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The Great SaaS Hangover (and the Cure Nobody Is Talking About)

Chris Webber
Formstack

We've all been there.

The morning-after fog. The pounding headache. The light sensitivity. The creeping existential dread.

You had a few too many last night.

It's not entirely your fault. The playlist was amazing. The dance floor was hopping. The drinks were flowing. It happens to the best of us.

What follows varies from person to person — and culture to culture. Reddit threads offer thousands of post-party remedies: a scalding hot shower, a punishing gym session, a greasy breakfast, or — for the bold — the infamous "hair of the dog." Some of these might help. Most don't. At the end of the day, everyone comes to the same conclusion: the only surefire way to avoid a hangover is to drink less in the first place.

And that brings us to the SaaS industry.

The SaaS Party That Went Too Hard

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality.

Gartner estimated global SaaS spending hit $157 billion in 2020, and it hasn't slowed much since. Companies layered tools upon tools, often with overlapping functionalities, all in the name of agility and speed.

But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill.

Welcome to the Great SaaS Hangover.

What Is a SaaS Hangover?

A SaaS hangover is the result of years of unchecked software adoption. It's marked by:

  • Redundant tools doing the same job in slightly different ways.
  • Ballooning software costs where every employee is another $$$ per month.
  • Disjointed user experiences that frustrate employees and reduce productivity.
  • Security and compliance risks from managing too many vendors and endpoints.

In fact, a 2023 Productiv report found that companies use an average of 371 SaaS apps, yet only 47% are actively used in any given 30-day period. That's like stocking your fridge with five brands of orange juice and drinking just one.

The Cure: SaaS Consolidation Through Horizontal Platforms

Here's the good news: unlike a gin-fueled hangover, the SaaS hangover does have a cure — and it's surprisingly simple: Shrink your stack. Consolidate your spend. Invest in platforms, not point solutions.

The smartest companies today are shifting toward horizontal platforms — tools that solve broad business problems across departments, rather than hyper-specialized point solutions. Think Notion over five separate productivity apps. Think HubSpot over a scattered mix of CRM, email, and marketing tools. Think Microsoft 365, not a patchwork of document editors, cloud drives, and meeting apps.

Why It Works

  • Lower cost: Bundled pricing often beats à la carte tools.
  • Simpler onboarding: Fewer tools means faster adoption and less training.
  • Better integration: Native connections across features reduce data silos.
  • Improved visibility: Centralized platforms offer unified reporting and analytics.
  • Stronger security: One platform means fewer vendors to vet and monitor.

And here's the kicker: consolidation doesn't mean compromise. Modern horizontal platforms are more robust than ever, often outperforming niche competitors while offering broader utility.

You Wouldn't Build a Sandwich This Way

Let's end with a metaphor as simple as it is relatable: you wouldn't go to three different sandwich shops to assemble your lunch. One for the bread, one for the meat, one for the cheese? Ridiculous. You go to one deli. You get the combo. It's faster, cheaper, and it just makes sense.

So why do we treat our software stack any differently?

It's time to sober up.

The SaaS party was fun while it lasted — but now, it's time to clean house and consolidate. Your budget, your team, and your sanity will thank you.

Chris Webber is Director of Engineering at Formstack

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

The Great SaaS Hangover (and the Cure Nobody Is Talking About)

Chris Webber
Formstack

We've all been there.

The morning-after fog. The pounding headache. The light sensitivity. The creeping existential dread.

You had a few too many last night.

It's not entirely your fault. The playlist was amazing. The dance floor was hopping. The drinks were flowing. It happens to the best of us.

What follows varies from person to person — and culture to culture. Reddit threads offer thousands of post-party remedies: a scalding hot shower, a punishing gym session, a greasy breakfast, or — for the bold — the infamous "hair of the dog." Some of these might help. Most don't. At the end of the day, everyone comes to the same conclusion: the only surefire way to avoid a hangover is to drink less in the first place.

And that brings us to the SaaS industry.

The SaaS Party That Went Too Hard

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality.

Gartner estimated global SaaS spending hit $157 billion in 2020, and it hasn't slowed much since. Companies layered tools upon tools, often with overlapping functionalities, all in the name of agility and speed.

But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill.

Welcome to the Great SaaS Hangover.

What Is a SaaS Hangover?

A SaaS hangover is the result of years of unchecked software adoption. It's marked by:

  • Redundant tools doing the same job in slightly different ways.
  • Ballooning software costs where every employee is another $$$ per month.
  • Disjointed user experiences that frustrate employees and reduce productivity.
  • Security and compliance risks from managing too many vendors and endpoints.

In fact, a 2023 Productiv report found that companies use an average of 371 SaaS apps, yet only 47% are actively used in any given 30-day period. That's like stocking your fridge with five brands of orange juice and drinking just one.

The Cure: SaaS Consolidation Through Horizontal Platforms

Here's the good news: unlike a gin-fueled hangover, the SaaS hangover does have a cure — and it's surprisingly simple: Shrink your stack. Consolidate your spend. Invest in platforms, not point solutions.

The smartest companies today are shifting toward horizontal platforms — tools that solve broad business problems across departments, rather than hyper-specialized point solutions. Think Notion over five separate productivity apps. Think HubSpot over a scattered mix of CRM, email, and marketing tools. Think Microsoft 365, not a patchwork of document editors, cloud drives, and meeting apps.

Why It Works

  • Lower cost: Bundled pricing often beats à la carte tools.
  • Simpler onboarding: Fewer tools means faster adoption and less training.
  • Better integration: Native connections across features reduce data silos.
  • Improved visibility: Centralized platforms offer unified reporting and analytics.
  • Stronger security: One platform means fewer vendors to vet and monitor.

And here's the kicker: consolidation doesn't mean compromise. Modern horizontal platforms are more robust than ever, often outperforming niche competitors while offering broader utility.

You Wouldn't Build a Sandwich This Way

Let's end with a metaphor as simple as it is relatable: you wouldn't go to three different sandwich shops to assemble your lunch. One for the bread, one for the meat, one for the cheese? Ridiculous. You go to one deli. You get the combo. It's faster, cheaper, and it just makes sense.

So why do we treat our software stack any differently?

It's time to sober up.

The SaaS party was fun while it lasted — but now, it's time to clean house and consolidate. Your budget, your team, and your sanity will thank you.

Chris Webber is Director of Engineering at Formstack

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...