Revenue Planning When the Economy Sends Mixed Signals

Executive summary

• US headline inflation moderated to 3.5% year over year in June, and core inflation sits at 2.6%. Over the same twelve months, energy rose 15.7% and gasoline 26.7%. For a business with freight exposure, “inflation is moderating” is simply false.
• US real GDP slowed to a 1.5% annualized rate in Q2 from 2.1% in Q1, while the S&P manufacturing PMI held at 53.9 in July, comfortably in expansion. Aggregate deceleration and sector-level expansion are happening at once.
• Mixed signals are harder to plan against than bad ones, because they justify any conclusion. Most planning processes resolve that ambiguity in the worst possible place: at the top, by choosing a growth number, then cascading it down as if it were known.
• Three questions convert a macro data point into a revenue decision. Does it change what customers can afford, what it costs to serve them, or how long they take to decide. Most macro noise touches none of the three for a given business.
• The output of good planning under uncertainty is not a better number. It is a smaller number of decisions, each with a named trigger and a pre-agreed response.
• A second category of assumption never flips inside a quarter and so gets omitted from annual planning entirely. Where your customers deploy capital determines your addressable market three years out, and most plans inherit that geography rather than choose it.
• This article makes no economic forecast and none of it should be read as one.

The signal really is mixed

Start with what is measured rather than what is felt.

Inflation. The US Consumer Price Index rose 3.5% over the twelve months ending June 2026, and core CPI, which excludes food and energy, rose 2.6%. Those are the numbers that make headlines about cooling inflation.

Underneath them, energy prices rose 15.7% over the same period, gasoline 26.7%, and airline fares 26.5%. Shelter rose 3.3%. Food rose 3.0%.

That distribution matters more than the average. A software company with a remote workforce and a services company with a national delivery fleet experienced two different economies over the last year, and only one of them can honestly describe inflation as moderating.

Growth. US real GDP grew at a 1.5% annualized rate in the second quarter, down from 2.1% in the first, according to the Bureau of Economic Analysis advance estimate. Consumer spending, investment and exports rose; government spending fell.

Activity. The S&P Global US manufacturing PMI was 53.9 in July, matching June, which is solid expansion territory. The eurozone composite PMI sat at 50.0, the exact line between expansion and contraction, with manufacturing at 51.4.

Expectations. This is the number most revenue leaders skip, and it is the one that shows up in negotiations. Median one-year-ahead inflation expectations rose to 3.7% in June and three-year expectations to 3.3%, the highest since June 2022, as reported in McKinsey’s Global Economics Intelligence summary for July.

Trade. The United States imposed 25% tariffs on a range of Brazilian products from July 22, with beef, coffee and aircraft exempt, and a targeted 10% tariff on roughly 20% of Mexican exports from July 24, applying to goods outside USMCA duty-free provisions.

So: inflation down, energy sharply up, growth slowing, factories expanding, expectations rising, and a tariff regime that moved twice in one month. Every one of those is true at the same time.

Why the headline number is the wrong input

Faced with contradiction, most annual planning processes do the same thing. Leadership picks a growth assumption, the assumption becomes a number, the number cascades into quotas, headcount and comp, and by November the entire organization is executing against a macro judgment that was made in one meeting by people who are not economists.

The problem is not that the judgment is wrong. It might be right. The problem is that it is now invisible. It has been converted into a quota, and quotas do not carry their assumptions with them.

When conditions move, and they will, nobody can tell which part of the plan was a commitment and which part was a guess. The plan does not adapt. It gets missed, and then it gets renegotiated under pressure, which is the most expensive moment to make a decision.

A mixed macro signal is not a reason to plan less. It is a reason to plan differently: fewer assumptions, made explicit, each attached to something observable.

Three questions that turn macro data into a revenue decision

Most macroeconomic news is irrelevant to a specific company’s revenue plan. The filter is short.

For any macro data point, ask:

1. Does this change what our customers can afford?
2. Does this change what it costs us to serve them?
3. Does this change how long they take to decide?

If a data point touches none of the three, it is context, not input. It belongs in the board narrative, not in the plan.

If it touches one, it belongs in the plan as a named assumption with a trigger.

