industry capacity utilization rate of 85%+ is likely benefiting from temporary pricing power that will not persist as utilization normalizes. Conversely, depressed margins during a period of 72% utilization likely understate the company's mid-cycle earning power. This relationship between utilization and margins is a core analytical concept that appears in interviews and in live deal analysis.

The capacity utilization data can also be decomposed by industry. The Fed publishes utilization rates for dozens of manufacturing sub-industries, from primary metals to transportation equipment to food and beverage. An industrials banker covering machinery companies would track machinery manufacturing utilization specifically, while a banker covering chemical-adjacent industrials would track the chemicals utilization rate. These sub-industry rates can diverge meaningfully from the headline figure: total manufacturing utilization might be at 78% while aerospace utilization sits at 85% and paper products utilization sits at 70%. This granularity makes the data far more useful for sector-specific analysis than the headline number alone.

The relationship between capacity utilization and operating leverage is particularly important. Fixed manufacturing costs are spread over a larger revenue base when utilization is high, magnifying margins. When utilization drops, those same fixed costs are absorbed by fewer units, compressing margins disproportionately. A factory running at 90% utilization might generate 25% EBITDA margins. The same factory at 65% utilization might generate only 10% margins, even with identical pricing. This non-linear relationship between volume and profitability is central to the incremental/decremental margin analysis that industrials bankers perform.

Housing starts (the number of new residential construction projects begun each month) and building permits (authorizations for new construction) are the primary leading indicators for early-cycle industrials sub-sectors including building products, residential construction materials, and HVAC systems.

Housing starts lead the broader economy because residential construction is the most interest-rate-sensitive component of GDP. When the Federal Reserve cuts rates, mortgage affordability improves, housing demand increases, and construction activity accelerates, pulling building products companies forward. The US saw approximately 1.36 million housing starts in 2024 (a 3.9% decline from 2023), well below the long-term demographic demand level, though the level fluctuates significantly with rate movements.

Building permits lead housing starts by 1-2 months because permits are issued before construction begins. This layered leading indicator chain (permits lead starts, which lead building products revenue, which leads earnings) gives industrials bankers multiple data points to assess the trajectory of early-cycle sub-sectors.

The long-term demographic demand for US housing is estimated at approximately 1.5-1.6 million starts per year, based on household formation rates, immigration, and replacement of aging housing stock. When actual starts fall significantly below this level (as they did in 2024-2025 when elevated mortgage rates held starts at approximately 1.36 million), it creates pent-up demand that eventually releases when affordability improves. This concept of pent-up demand relative to demographic need is how bankers frame housing exposure in investment theses, arguing that below-trend starts create a future tailwind for building products companies when the cycle turns.

The Mortgage Bankers Association's purchase application index and the National Association of Home Builders (NAHB) Housing Market Index provide even earlier signals of housing demand, as they capture buyer interest and builder confidence before permits are filed and construction begins. For bankers covering the building products and construction sub-sector, these early signals can provide several months of lead time on revenue trends.

The Federal Reserve's Industrial Production Index measures the real output of the manufacturing, mining, and utilities sectors. While the ISM PMI is a survey-based leading indicator, industrial production is a hard data measure of actual output. The two typically move in the same direction but can diverge: the PMI might signal deterioration while production is still growing (because surveys capture sentiment and expectations, not just current output).

Industrial production is particularly relevant for mid-cycle capital goods companies because their revenue correlates directly with manufacturing output. When industrial production grows above 2-3% annually, machinery companies see orders accelerate. When it contracts, orders decline. During the 2008-2009 recession, industrial production fell over 16% from peak to trough, producing the deepest capital goods downturn in decades.

For specific sub-sectors, bankers track component indices within the broader industrial production data: motor vehicles and parts production for automotive-linked suppliers, mining production for natural resource equipment companies, and utilities production for electrical equipment firms. This granularity allows more precise cycle positioning than the headline figure alone.

Industrial production also provides a useful cross-check on the ISM PMI. Because the PMI is survey-based (reflecting sentiment and expectations), it can sometimes overstate or understate actual conditions. Industrial production, being a hard data measure, confirms whether the sentiment expressed in PMI surveys is translating into real output changes. When the PMI signals contraction but industrial production is still growing, it may indicate that the downturn is less severe than purchasing managers fear. When both indicators align in the same direction, the signal is stronger and more reliable for banking applications.

