This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
For example, metrics like the percentage of missing values help measure completeness, while deviations from authoritative sources gauge accuracy. These metrics are typically visualized through tools such as heatmaps, pie charts, or bar graphs, making it easy for stakeholders to understand compliance levels across different dimensions.
Most teams approach this like traditional software development but quickly discover it’s a fundamentally different beast. Check out the graph belowsee how excitement for traditional software builds steadily while GenAI starts with a flashy demo and then hits a wall of challenges? Whats worse: Inputs are rarely exactly the same.
Mastering them requires robust data infrastructure, clear ROImetrics, security and trust, and a forward-looking operating model. And beyond productivity, they are increasingly viewed as catalysts for tangible ROI and market disruption. Starting now can help you leverage AI agents for genuine business transformation.
AI governance software will also become increasingly important in this process, with Forrester predicting spending on off-the-shelf solutions will more than quadruple by 2030, reaching almost $16 billion. Measuring AI ROI As the complexity of deploying AI within the enterprise becomes more apparent in 2025, concerns over ROI will also grow.
Proving the ROI of AI can be elusive , but rushing to achieve it can prove costly. Specify metrics that align with key business objectives Every department has operating metrics that are key to increasing revenue, improving customer satisfaction, and delivering other strategic objectives.
When you reframe the conversation this way, technical debt becomes a strategic business issue that directly impacts the value metrics the board cares about most. So it’s essential to show the ROI to your business from the management of these costs. This creates a compelling “act now” narrative that boards understand.
Diminishing returns CIOs ask how to get data clean, but they should ask how far to take it, says Mark Molyneux, EMEA CTO at software developer Cohesity. So, before embarking on major data cleaning for enterprise AI, consider the downsides of making your data too clean.
Then there’s Upwave, a data-driven ad analytics firm, which found ROI from a customer-facing tool that uses gen AI to create campaign performance reports. The ROI, he says, is evident in shorter development cycles, and reduced friction in HR and customer service. Their secret: flexible thinking and diverse metrics.
Investments in AI agent projects are expected to yield orders of magnitude in ROI and business value if companies select high-impact use cases. There is no faster way to erode ROI than through unneeded token costs and extra processing costs. Now is the time to explore agentic AI. But then, that’s where we must dive in slowly.
Supply chain management (SCM) is a critical focus for companies that sell products, services, hardware, and software. Each digital DCM capability is mapped to elements in the SCOR DS, the platform-agnostic framework that links business processes, metrics, best practices, and technology into one streamlined format.
What’s multicloud’s return on investment (ROI) — and how can you improve it? Why you need to justify the ROI of multicloud The right question isn’t whether multicloud saves money — it’s whether it’s worth the cost. If your software doesn’t run in those clouds, it can be a dealbreaker.”
Many organizations have launched dozens of AI proof-of-concept projects only to see a huge percentage fail, in part because CIOs don’t know whether the POCs are meeting key metrics, according to research firm IDC. Many POCs appear to lack clear objections and metrics, he says. The customer really liked the results,” he says.
This year saw emerging risks posed by AI , disastrous outages like the CrowdStrike incident , and surmounting software supply chain frailties , as well as the risk of cyberattacks and quantum computing breaking todays most advanced encryption algorithms. Furthermore, the software supply chain is also under increasing threat.
Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.
Implement outcome-based metrics : Measure architectural success through business outcomes rather than technical compliance. Develop new skills and competencies : Invest in architectural talent that combines technical expertise with strategic business acumen to lead AI transformation.
TL;DR Small language models (SLMs) are optimized generative AI solutions that offer cheaper and faster alternatives to massive AI systems, like ChatGPT Enterprises adopt SLMs as their entry point to generative AI due to lower training costs, reduced infrastructure requirements, and quicker ROI. Faster ROI. Cerence Inc. Cerence Inc.,
Each one paired with the business metrics its meant to move. Begin with direct costs internal labor, contractors and product-specific software those items that easily map to only one product team. For each product line, include the total cost of ownership and the business metrics the team is driving. Side-by-side with metrics.
Companies must get this puzzle solved right to avoid the disappointing ROI that many have experienced in 2024 related to their AI capabilities. He is a global information technology leader with broad experience from multinational IT consulting organizations and leading independent software vendors.
On the other hand, there are also many cases of enterprises hanging onto obsolete systems that have long-since exceeded their original ROI. He recommends building a user feedback loop and carefully studying satisfaction metrics. Kar advises taking a measured approach to system modernization.
Low Code No Code Development Supports Analytics Performance Within the very near future, it is estimated that 70% of all software and application design will include a component of low-code or no-code development. So, it is no surprise that analytics software and tools are also affected by this trend.
What’s needed is agentic AI — software entities that interpret context, make decisions and take action. What’s at stake This shift isn’t about vanity metrics. Going live faster = faster ROI. These are ideal candidates for automation, especially if the resolution steps are policy-driven, well-documented workflows.
Decide how fast you should go, not can go According to Dan Garcia, CISO at software developer EDB, he and his team recognize that different agentic AI use cases require varying degrees of pacing. They move fast in areas where the business ROI is clear, where theres mature data infrastructure, and where governance allows.
Logs, metrics, and traces generate vast amounts of data, making it challenging to maintain performance, reliability, and cost-efficiency. Roi Gamliel is a Senior Solutions Architect helping startups build on AWS. This post is co-written with Ido Ziv from Kaltura. His hobbies include sailing and Kubernetes (but not at the same time).