The third question is the one most often skipped, and it is where the current environment does its real damage. Rising cost of capital does not usually reduce demand. It lengthens approval chains and pulls the CFO into deals that a VP used to sign. Nothing about the buyer’s need changed. Everything about the cycle did, and a plan built on last year’s cycle length will miss on timing while the demand assumption was correct all along.

What July’s data actually means for a plan

The pattern across the table is worth naming. The aggregate number is almost never the one that matters to you. In every row, the useful figure is one level below the headline, and it is usually available.

The assumptions that are not cyclical

Everything above concerns signals that move within a year. Inflation, cycle length, approval friction, tariffs. Those belong in the trigger table because they can flip inside a planning horizon.

A second category does not move that way, and it gets left out of annual planning entirely because the annual cadence is the wrong instrument for it.

The McKinsey Global Institute published a study of global investment patterns in June 2026, built on national statistical agency data alongside Eurostat, the IMF, the OECD, UNCTAD and S&P Global Market Intelligence. Three findings from it matter to anyone whose customers build things.

Investment is diverging sharply by region, not cyclically but structurally. Europe carries an annual investment gap the study puts at 800 billion. China is adding roughly three times more productive assets each year than Europe and the United States combined, though its capital returns run about 40 percent lower.

Cost positions differ by more than most plans assume. Levelized costs in Europe and the United States are at least 50 percent higher than in the countries currently attracting the most investment. In manufacturing the gap against China is around 50 percent, driven mainly by wages not matched by productivity. In research and development the gap is closer to 300 percent, with time to market a significant driver.

Policy is a cost input, not background. Implicit subsidies differ by as much as eight times between regions, and exchange rate effects widen the gap further.

Here is why that belongs in a revenue conversation rather than a strategy offsite.

If you sell into industrial capacity, where that capacity gets built is your addressable market three years out. Equipment, components, industrial software, engineering services, maintenance, logistics, financing. Your pipeline in 2029 is a function of who is pouring concrete in 2026.

Most B2B revenue plans forecast next year’s number from last year’s pipeline, segmented by geography. Very few forecast from where their customers are actually deploying capital. Those two produce the same answer for as long as the pattern holds, and they diverge quietly once it stops.

That is not a trigger, because it will not flip inside a quarter. It is a standing assumption, and it wants a different treatment: reviewed annually rather than monthly, owned at the executive level rather than by RevOps, and written down explicitly so that when the coverage model is next redesigned, somebody can check whether it still holds.

The practical version is one line in the plan document. Where do we assume our customers will be investing over the next three years, and what would tell us that is changing? If nobody can answer it, the geographic shape of your coverage is inherited rather than chosen.

Plan the triggers, not the number

The practical alternative to a single growth assumption is short.

Name the three to five assumptions the plan actually rests on. Not twenty. The ones where being wrong changes what you would do. For most B2B companies entering 2027 those will be some combination of: demand in the top two segments, average cycle length, realized price, cost to serve, and churn or renewal rate.

Give each one an observable indicator. Not a feeling and not a quarterly review. Something a named person can look at on a specific day: your own cycle length by segment, your own win rate at the CFO approval stage, your own realized price versus list, your own freight cost per unit shipped.

Pre-agree the response. This is the part organizations skip, and it is the part that makes the whole thing work. Decide now, while nobody is under pressure, what happens if cycle length extends by 20%. Reallocate coverage? Change the discount authority? Pull forward the renewal motion? A decision made in September at a whiteboard is a better decision than the same one made in March against a miss.

Review the assumptions on a fixed cadence, separately from the pipeline review. Thirty minutes a month, looking only at whether the assumptions still hold. If assumption review happens inside the pipeline meeting, it never happens, because the pipeline is louder.

The output is not a more accurate plan. Nobody can produce that from this data. The output is a plan that tells you, early and specifically, which part of it broke.