While housing starts capture the early cycle, nonresidential construction spending captures the mid-to-late cycle. The Census Bureau's monthly construction spending data tracks private nonresidential investment (office buildings, retail, warehouses, manufacturing facilities) and public construction (highways, bridges, water systems, schools).

This indicator is critical for companies like Vulcan Materials, Martin Marietta (aggregates), Quanta Services (electrical infrastructure), and AECOM (engineering services). Government infrastructure spending through the IIJA has created a secular tailwind that complicates the cyclical read: even if private nonresidential construction softens, public infrastructure spending may continue to grow, creating a partial offset.

The split between public and private nonresidential construction matters significantly. Private nonresidential construction (offices, warehouses, data centers, manufacturing facilities) is cyclical and follows business confidence and commercial real estate returns. Public construction (funded by federal, state, and local governments) follows budget and political cycles that operate independently of the economic cycle. The IIJA's $550 billion in incremental federal infrastructure spending is creating a multi-year public construction wave that provides a meaningful counter-cyclical buffer for construction materials and E&C companies. Bankers must disaggregate these two streams to accurately assess cycle exposure for any construction-linked company.

The Cass Freight Index, the American Trucking Associations' truck tonnage data, and railroad carload volumes provide real-time visibility into the physical movement of goods through the economy. Because industrial companies produce physical products that must be shipped, freight volumes serve as a barometer of aggregate industrial activity.

The Cass Freight Index tracks both shipment volumes and expenditures, offering a dual read on demand (volumes) and pricing (expenditures per shipment). When freight volumes decline while expenditures per shipment increase, it signals pricing power despite weaker demand, a pattern that can occur during capacity tightening in the trucking industry. When both volumes and expenditures decline, it signals broad-based demand weakness.

Railroad carload data is particularly useful because it can be decomposed by commodity type. Coal carloads signal utility and export demand. Intermodal volumes signal consumer goods movement. Chemicals carloads signal industrial production activity. This granularity allows bankers to assess which parts of the economy are strengthening or weakening, information that feeds directly into sub-sector cycle positioning.

The Census Bureau's monthly durable goods report tracks new orders for manufactured goods expected to last three years or more. This directly measures demand for capital goods and provides one of the earliest signals of business investment trends.

The key distinction within durable goods data is between total orders (which include volatile defense and aircraft orders) and core capital goods orders (nondefense capital goods excluding aircraft). Core capital goods orders are the purest measure of business investment intentions and correlate strongly with capital goods company revenue 3-6 months later. A sustained decline in core capital goods orders warns that mid-cycle sub-sectors like machinery, electrical equipment, and engineered components will soon see revenue pressure.

The durable goods report also provides data on shipments (which track closer to current revenue than orders do), unfilled orders (the backlog), and inventories. Together with new orders, these four data points create a comprehensive picture of manufacturing demand and supply balance. When new orders exceed shipments, backlogs are building, signaling future revenue growth. When shipments exceed new orders, backlogs are declining, signaling future revenue pressure. This orders-to-shipments dynamic is directly analogous to the book-to-bill analysis that industrials bankers perform at the individual company level, but the Census Bureau data provides the macro context.

The volatility in total durable goods orders (driven by lumpy defense and aircraft contracts that can swing the month-to-month figure by billions of dollars) means that bankers focus on the three-month moving average of core capital goods orders rather than any single monthly reading. A single month's data can be misleading; the trend across three to six months provides a much more reliable signal of underlying demand momentum.

Experienced industrials bankers do not rely on a single indicator but synthesize multiple signals into a composite view of the cycle. A practical framework combines the indicators into three questions:

Where are we in the cycle? The ISM PMI headline reading and trend direction provide the broadest answer. Capacity utilization adds precision about how stretched (or how slack) the manufacturing sector is. If the PMI is above 50 and capacity utilization is above 80%, the economy is in a mid-to-late expansion. If the PMI is below 50 and utilization is below 75%, the economy is in contraction or early recovery.

Which sub-sectors are leading? Housing starts lead building products. Core capital goods orders lead machinery. Freight volumes lead transportation. Nonresidential construction spending leads infrastructure and aggregates companies. By tracking which sub-sector indicators are turning up or down first, bankers can position their coverage teams to pursue the right mandates at the right time and advise clients on optimal transaction timing.

What does this mean for our clients? A banker pitching a sell-side mandate to a capital goods company during an expansion can use rising PMI readings, improving capacity utilization, and growing durable goods orders to argue that the time to sell is now (or soon), while earnings are strong and the macro backdrop supports buyer confidence.