How to rise above obstacles and increase productivity

Data that’s out of date can’t keep up with the pace of modern business. Working with real-time data boosts productivity and helps you make faster, better decisions.

Ultimately, you need agile, responsive capabilities to adapt to anything your industry throws your way, whether that’s spotting market changes before they happen, or anticipating customer needs.

There’s a lot to unpack there, so let’s paint a picture with our first “Data Leader Scenario”, featuring popular lifestyle brand Urban Outfitters. 

Fact is, whether it’s a campaign performance dashboard, a sales forecast, or an inventory check, if it’s lagging behind, it’s leading you in the wrong direction. That’s where Change Data Capture technology shines: syncing your entire data ecosystem so people see what’s happening right now, not what happened last week.

After you get your data pipeline flow in order, the best insights appear out of nowhere, right? Wrong! The final step is making sure to get the insights to the right place, at the right time, to be accessed by the right person.

When done correctly, and integrated with the latest AI experiences, you can more effectively spot patterns, make better decisions, and optimize processes in real time. Think alerts, predictive insights, and personalized recommendations that happen with minimal manual effort. It streamlines your work and elevates your decision-making, letting you focus on what really matters.

Overall, remember this: When the goals are increased productivity and faster GTM, analytics isn’t a one-and-done action item. It’s an always-on, intelligent, and democratized process that gets everyone involved, not just data and AI experts.

No, seriously. Slipping into a nature documentary for a sec, a beehive is a high-functioning, honey-producing machine because the honeybees share one purpose, with each bee playing an important, productive role. Your data should be like a beehive: unified — no matter the number of sources — and seamlessly collaborative. So, how do you get that data buzzing? Let’s take a look at another Data Leader Scenario for inspiration. 

While Intuit revamped their analytics operations with a unified web portal, dashboards and the like are just the start of the conversation. In fact, most Data Leaders like you have been doing that for years. An ideal next step is deepening your capabilities with data products. 

Data products are highly trusted, reusable, and consumable data assets designed to solve domain-specific business challenges and help organizations break free from silos. Data products bring ownership, accountability, and trust to data. And by making data accessible to everyone — from business users to data analysts to engineers — they help people put AI to work where it really counts, lighten everyone’s workload, and unlock new opportunities for growth.

In a utopian unified environment, there are no more disconnected apps, misaligned understandings, wasted time on duplicate work, or delays in making data useful — just clear, data-driven collaboration throughout your organization that lets people move at full speed. No doubts. Just decisions. 

And as unification, accessibility, and productivity rise, you might see a natural increase in how well teams understand, explore, and use data (aka data literacy).  

Likewise, since much of your data management will be driven by AI, it's crucial to make sure your people understand AI basics, including its limitations, and have the skills to correctly and effectively use AI-driven tools. Focusing on this AI literacy and soft AI skills combo will help drive adoption and usability. Over time, your team will discover new ways to use AI, track performance, and make more informed decisions.  

It’s worth mentioning that although AI and machine learning can boost productivity, what allows us to work together and succeed is the human element. 

The power of AI to transform data’s effectiveness and insightfulness is undeniable. But don’t focus solely on technology without helping your people embrace it. By making a work-smart culture part of your data and analytics solutions, you can create an AI-driven culture that can be championed across your organization. 

That’s what Transbank accomplished in Part 1’s third and final Data Leader Scenario. 

What was once the exclusive realm of developers and coders is now a place where almost everyone can play. As Transbank proved, no-code and low-code data platforms make AI available to anyone in your organization who works with data, from chief data scientists to junior employees. Intuitive interfaces give users a simple, visual approach to building data workflows. With a simple UX, you can connect your data, clean it up, and send it where it needs to go in just a few clicks. 

Thanks to OpenAI’s ChatGPT, most people are familiar with generative AI tools by now. But in work environments, what can be accomplished by simply crafting a smart prompt is astonishing. Throughout the data journey, AI is doing the heavy lifting for things like pipeline design, script generation, and insight generation. It can also make your people more productive by streamlining complex tasks that require manual effort and technical knowledge, effectively taking a wrecking ball to the advanced analytics skill barrier. 

This new, streamlined approach to analytics lets teams work faster, launch products sooner, target customers more accurately, fine-tune strategies on the fly, and even simplify data management through automation. Overall, it creates a mutual give-and-take where AI makes insights more accessible, simple, and useful, all without you needing to be an AI expert. 

Before we close this Part on productivity, we would be remiss not to talk about the new kid on the block, agentic AI. Agentic AI is your best friend for eliminating barriers to AI adoption. It takes GenAI to another level, handling time-consuming, multi-step processes of collecting, cleaning, and analyzing data (i.e., the stuff that traditional automation struggles with). It can read text data, such as sentiment analysis, and generate reports in plain language. It even saves people from having to wait on a data specialist or programmer to generate insights.  

And since agentic AI is more autonomous, it frees up your people to focus on more strategic and creative work.

Gen AI is very important, but agentic AI is beyond that. Every organization can unlock exponential growth; You unlock a different pace of agility and innovation.

Ritu Jyoti

Group VP/General Manager | IDC

Achieving high levels of productivity doesn’t have to be a daily headache. Data is the lynchpin of a more productive organization that makes brilliant move after brilliant move. So, whether you’re on the AI-ready road already or still planning your route, now’s the time to embrace speed, teamwork, and the power of AI. Your business will be more agile, adaptable, and ready for whatever comes next.