A CEO's Guide to Leading Indicators: What to Measure Before the Results Are In.

Hannah Wilner
Jul 15
7 min read

Most companies measure outcomes. High-performing ones measure what drives them.

Last month I argued that strategic plans fail not because the goals were wrong, but because the infrastructure to execute them was never built. One of the most commonly misunderstood and most consistently absent of the three components listed is leading indicators. This post goes deeper on what they are, how to identify the right ones, and what it takes to make them work.

Most executive teams I work with share the same problem: they aspire for growth, set BHAG goals, and they track financials. Unfortunately, this is not a reliable plan to ensure those goals are achieved. By the time quarterly financial results confirm something went wrong, the opportunity to correct course has already passed.

This is the core failure of measurement systems that rely exclusively on financial outcomes. Revenue, profit margin, and sales are important; however they are backward-looking. They tell you what happened and nothing about what is about to happen.

The solution is not more metrics. It is the right metrics, structured in a deliberate cause-and-effect sequence. That sequence begins with leading indicators.

Of the three components of execution infrastructure; leading indicators, cascading goals, and accountability cadences, this post focuses on the first. It covers what leading indicators are, how to identify the ones that matter for your business, and which show up consistently across high-performing SMBs, with specific guidance for service-based firms. Cascading goals and accountability cadences are the subject of future posts.

Leading vs. Lagging: The Distinction That Changes Everything

A lagging indicator measures an outcome after it has occurred. A leading indicator measures an activity or condition that predicts that outcome before it occurs.

"Leading KPIs help you influence future outcomes. They are the only ones you can act on in real time."

The distinction seems simple, but the implications are significant. If your only measurement infrastructure is built around lagging indicators (revenue, net profit, customer count, etc.) you are operating reactively. You’re essentially steering the ship by looking at the wake.

The right question is not: "How did we do?" It is: "What are the conditions right now that determine how we will do 90 days from now?"

This is the 90-day window: if your first signal arrives in the quarterly financials, the window to course-correct has already closed. Reframing your data visibility from what happened to what is about to happen is the foundation of a measurement infrastructure built for execution, not just reporting.

Founded in Research: This Isn't Just Theory

The most empirically grounded framework for goal attainment through leading and lagging indicators is the Balanced Scorecard (BSC), introduced by Robert S. Kaplan and David P. Norton in the January–February 1992 issue of Harvard Business Review.¹ Their central argument: financial data alone cannot predict future performance. What organizations need is a broader measurement architecture that captures the drivers of financial outcomes, not just the outcomes themselves.

Kaplan and Norton organized those drivers across four perspectives in an explicit causal chain:

Learning & Growth — employee capability, culture, and systems
Internal Processes — operational quality and delivery efficiency
Customer — satisfaction, loyalty, and market position
Financial — revenue, margin, and growth

The causal logic runs downhill: investment in learning and growth drives process quality; process quality drives customer outcomes; customer outcomes drive financial results. Each tier is a leading indicator for the tier below it.

A 2025 meta-analysis published in SAGE Journals synthesizing BSC research across organizations confirmed this structure empirically: learning and growth had a strong positive effect on overall performance, and internal process improvements were closely linked to customer satisfaction, which in turn drove financial health.²

This is not consulting theory. It is a tested causal model with decades of application data behind it. Your measurement infrastructure should be built on the same logic.

How to Identify the Right Leading Indicators for Your Business

Before reaching for a list of metrics, there is an initial step most companies skip: clearly defining the strategic outcomes they are trying to produce.

The correct sequence is:

Define the strategic outcome (the lagging indicator or result you want)
Identify the behavioral or operational drivers of that outcome
Confirm that each driver is controllable and temporally prior to the outcome
Verify that the metric can be measured before the outcome changes

A critical diagnostic: if you cannot act on a metric before the outcome shifts, it is not functioning as a leading indicator. It is in fact lagging while operating under an incorrect label.

The other common failure is measuring what is easy to track rather than what actually predicts results. Social media follower counts. Email open rates. Headcount added. These are activity metrics, not predictive indicators. An indicator is only "leading" if there is a documented, testable relationship between the driver and the outcome.

Once you have mapped your strategic outcomes to the operational drivers, you can select 2–3 leading indicators per outcome. Most executive teams need no more than 7–10 company-level indicators total.³ Beyond that, it digresses from a management system into a reporting system.

Universal Leading Indicators: What Crosses All Industries

The following indicators appear consistently across SMBs regardless of sector. These are validated through the BSC research base and practitioner literature. They are organized by the strategic outcome they predict.

