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Digital Transformation Needs Intentionality

Larry Dragich

With the convergence of technology finding its way from the corporate world to our personal devices and home appliances, meeting the expectations of a quality customer experience is a formidable challenge.

Digital Transformation seems to be on everyone's radar but if there is no intentionality from the IT Executive who is sponsoring the program it becomes more of a loose correlation of technology initiatives under an IT strategy banner.

Consider some of the initiatives: Data/Analytics, Mobile Technology, Private Cloud, Artificial Intelligence (AI), Machine Learning, and the Internet of Things (IoT). All have their own unique role to play that is intrinsic to a Digital Transformation program. Although, when you step back and consider how to measure the success for such a program, things can get a little murky.

Digital Transformation requires more than just the latest technology, it's a mindset that iterative change is on the way and should be embraced. This also requires us to factor in the people and process parts of the equation and find ways to measure the end-user-experience (EUE).

One way to do this is to sponsor an Application Performance Monitoring (APM) initiative that can provide visibility to the business, help communicate the progress, and highlight the impacts to the organization.

Meaningful metrics can be difficult to obtain without a specific focus on business impact (transactions) and a concise way to collect them. Consider that a strong APM solution opens the door for better clarity on how each technology initiative affects the EUE, providing key metrics for a Digital Transformation program.

I recommend including all three monitoring factions within an APM strategy, Wire Data Analytics, Synthetic Transactions, and Agent Code Instrumentation.

1. Wire Data Analytics- Discover and decipher application performance data as it traverses the network.

2. Synthetic Transactions- Web robots that execute specific transactions for location-based availability and act as a barometer for measuring application performance.

3. Agent Code Instrumentation- Lightweight agents monitoring the application code as it executes from the Web and App servers. To gain visibility at the edge, script injection is often used for client render time.

Utilizing these overarching delivery mechanisms to provide input into a Machine Learning and/or AI solution has the potential to dramatically improve application delivery and performance across a variety of IT disciplines. This also lays the ground work to support a DevOps culture, providing an amplified feedback loop that is so desperately needed.

Once you develop a strategy on the best way to bring together the 3 monitoring factions, APM becomes "table stakes" on the digital transformation front because you can't improve what you don't measure.

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Digital Transformation Needs Intentionality

Larry Dragich

With the convergence of technology finding its way from the corporate world to our personal devices and home appliances, meeting the expectations of a quality customer experience is a formidable challenge.

Digital Transformation seems to be on everyone's radar but if there is no intentionality from the IT Executive who is sponsoring the program it becomes more of a loose correlation of technology initiatives under an IT strategy banner.

Consider some of the initiatives: Data/Analytics, Mobile Technology, Private Cloud, Artificial Intelligence (AI), Machine Learning, and the Internet of Things (IoT). All have their own unique role to play that is intrinsic to a Digital Transformation program. Although, when you step back and consider how to measure the success for such a program, things can get a little murky.

Digital Transformation requires more than just the latest technology, it's a mindset that iterative change is on the way and should be embraced. This also requires us to factor in the people and process parts of the equation and find ways to measure the end-user-experience (EUE).

One way to do this is to sponsor an Application Performance Monitoring (APM) initiative that can provide visibility to the business, help communicate the progress, and highlight the impacts to the organization.

Meaningful metrics can be difficult to obtain without a specific focus on business impact (transactions) and a concise way to collect them. Consider that a strong APM solution opens the door for better clarity on how each technology initiative affects the EUE, providing key metrics for a Digital Transformation program.

I recommend including all three monitoring factions within an APM strategy, Wire Data Analytics, Synthetic Transactions, and Agent Code Instrumentation.

1. Wire Data Analytics- Discover and decipher application performance data as it traverses the network.

2. Synthetic Transactions- Web robots that execute specific transactions for location-based availability and act as a barometer for measuring application performance.

3. Agent Code Instrumentation- Lightweight agents monitoring the application code as it executes from the Web and App servers. To gain visibility at the edge, script injection is often used for client render time.

Utilizing these overarching delivery mechanisms to provide input into a Machine Learning and/or AI solution has the potential to dramatically improve application delivery and performance across a variety of IT disciplines. This also lays the ground work to support a DevOps culture, providing an amplified feedback loop that is so desperately needed.

Once you develop a strategy on the best way to bring together the 3 monitoring factions, APM becomes "table stakes" on the digital transformation front because you can't improve what you don't measure.

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

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 ... 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 ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...