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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

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Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

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Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

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

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...