A brief history of the EPM marketplace

To fully understand the opportunities in EPM today, it’s important to understand how the EPM market has evolved from the beginning.

Where we begun

The first days of digital business operations relied on a combination of spreadsheets and online transaction processing (OLTP) databases. Spreadsheets offer flexibility and have a low learning curve due to their prevalence, but can be tricky to manage at scale, and across teams.

OLTP databases are ideal for frequent transactional operations (e.g. insert, update and delete operations), and they are enormously flexible for storing data in a way that naturally mirrors the real-life business using them. 

However, early versions of these databases lacked the robustness required for more complex analysis that would require the aggregation of data across multiple tables and datasets, and performance for processing these aggregations, as well as performing data updates, was untenable as data volumes grew.

Aggregation means summarizing detailed data into higher-level metrics. Instead of looking at every individual data point (like each sale or transaction), aggregation lets you group and calculate values across a set of records.

Imagine you have sales data like this:

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Aggregating this by Region might look like:

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The introduction of OLAP (1980-)

But with the introduction of online analytical processing (OLAP) databases around the early 1980s, the EPM market was transformed. In OLAP, data is pre-aggregated into ‘cubes’ so that analysis of data across multiple predetermined dimensions (e.g. product by sales by region) is performant at scale.

In essence, once data is loaded into the system, the system precomputes a large number of aggregations on it. That means when users ask, the system already ‘knows’ the answer.

This drove transformation in the EPM market: beginning with the likes of Oracle Hyperion and Cognos PowerPlay, the industry saw a surge of products such as Applix TM1, Adaytum and OutlookSoft. These products aimed to combine the user-friendly spreadsheet interface of Excel with the power and performance demanded by the market.

To this day, the majority of EPM vendors build their software on OLAP technology.

While some of these earlier names may no longer be familiar players, the foundational technologies remain in place within some of the largest EPM providers even now. Mergers and acquisitions during the early 2000s saw Applix TM1, Adaytum and Cognos become the basis of IBM Planning Analytics, OutlookSoft was rolled into SAP’s BPC product, and Arbor Software’s Essbase merged with Hyperion in 1998 to cement it as a cornerstone of the EPM industry ahead of its acquisition by Oracle in 2007.

Moving into the cloud (2000-2010)

These founding players broadened the capabilities of EPM by embedding their new EPM technologies within their wider ecosystems. Deep integration with databases, ERP tooling, and other products gave these companies a stronghold in the enterprise EPM market.

However, the emergence of cloud-native technologies necessitated further development to address market demand. Historically, EPM and other enterprise tooling were hosted on-premise, requiring investment in infrastructure and teams to operate and maintain systems. Scalability was a costly limiting factor for large enterprises, and insurmountable for smaller enterprises.

It was at this point that the next generation of EPM players entered the market to take advantage of the increased demand for cloud-native EPM solutions. With the rise of cloud computing platforms such as AWS and Microsoft Azure, businesses had begun to see the benefits of SaaS tools that were cheaper to maintain, which facilitated collaboration for geographically dispersed teams. Early players during this phase included Anaplan, Host Analytics (now Planful) and Adaptive Insights (now Workday Adaptive Planning).

Extending beyond finance (2010-2020)

As the EPM market continued to evolve in parallel to the connection of disparately located teams, the concept of integrated business planning (IBP) became an increasingly appealing goal. IBP is a natural target for any business seeking to connect siloed business units and their data together so the impact of decisions can be assessed and understood across every facet of the organization. This evolved into various terms, including ‘connected planning’ and extended planning and analysis (xP&A), but the core aim is to ensure that teams across the enterprise are aligned and working together to make cohesive plans.

Typically this is achieved with a ‘hub and spoke’ style operating model for enterprise planning, with data deployed from a central store to each business unit for use within their planning processes, and data aggregation performed by finance and leadership teams for a comprehensive view of the business at fixed points in time.

This approach is great in principle, but comes with some challenges and limitations we’ll explore soon.

What’s next?

That’s where the market was at before Pigment entered. In the next article, I’ll explore the secret sauce that’s enabled us to change things, and where we’re going next.