PART 1

How to rise above obstacles and increase productivity

Green hot air balloon with the Qlik logo flying over various icons against a clear sky

Chances are, you’re aware of the barriers between your team and productivity. Ineffective communication. Siloed departments. Outdated processes. Inadequate resources. Multitasking due to a high workload. Upskilling for AI is taking forever. The list goes on.  

While this guide can’t solve all those problems, we’ll look at how modern data strategies are prioritizing accuracy and trustworthiness — two keys to unlocking efficiency throughout your organization. And we’ll explore how you can increase productivity and get to market faster by moving data in real time; improving collaboration between IT, Analytics, and Business teams; and simplifying your AI. 

Ready to take off?  

DOING DATA DIFFERENTLY: Companies with strategic data practices finish projects 90% faster 2 and spend 50% less time preparing data.3

Get real about working in real time

Data that’s out of date can’t keep up with the pace of modern business.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.

Data Leader Scenario #1

IDENTIFY THE PROBLEM

With over 400 stores across the globe running on siloed systems, Urban Outfitters’ corporate leaders didn’t have a clear store-by-store snapshot, with reports often outdated and hard to act on.

DO DATA DIFFERENTLY

Feeling behind the times, Urban Outfitters consolidated their data and analytics strategy, and they rolled out real-time data access to store managers to support in-the-moment decision-making.

GET RESULTS
  • Instant insights into store performance

  • Simplified store setup, anywhere in the world

  • Accurate inventory and distribution management

  • Improved ecommerce experience and increased sales

  • More time on the sales floor for managers



Urban Outfitters company logo
The more data we have in the cloud, the easier it is for us to set up new stores and connect them from anywhere around the globe.
Paul Reigel
Technology Director | 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.

A man wearing glasses holds a laptop, smiling looking at the screen

Data Leader Tip

5 ways to spot an unproductive data flow:
• Data isn’t synced across systems
• Dashboards only show data from yesterday
• Analysts request new data sets
• Manual workarounds are the norm
• People don’t trust the numbers

Float like a butterfly, collab like a bee

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. 

Data Leader Scenario #2

IDENTIFY THE PROBLEM

Intuit, a technology company, has loads of useful data, but it’s too complex for the sales team to use. Since they rely on many data sources with differing metrics and definitions, putting together presentations and performance reviews is a nightmare. 

DO DATA DIFFERENTLY

Needing a stronger data culture, Intuit unified their data and analytics into a single, modern web experience, rationalizing its infrastructure and simplifying the way their team interacts with data. 

GET RESULTS
  • A single source of data truth across platforms  

  • Accurate KPI reporting that keeps people accountable  

  • Confident presentations, knowing your data is the latest  

  • A tenfold increase in analytics usage across the company  

  • Tighter alignment between IT and business teams



Intuit logo in white font with a dot above each capital T to make them look like people
Using a data product approach led to a 26% productivity improvement for project teams and a 44% decrease in LLM hallucinations in our developer facing chatbots.
Tristan Baker
Data Strategy and Architecture Leader | Intuit


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.

DOING DATA DIFFERENTLY: A majority of the value that a company derives from data will stem from 5 to 15 data products.4

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. 

DOING DATA DIFFERENTLY: 88% of senior decision-makers feel AI is essential or very important for reaching strategic goals and increasing profits.5

A woman in a business suit confidently holds a laptop looking into the distance with a smile

Data Leader Tip

How to ensure teams can turn data into productivity:
• Establish KPIs that set benchmarks for efficiency
• Conduct in-depth interviews with teams and other stakeholders
    ○ Determine their skillsets and any skill gaps
    ○ Understand how the team works and/or would prefer to work
    ○ Collaborate within and outside the department
• Offer regular training opportunities so important skills stay fresh

With data and AI, kiss questioning goodbye

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. 

Data Leader Scenario #3

IDENTIFY THE PROBLEM

Transbank, a fintech company, loves seeing their daily payment transactions soar, but their outdated processes are holding back employee productivity and customer experience. The need to protect privacy and data quality makes things even harder. 

DO DATA DIFFERENTLY
GET RESULTS
  • An autonomous agent with a chat-like UX  

  • Sales teams analyze customer transactions and other behavior on the go  

  • Execs use GenAI to access key client profiles, portfolios, and reporting  

  • ML models proactively address customer churn  

  • Increase in Net Promoter Scores and other sentiment metrics



Transbank: creciendo juntos logo
Moving to the cloud is a process of evolution, and evolving internal processes away from on-premises environments is also a process of discovery.
Williams Fáez
Head of Platforms, Data, and Artificial Intelligence | Transbank


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. 

DOING DATA DIFFERENTLY: Compared to employees who don't use GenAI capabilities, employees using GenAI can increase performance by nearly 40%.6

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.


IDC company logo
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


A man and woman are focused on a laptop screen, engaged in discussion or collaboration

Data Leader Tip

How to ensure teams can turn data into productivity:
• Establish KPIs that set benchmarks for efficiency
• Conduct in-depth interviews with teams and other stakeholders
 ○ Determine their skillsets and any skill gaps
 ○ Understand how the team works and/or would prefer to work
 ○ Gauge how well they collaborate within the department and outside it
• Manual workarounds are the norm

Don’t just do data. Let data help you do it all.

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. 

Green hot air balloon with the Qlik logo flying over various icons against a clear sky

Data Leader Part 1 Checklist

  • Using AI to transform productivity isn’t a one-and-done action item. It’s an always-on task that needs to evolve as your business and work demands change.  

  • Integrate data and AI literacy into your work culture from the beginning. The more your team understands each, the more prolific they’ll become.  

  • Embrace — no, bear hug — advanced automation like agentic AI. It’s a whip-smart time-saver that keeps your people working at peak performance.