Five ways this goes wrong

1. Planning off the headline. GDP and CPI are averages across an economy you do not sell to. Every row of the table above is a case where the aggregate points one way and the relevant number points another.
2. One number, no triggers. A plan with a growth target and no named indicators cannot tell you it is failing until the quarter closes.
3. Letting the macro debate replace the segment analysis. Two hours arguing about whether a slowdown is coming, zero hours on which of your segments actually decelerated last quarter. Your own data is more predictive of your own revenue than any national statistic.
4. Treating a mixed signal as a reason to wait. Ambiguity is the normal condition. A plan built to adapt is available now; certainty is not coming before you have to commit headcount.
5. Adjusting demand when the problem is cycle length. The most common misdiagnosis in a tightening capital environment. Demand held, approval got harder, and the company cut the forecast and the coverage that would have carried the deals through.

The next two weeks

Planning cycles for 2027 open in most B2B companies within the next few weeks, which makes this a short and specific window.

Before the first planning meeting, get three things on one page: your own cycle length by segment for the last four quarters, your own realized price versus list, and your own cost to serve broken out far enough to see whether energy and freight moved it. Those three lines will do more for the plan than any macro briefing, including this one.

Then bring the macro in as a constraint on the assumptions rather than as the source of the number. The economy is an input to your plan. It is not your plan.

Frequently asked questions

How should macroeconomic data be used in a revenue plan?

As a constraint on assumptions, not as the source of the growth number. Filter every data point with three questions: does it change what customers can afford, what it costs to serve them, or how long they take to decide. Data that touches none of the three is context for the board narrative, not an input to the plan.

Is inflation moderating or not?

Both, depending on your cost base. US headline CPI rose 3.5% over the twelve months to June 2026 and core CPI 2.6%, which reads as moderation. Over the same period energy rose 15.7% and gasoline 26.7%. A business with significant freight or fuel exposure did not experience moderating inflation, and should not price as though it did.

Should we plan conservatively given the slowdown?

That question skips a step. US GDP did slow to 1.5% annualized in Q2 from 2.1%, but manufacturing PMI stayed at 53.9, in expansion. The aggregate and the sector disagree. Look at the leading indicator for your own segment before deciding the posture, because “conservative” applied to a segment that is growing costs as much as optimism applied to one that is not.

What is the single most common planning error in this environment?

Cutting the demand assumption when the actual change is cycle length. Rising cost of capital adds approvers and moves decisions up the org chart without reducing the underlying need. Companies that misdiagnose this cut coverage and forecast, and then miss deals that would have closed one quarter later.

Should long-term investment trends be in an annual revenue plan?

Not as triggers, because they do not flip inside a quarter. As one written standing assumption, reviewed annually and owned at executive level. If you sell into industrial capacity, where your customers deploy capital determines your addressable market roughly three years out, and McKinsey Global Institute research published in June 2026 shows those patterns diverging sharply by region rather than moving together. Most plans inherit their geographic shape from last year’s pipeline rather than choosing it.

How many assumptions should a revenue plan have?

Three to five that are named, documented and tracked. The test for inclusion is whether being wrong about it would change what you do. Assumptions that fail that test add process without adding adaptability.

Sources

1. US Bureau of Labor Statistics, Consumer Price Index, June 2026, released July 14, 2026. bls.gov
2. US Bureau of Economic Analysis, Gross Domestic Product, Second Quarter 2026 (Advance Estimate). bea.gov
3. Arvind Govindarajan, Shubham Singhal, Sven Smit, with Jeffrey Condon and Krzysztof Kwiatkowski, “Global Economics Intelligence executive summary, July 2026,” McKinsey and Company, August 25, 2026. mckinsey.com
4. Global Supply Chain Pressure Index, Federal Reserve Bank of New York, as reported in McKinsey Global Economics Intelligence, July 2026.
5. Anna Kortis, Jan Mischke, Chris Bradley, Sylvain Johansson, Shubham Singhal, Olivier Bus and Camillo Lamanna, “Catalyzing competitiveness: Where investment happens and why,” McKinsey Global Institute, June 30, 2026. Exhibits draw on national statistical agencies, Eurostat, the IMF, the OECD, UNCTAD and S&P Global Market Intelligence. mckinsey.com

About the author

Andre Magrini is a chief revenue officer and fractional CRO based in the Greater Chicago Area. He led North America for Ag Growth International and, as general manager in Brazil, scaled an operation more than 4x in three years. He served as Vice President of the Marketing and Communications Committee at the American Feed Industry Association, and is the author of seven books, including five on sales, marketing analytics and corporate governance.