Revenue & Pipeline Health

Sales pipeline value (weighted and unweighted) — predicts revenue 60–90 days out
Pipeline coverage ratio — pipeline value relative to near-term bookings target; signals whether enough opportunity exists to hit revenue goals
Proposal or quote win rate — effectiveness of the sales process and competitive positioning
Average sales cycle length — elongating cycles predict revenue delays before they appear in bookings

Customer Health

Net Promoter Score (NPS) or Customer Satisfaction Score (CSAT) — predicts retention volume and referral rate
Client concentration — percentage of revenue from top 1–3 clients; high-performing firms recognize the risk when one client exceeds 15–20% of total revenue
Repeat and expansion revenue rate — signals relationship health and cross-sell effectiveness

People and Capacity

Employee engagement score (eNPS) — predicts voluntary turnover (aka attrition); voluntary turnover predicts capacity and delivery risk
Time-to-fill open roles — signals capacity constraints 60–90 days before they affect delivery
Training hours per employee — leading indicator for capability development and service quality

Financial Efficiency

Days Sales Outstanding (DSO) — predicts cash position; a rising DSO signals collection problems before they reach the bank account
Gross margin by service line — early signal of pricing and delivery model health
Operating expense ratio — early warning on cost structure before it compresses net margin

Service Business Leading Indicators: Where the Specificity Matters

Professional and knowledge-based service firms such as consulting, law, HR, and engineering have a distinct set of leading indicators. The information provided is anchored by the SPI Research 2026 Professional Services Maturity Benchmark, a 19th-annual study covering 509 organizations representing over 245,000 consultants globally.⁴

Capacity and Utilization

Billable utilization, which is the percentage of available consultant hours billed to clients, is the most structurally important metric in a services business. The 2026 SPI Benchmark reported the industry average at 66.4%, the lowest in the benchmark's 19-year history. Notably, firms added headcount but failed to convert that capacity into billable hours. The capacity was there but the conversion was not.⁴ Maintaining this gap in a 20-person firm represents hundreds of thousands of dollars in recoverable revenue.

Scheduled billable hours (forward-looking) — tells you how busy your team is planned to be before the month starts, enabling proactive capacity adjustment
Resource allocation accuracy — the gap between planned and actual staffing assignments; gaps exceeding 10–15% consistently indicate forecasting problems that will surface in margins later⁴
Bench time — unallocated billable staff is a leading indicator of margin compression

Revenue Quality

Realization rate — billable hours invoiced versus billable hours worked; low realization reveals scope, pricing, or write-off problems that erode margin before they appear in P&L
Revenue per billable consultant — the 2026 SPI benchmark reports an industry average of approximately $204K, with top firms exceeding $270K⁴
Backlog value — confirmed, signed contracts not yet delivered; predicts near-term revenue regardless of pipeline activity

Delivery Health

Client satisfaction measured mid-engagement, not just at project close, catches delivery problems and potential payment delays while correction is still possible
On-time delivery rate impacts billing and revenue, early identification of delayed projects and missed deadlines help forecast accuracy
Scope change order rate is also an early indicator of project margin erosion and relationship strain

Turning the List Into a System

A list of indicators is not a measurement infrastructure. What turns indicators into a management tool is the operating system built around them:

Each indicator requires a single named owner — not a team, not a department
Targets are set in advance, not retroactively
A review cadence is established that corresponds to the indicator's time horizon (weekly for pipeline; monthly for utilization; quarterly for NPS trends)
Decisions are documented when indicators trigger action which builds institutional knowledge about what works

The most common failure I see in strategic planning engagements is not that companies choose the wrong metrics. It is that they choose reasonable metrics without an operating system to support them. The dashboard gets built but the review cadence never materializes.

The difference between a measurement infrastructure and a reporting function is whether the data produces action.

This matters for reasons that go beyond process design. The research on intrinsic motivation — specifically Deci and Ryan’s self-determination theory — identifies competence, a felt sense of progress and mastery, as a primary driver of sustained effort. When people cannot see the effect of their work, they stop trying to change it. Leading indicators create the visible feedback necessary for ongoing motivation. The infrastructure question is also a behavioral one.

High-performing firms treat measurement as a management discipline, not a reporting function. According to the 2026 SPI Benchmark, the single capability that most consistently separates high-performance organizations from the rest is integrated, real-time visibility across delivery, resources, and financials with an operating cadence that translate that visibility into decisions.⁴

The Bottom Line

Most strategic plans don’t fail because the goals were wrong, it’s typically because the measurement infrastructure was never built to support execution. Leading indicators are the mechanism that connects today's activities to tomorrow's results. Without them, strategy is aspiration — a document reviewed once a year that has no relationship to what people actually do.

If your current measurement infrastructure is built entirely around financial outcomes, the first step is straightforward: for each strategic goal, identify one or two upstream drivers that you can observe and act on before the outcome materializes. Start there.

Build the review cadence. Assign ownership. The list in this post is a starting point, what matters is the discipline you build around it.

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FOOTNOTES & CITATION STATUS

¹Kaplan, R.S. & Norton, D.P. (1992). "The Balanced Scorecard — Measures That Drive Performance." Harvard Business Review, 70(1), 71–79. URL: https://hbr.org/1992/01/the-balanced-scorecard-measures-that-drive-performance-2

²Liao, Y-K., Wang, S., Thinh, V.T., & Wu, W-Y. (2025). "An Investigation of Leading and Lagging Indicators for Balanced Scorecard: A Meta-Analytic Approach." SAGE Open.

³Kaplan, R.S. & Norton, D.P. (1996). The Balanced Scorecard: Translating Strategy into Action. Harvard Business School Press.

⁴Rocketlane and SPI Research / Service Performance Insight. (2026). 2026 Professional Services Maturity Benchmark™. Co-published with Rocketlane and TimeLog. URL for co-publisher summary: https://www.rocketlane.com/blogs/professional-services-maturity-index-2026