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IT Execs Struggling with Transition to Digital Business Model

Pete Goldin
APMdigest

IT and business professionals in the US and Europe understand the value of adopting a digital business model but struggle to find the best way to engineer it to deliver the greatest value to employees and customers, according to new research from Unisys Corporation.

The digital business model represents the convergence of social technology, cloud, mobility, data analytics and security to drive new business models and engage, enable and support an increasingly tech-savvy workforce and customer base. The IT infrastructure enabling digital business transformation must be flexible and scalable on demand.

The 188 respondents to the survey – conducted for Unisys by IDG Research – appreciate that digital business transformation provides the key to elevating levels of service to those demanding internal and external constituencies: 55 percent cite that service requirement as their key challenge for 2016.

In addition, nearly two-thirds (65 percent) of respondents consider it highly important for their organizations to modify technology, IT processes or IT resources over the next 12 months to implement digital business, focusing especially on five key priority areas: mobile application development, cloud deployment, social media, data analytics and security.

Yet 54 percent assess their organization's progress toward a digital-business model that delivers on user expectations as average or below average (32 and 22 percent, respectively), while 45 percent rate progress above average.

In addition, less than 20 percent of respondents who rate each of the five IT focus areas as critical or high priority for digital-business implementation report significant progress in any one area. Few indicate that their organization is ready to meet customer expectations over the next 12 months: only 41 percent indicate that their technology or infrastructure is prepared, while 40 percent and 39 percent, respectively, rate their IT skill sets and security/compliance strategies as adequate.

Respondents who consider each of the 5 IT initiatives as at least a moderate priority report the greatest progress in two key areas: 69 percent cite at least some progress in both mobile application development and cloud deployment, but cite less significant progress in social media, data analytics and security.

Making Progress

"Digital business can be a powerful force for enhanced productivity and competitive differentiation in a crowded marketplace," said Dan Huberty, VP, Vision, Strategy and Enterprise Architecture, Unisys. "However, the window for seizing the initiative is rapidly narrowing. Smart IT organizations must take steps now to implement a concerted digital-business strategy and infrastructure or risk missing a golden opportunity for innovation and growth."

Many respondents to the survey indicate that their organizations are making progress in areas crucial for delivering the benefits of digital business. For example, a third (34 percent) of respondents say that their organizations are struggling to deliver improved end-user and customer experiences, but 70 percent indicate that they are delivering persona-based service to support internal IT users (and another 15 percent of respondents would like to do so).

Persona-based services are personalized to the job or service requirements of a specific role, extending to internal users the principles of customer relationship management (CRM) that normally apply to external customers. The digital business model is a natural vehicle for CRM and other applications that rely on unified delivery of personalized, integrated information from multiple sources.

Digital businesses perform best when they transform into software-defined enterprises in which key enabling technologies are based on and connected through software to enable greater flexibility and scalability at lower cost than hardware-heavy data centers – the traditional hubs of enterprise IT. Service management for personalized delivery of vital productivity services and service integration and management for cost-efficient coordination of multiple external service providers are key to the success of the software-defined digital business.

Survey Methodology: IDG Research conducted the survey on Unisys' behalf in September and October 2015. The results are based on responses from 188 IT directors and vice-presidents in non-IT roles working for international organizations with 500-plus employees and US organizations of 1,000-plus employees. The respondents were based in the US, UK and Germany.

Pete Goldin is Editor and Publisher of APMdigest

The Latest

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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 ...

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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 ...

IT Execs Struggling with Transition to Digital Business Model

Pete Goldin
APMdigest

IT and business professionals in the US and Europe understand the value of adopting a digital business model but struggle to find the best way to engineer it to deliver the greatest value to employees and customers, according to new research from Unisys Corporation.

The digital business model represents the convergence of social technology, cloud, mobility, data analytics and security to drive new business models and engage, enable and support an increasingly tech-savvy workforce and customer base. The IT infrastructure enabling digital business transformation must be flexible and scalable on demand.

The 188 respondents to the survey – conducted for Unisys by IDG Research – appreciate that digital business transformation provides the key to elevating levels of service to those demanding internal and external constituencies: 55 percent cite that service requirement as their key challenge for 2016.

In addition, nearly two-thirds (65 percent) of respondents consider it highly important for their organizations to modify technology, IT processes or IT resources over the next 12 months to implement digital business, focusing especially on five key priority areas: mobile application development, cloud deployment, social media, data analytics and security.

Yet 54 percent assess their organization's progress toward a digital-business model that delivers on user expectations as average or below average (32 and 22 percent, respectively), while 45 percent rate progress above average.

In addition, less than 20 percent of respondents who rate each of the five IT focus areas as critical or high priority for digital-business implementation report significant progress in any one area. Few indicate that their organization is ready to meet customer expectations over the next 12 months: only 41 percent indicate that their technology or infrastructure is prepared, while 40 percent and 39 percent, respectively, rate their IT skill sets and security/compliance strategies as adequate.

Respondents who consider each of the 5 IT initiatives as at least a moderate priority report the greatest progress in two key areas: 69 percent cite at least some progress in both mobile application development and cloud deployment, but cite less significant progress in social media, data analytics and security.

Making Progress

"Digital business can be a powerful force for enhanced productivity and competitive differentiation in a crowded marketplace," said Dan Huberty, VP, Vision, Strategy and Enterprise Architecture, Unisys. "However, the window for seizing the initiative is rapidly narrowing. Smart IT organizations must take steps now to implement a concerted digital-business strategy and infrastructure or risk missing a golden opportunity for innovation and growth."

Many respondents to the survey indicate that their organizations are making progress in areas crucial for delivering the benefits of digital business. For example, a third (34 percent) of respondents say that their organizations are struggling to deliver improved end-user and customer experiences, but 70 percent indicate that they are delivering persona-based service to support internal IT users (and another 15 percent of respondents would like to do so).

Persona-based services are personalized to the job or service requirements of a specific role, extending to internal users the principles of customer relationship management (CRM) that normally apply to external customers. The digital business model is a natural vehicle for CRM and other applications that rely on unified delivery of personalized, integrated information from multiple sources.

Digital businesses perform best when they transform into software-defined enterprises in which key enabling technologies are based on and connected through software to enable greater flexibility and scalability at lower cost than hardware-heavy data centers – the traditional hubs of enterprise IT. Service management for personalized delivery of vital productivity services and service integration and management for cost-efficient coordination of multiple external service providers are key to the success of the software-defined digital business.

Survey Methodology: IDG Research conducted the survey on Unisys' behalf in September and October 2015. The results are based on responses from 188 IT directors and vice-presidents in non-IT roles working for international organizations with 500-plus employees and US organizations of 1,000-plus employees. The respondents were based in the US, UK and Germany.

Pete Goldin is Editor and Publisher of APMdigest

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 ...