If the finance industry as a whole wants to experience success in the age of AI, finance teams everywhere need to start investing in automated financial reporting software. Measurable ROI Finance teams are set to transform their financial reporting strategies this year, driven by a challenging economic climate.
Even as many organizations infuse AI into software development and tech support teams, most enterprise leaders DiLorenzo speaks with see a slowdown in hiring new developers and IT support staff, rather than layoffs for current staff, he says. “The If a software developer is not using AI development tools, it’s going to be a challenge.”
This shift often led to strategic design decisions that favoured finance, where all data, primarily financial transaction data, as opposed to broader operational metrics like customer behavior, supply chain efficiency or production output, sometimes passed through finance first. Operational
But without strong analytics, you may be leaving ROI on the table. Visualizations in business intelligence software are often dismissed as a commodityinterchangeable and easily overlooked. But analytics can help you and your customers maximize ROI and maintain a competitive edge. Your application is built to deliver value.
As a tech lead managing infrastructure and platform teams, I’ve seen how CIOs can reduce IT costs without stifling innovation,” says Chandrakanth Puligundla, software development engineer and data analyst at Albertsons Companies. “It Additionally, he says CIOs need to audit software and tools to remove duplicate or underutilized applications.
Subpar and inaccurate data doesnt just threaten decision-making; it can lead to regulatory mishaps, adds Souvik Das, chief product and technology officer at financial software firm Clearwater Analytics. A fundamental mistake organizations make is launching AI initiatives without clear success metrics, he says.
The business impact: CDP by the numbers Let’s talk ROI. These aren’t just vanity metrics but proof that the art of the possible is real. I’ve found that cross-functional teams across finance, sales/marketing, IT, legal/compliance and infosec drive the best results. Revenue growth? I’ve seen 10–15% lifts from smarter targeting.
found that 71% of organizations use agile in their software development lifecycle but only 11% are very satisfied and only 33% are somewhat satisfied with their results. It is helping us to think out of the box, to shrink the software development lifecycle, and increase the pace and agility of digital transformation.
They dont just build software; they own strategy, delivery, iteration, and ultimately, outcomes. In a product model, the question is different: Did we move the needle on a meaningful business metric? And that last word is key: outcomes. For a commerce team, that might mean increasing pipeline velocity or boosting conversion rates.
And the one that isn’t has a four-year ROI and degrades our ability to support the business. These experiences spanned both public and private equity-owned software companies undergoing transitions to subscription models. We looked at these metrics across IT support tiers and by service. I was ready.
Longtime CIO Frank LaQuinta has been elevated to a multi-role post, serving as head of digital, data, and operations, with Kevin Adams, now head of technology, taking oversight of technology strategy, software engineering, cybersecurity, infrastructure, and support.
One client proudly showed me this evaluation dashboard: The kind of dashboard that foreshadows failure This is the tools trapthe belief that adopting the right tools or frameworks (in this case, generic metrics) will solve your AI problems. Second, too many metrics fragment your attention. When everything is important, nothing is.
This blog explores the true ROI of connected finance and reveals how AI is reshaping finance teams with practical, business-specific applications—not just chatbots, but intelligent assistants that deliver real impact daily. Beyond Efficiency Metrics Time savings matter—reducing close cycles and manual work frees teams to focus on analysis.
That’s why it’s critical to monitor and optimize relevant supply chain metrics. Finally, we will show how to combine those metrics with the help of modern KPI software and create professional supply chain dashboards. Your Chance: Want to visualize & track supply chain metrics with ease?
1) What Are Productivity Metrics? 3) Productivity Metrics Examples. 4) The Value Of Workforce Productivity Metrics. Your Chance: Want to test a professional KPI tracking software? What Are Productivity Metrics? In shorter words, productivity is the effectiveness of output; metrics are methods of measurement.
6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. More generally, low-quality data can impact productivity, bottom line, and overall ROI. Table of Contents. 1) What Is Data Quality Management?
Here, we’ll examine 18 essential KPIs for social media, explore the dynamics and demonstrate the importance of social metrics in the modern business age with the help of a KPI software , and, finally, wrapping up with tips on how to set KPIs and make the most of your social platforms. Let’s get going. What Are Social Media KPIs?
With the help of the right logistics analytics tools, warehouse managers can track powerful metrics and KPIs and extract trends and patterns to ensure everything is running at its maximum potential. Making the use of warehousing metrics a huge competitive advantage. Explore our modern KPI software for 14 days, completely free!
2) What Are Metrics? 3) KPIs vs Metrics: Main Differences. 4) Tips For KPI & Metrics Tracking. This is done with the help of KPI and metrics. KPIs and metrics are often considered the same thing in day-to-day business contexts. Let’s quick it off with the definition of metrics and KPIs! What Are Metrics?
IT leaders are drowning in metrics, with many finding themselves up to their KPIs in a seemingly bottomless pool of measurement tools. There are several important metrics that can be used to achieve IT success, says Jonathan Nikols, senior vice president of global enterprise sales for the Americas at Verizon. “To Here they are.
I have found very few companies who have found ROI with AI at all thus far,” he adds. The concern about calculating the ROI also rings true to Stuart King, CTO of cybersecurity consulting firm AnzenSage and developer of an AI-powered risk assessment tool for industrial facilities. “I
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content