Use Growth Analytics to Surge Company Revenue

Research Shows What the Highest Growth Companies Do Differently

Highlights

  • Research shows that most companies do not have an active data and growth analytics strategy. However, the data also reveals that 81% of the highest growth companies did manage active and documented growth analytics strategies.
  • The research found that the three most effective business intelligence tools are predictive analytics, artificial intelligence and digital dashboards.
  • Only 19 percent of survey respondents reported using industry benchmarks as part of their business intelligence. However, their use was heavily skewed among performance archetypes. 83 percent of the highest growth companies reported using benchmarks.
Johnny Grow Revenue Growth Consulting

You can't manage what you can't measure. Perhaps that why the highest growth companies cited revenue growth analytics as a top driver for company expansion.

Research performed for the Business Growth Report found that the highest growth companies made extensive use of revenue growth analytics to develop business development plans, measure progress and swiftly intervene when revenue performance fell short of those plans.

The research survey posed questions to understand and measure how revenue analytics were designed, what tools are most effective and what barriers stand in the way of success. Below are four findings from the research.

1

A Data & Analytics Strategy Correlates to Accelerated Revenue

Only 24 percent of respondents advised they have an active and documented data and growth analytics strategy. While that figure is surprisingly low, what's less surprising is that the top 15% designated as the Best-in-Class performance archetype operated a strategy 121 percent more frequently than their lower performing peers.

Growth Analytics Strategy

The disproportionately higher adoption among the top performance archetype should not go unnoticed by others considering the use of decision support to scale revenue.

We know from three decades of helping clients grow their revenue that most companies are data rich and information poor. A strategy is the first step to fix that.

The strategy shows how to connect data, insights, actions and outcomes. What makes an analytics strategy different from a broader business strategy is the focus on how to convert customer data into revenue outcomes.

Even small improvements to an analytics strategy are shown to deliver significant financial impact.

2

The 3 Most Effective Tools

Survey participants were asked to rate the effectiveness of each type of growth analytic on a 10-point scale. For those tools rated above a score of 8 we asked why they were effective. For those scored below 7 we asked why they were ineffective.

The three most effective tools are shown below by performance archetype.

Growth Analytics Tools

Research shows the top 3 business intelligence tools to support company revenue growth are predictive analytics, artificial intelligence and digital dashboards.

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The data show that predictive analytics are the most valuable tool among the highest growth companies. However, it also shows the effectiveness among performance archetypes is significantly different.

Dashboards were cited as the most frequently used tool but not the most effective. Comments cited that dashboards were used for continuous and real-time revenue and performance management reporting.

Dashboards rated ineffective were described as all show and no go. They may have been visually appealing but failed to gain adoption as they didn't display information that helped the decision maker.

On the flip side, dashboards rated as effective were less about displaying figures and more about making the information actionable.

The five most effective ways to make data actionable are to make the metrics highly visual and interactive, align departmental metrics with the most important company outcomes, show Key Performance Indicators alongside budgets or industry benchmarks for context, allow the data to be interrogated and link the data findings to recommended actions.

The below dashboard was created for a client. It is an example of how to make data actionable. Negative variances are color coded, offer drill-down analysis and display links to a Sales Playbook for prescriptive recommendations to remedy each shortfall.

Sales Dashboard

Dashboards are particularly effective in identifying performance deviations in real-time. Variance alerts permit swift adjustments to head off problems before they happen or remedy performance shortfalls before they exacerbate.

3

Top Performers Use Industry Benchmarks

The use of industry benchmarks with growth analytics surfaced the single greatest disparity among the highest growth companies and all others.

Growth Analytics Benchmarks

Only 19 percent of respondents reported using industry benchmarks. However, while the highest growth companies are a small subset, 83 percent of that cohort reported using benchmarks.

Industry performance benchmarks show what good looks like. They bring context to revenue performance metrics.

Supplementing performance measures with industry benchmarks can quickly spot gaps or underperforming areas that offer the biggest financial uplift. Benchmarking can turn competitive knowledge into competitive advantage.

Sales Win Rate Benchmark

When managers have both visibility and measurability to the most significant gaps between their current state and where they want to be, they can employ an effective case for change and plot the most direct route to improvements.

And rather than guesswork or estimated ROI figures with questionable assumptions, forecasts built on benchmarks using industry data provide confidence in calculating pro forma revenue outcomes and setting realistic goals. The knowledge of what has worked for similar companies lowers risk and accelerates time to value.

4

The Top Barriers

We posed survey questions to measure the top challenges. The top three are shown below.

Top Growth Analytics Challenges

The data was interesting for two reasons.

First, the top three challenges incurred no significant differences among performance archetypes. They were all near equally challenging for the lowest and highest revenue growth companies. This suggests an ideal opportunity to mitigate these risks with technology growth best practices.

Second, all three challenges were data related. That reinforces that fact that accurate and complete data is a prerequisite to all forms of business intelligence.

A good technology strategy starts with data. And a significant portion of revenue performance data is related to customers. That creates a data quality challenge as customer data is a highly perishable asset. Unless managed with a CRM data quality program the data will deteriorate at about 2 percent per month. A data quality program ensures customer data is accurate and complete, secured and available to those who need it, and in compliance with company policy and regulatory requirements.