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Steps Every Business Must Take to Digitize and Survive

Mark Banfield
LogicMonitor

In 2020, our society is undergoing massive upheaval and businesses are being forced to adapt on the fly. During this period of crisis, the companies that make the necessary adjustments the quickest will succeed. We're already seeing it happen in the accelerated push toward digitization, as companies that smoothly digitize their customer experiences move forward and those that don't get left behind.


Of course, digitization is not new, but rather an evergreen topic of discussion at board and executive-level meetings. What is new, however, is the speed at which the gap between the digital haves and have-nots is widening amid the COVID-19 crisis.

The global pandemic has magnified the urgency of digitization, and it has exposed the businesses that are still struggling to manage even the most basic of digital interactions with their customers and employees. Organizations everywhere are under enormous pressure to accelerate digital transformation, expand cloud services and do whatever else it takes to stay connected with customers and workers.

What's striking, however, is that only 39% of IT professionals have a high level of confidence in their organization's ability to seamlessly deliver digital services in the midst of a crisis, according to a new survey we conducted here at LogicMonitor.

I've experienced this disconnect firsthand in my interactions with a number of businesses. For instance, I recently bought a house overseas and the real estate agent wanted to fax me the closing documents. When I told the agent I didn't have a fax machine (who has a fax machine anymore?), he offered to mail them to me so I could sign and send back to him. Who knows how long that would have taken? Fax machines are a relic of the past when services like DocuSign exist, which digitize transactions like these for an expedited and much better customer experience.

The reality is that there are millions of companies today that have not yet created digital experiences for their customers and, as a result, are still mired in manual processes that hamper the customer experience and put the entire business at risk. Here are just a few things every business can do to digitize operations and ultimately stay relevant in the market.

Create a Strategic Plan for Digitizing the Customer and Employee Experience

Start by putting together a game plan and identifying the processes within your business that can be digitized.

If you're a real estate agent, for example, how can you digitize the process of buying or selling a house?

If you're a medical office, how can you better deliver remote care?

If you're a government office, instead of relying on in-person services and paper forms, how can you deliver information and services to your customers quickly while they remain within the comfort of their own homes?

Basically, any service you offer that can be digitized and moved to the cloud should be digitized and moved to the cloud. Especially these days, when a limited number of employees are going into the office and on-premises technologies are likely collecting dust.

The good news is that many businesses are now getting the message and making the appropriate adjustments. Our survey found that organizations are increasingly embracing the cloud, with 87% of IT leaders stating that the COVID-19 pandemic and the need to work remotely has accelerated their cloud migrations.

Embrace Intelligent Automation

Of course, issues with digital experiences will invariably arise. When they do, companies need to have the visibility and capability to quickly identify the root of the problem and fix it. These days, companies are aggressively investing in artificial intelligence (AI) and other next-generation technologies to identify and resolve technical issues effectively and automatically, with minimal human intervention.

That's probably why IT leaders progressively believe that greater automation is the key to maintaining business continuity in the face of a crisis. According to our survey, 74% of IT leaders employ intelligent systems like AI and machine learning to provide insight into their IT infrastructure. Additionally, 93% say automation is essential because it allows their IT teams to focus on strategic initiatives and operate more effectively — all of which are critical in a time of crisis.

Specifically, AI can serve as an early-warning system, automatically piecing together patterns and trends to detect red flags and nip any emerging issues in the bud. A monitoring system powered by AI can help prevent outages, save time and money, provide greater insight into user behavior, and deliver the digital experiences customers expect.

No business today is complete without a digitization strategy. The bottom line is that every business must learn to ride the wave of digital change or risk being swept away by it.

Mark Banfield is CRO at LogicMonitor

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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 ...

Steps Every Business Must Take to Digitize and Survive

Mark Banfield
LogicMonitor

In 2020, our society is undergoing massive upheaval and businesses are being forced to adapt on the fly. During this period of crisis, the companies that make the necessary adjustments the quickest will succeed. We're already seeing it happen in the accelerated push toward digitization, as companies that smoothly digitize their customer experiences move forward and those that don't get left behind.


Of course, digitization is not new, but rather an evergreen topic of discussion at board and executive-level meetings. What is new, however, is the speed at which the gap between the digital haves and have-nots is widening amid the COVID-19 crisis.

The global pandemic has magnified the urgency of digitization, and it has exposed the businesses that are still struggling to manage even the most basic of digital interactions with their customers and employees. Organizations everywhere are under enormous pressure to accelerate digital transformation, expand cloud services and do whatever else it takes to stay connected with customers and workers.

What's striking, however, is that only 39% of IT professionals have a high level of confidence in their organization's ability to seamlessly deliver digital services in the midst of a crisis, according to a new survey we conducted here at LogicMonitor.

I've experienced this disconnect firsthand in my interactions with a number of businesses. For instance, I recently bought a house overseas and the real estate agent wanted to fax me the closing documents. When I told the agent I didn't have a fax machine (who has a fax machine anymore?), he offered to mail them to me so I could sign and send back to him. Who knows how long that would have taken? Fax machines are a relic of the past when services like DocuSign exist, which digitize transactions like these for an expedited and much better customer experience.

The reality is that there are millions of companies today that have not yet created digital experiences for their customers and, as a result, are still mired in manual processes that hamper the customer experience and put the entire business at risk. Here are just a few things every business can do to digitize operations and ultimately stay relevant in the market.

Create a Strategic Plan for Digitizing the Customer and Employee Experience

Start by putting together a game plan and identifying the processes within your business that can be digitized.

If you're a real estate agent, for example, how can you digitize the process of buying or selling a house?

If you're a medical office, how can you better deliver remote care?

If you're a government office, instead of relying on in-person services and paper forms, how can you deliver information and services to your customers quickly while they remain within the comfort of their own homes?

Basically, any service you offer that can be digitized and moved to the cloud should be digitized and moved to the cloud. Especially these days, when a limited number of employees are going into the office and on-premises technologies are likely collecting dust.

The good news is that many businesses are now getting the message and making the appropriate adjustments. Our survey found that organizations are increasingly embracing the cloud, with 87% of IT leaders stating that the COVID-19 pandemic and the need to work remotely has accelerated their cloud migrations.

Embrace Intelligent Automation

Of course, issues with digital experiences will invariably arise. When they do, companies need to have the visibility and capability to quickly identify the root of the problem and fix it. These days, companies are aggressively investing in artificial intelligence (AI) and other next-generation technologies to identify and resolve technical issues effectively and automatically, with minimal human intervention.

That's probably why IT leaders progressively believe that greater automation is the key to maintaining business continuity in the face of a crisis. According to our survey, 74% of IT leaders employ intelligent systems like AI and machine learning to provide insight into their IT infrastructure. Additionally, 93% say automation is essential because it allows their IT teams to focus on strategic initiatives and operate more effectively — all of which are critical in a time of crisis.

Specifically, AI can serve as an early-warning system, automatically piecing together patterns and trends to detect red flags and nip any emerging issues in the bud. A monitoring system powered by AI can help prevent outages, save time and money, provide greater insight into user behavior, and deliver the digital experiences customers expect.

No business today is complete without a digitization strategy. The bottom line is that every business must learn to ride the wave of digital change or risk being swept away by it.

Mark Banfield is CRO at LogicMonitor

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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 ...