The future of analytics is a metrics-first operating system. Let’s explore the current state of analytics and discuss three macro trends driving this inevitable evolution.

Three Macro Trends:

1. Sophisticated and Standardized Data Modeling

Data modeling is now widely accepted and implemented by data teams of all sizes. These models are increasingly capturing the nuances of varied business models.

  • From the early days of Kimball to today, powered by advanced data modeling and management tools, practitioners are coalescing around concepts like time grains, entities, dimensions, attributes and metrics modeled on top of a data platform.
  • Compared to even 7-8 years ago, we’ve made significant strides in tailoring these concepts for various business types—consumer, enterprise, and marketplace—across different usage and monetization models.
  • We’re now proficient in standardizing metrics and calculations for specific domains, such as sales funnels, lifetime value calculations for marketing, cohort tracking for finance, and usage and retention models for product teams.

The architecture of data production is more robust than ever as data and analytics engineers refine their practices. Now, let’s look at the consumption side.

2. Repeatable Analytics Workflows

Analytics workflows are becoming repeatable, and are centered around metrics:

  • Periodic business reviews and board meetings demand consistent metrics root-cause analysis, including variance analysis against budgets or plans.
  • Business initiatives, launches, and experiments require expedient analysis to extract actionable insights and drive further iterations. Experimentation is becoming a core workflow within organizations.
  • Organizations need to align on strategy, formulate hypotheses, and set metric targets to monitor progress effectively.

3. Limitations of Scaling Data Teams

The cold reality is that data teams are never going to be big enough. We are not going to scale data consumption by adding more folks into the data team. This has become even more apparent as investment levels have waned over the past three years.

Combining these insights:

  1. The increasing standardization of data models across various business models
  2. The secularization and rise of repeatable workflows centered around metrics.
  3. The need to maximize data team leverage

It is clear that a metrics-first, low to no code operating system is the future. Such a system will provide immense leverage for data teams, while empowering executives and operators.

This shift towards a metrics-first operating system represents the next evolution in analytics, driving both operational efficiency and strategic agility.

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