Beyond BI: The Future of Decision Intelligence for Insight Professionals

For years, insight professionals have relied on Business Intelligence (BI) tools like Power BI and Tableau to analyze data. While these platforms excel at handling structured, transactional data, they often fall short when it comes to survey analysis. As research teams face tighter budgets, smaller teams, and the growing demand for faster insights, the industry is evolving toward Decision Intelligence — a new advanced approach that removes the manual burdens of data prep and analysis, allowing organizations to move from data to decisions instantly.

To explore this shift, Crispin Beale, CEO of Insight250, sat down with Mark Langsfeld, CEO of mTab, to discuss the limitations of BI tools for survey analysis, the impact of AI on insights workflows, and why Decision Intelligence is transforming the way organizations extract value from their data.

Crispin: Mark, many research teams have used BI tools like Power BI and Tableau for years. What are the biggest challenges when analyzing survey data on these platforms?

ML: The problem is that BI tools were never purpose-built for survey data. They were designed for structured, transactional databases where every row represents a clean, distinct record. Survey data, on the other hand, is hierarchical, unstructured, and often includes multi-response questions that require special handling. This leads to several major challenges for research teams.

One of the biggest frustrations is handling multi-response questions and evaluation sets typically used in Brand Tracking, which every big brand conducts — BI tools don’t support them natively, so analysts must manually stack and restructure data just to make it usable. Then there’s the issue of data wrangling and cleaning. Every new survey wave requires extensive formatting and transformation, which eats up valuable time. The process is also error-prone and tedious, often requiring SQL or Python scripting to manipulate the data properly. Lastly, BI tools lack built-in statistical testing, meaning researchers have to run significance tests and weighting calculations separately, adding yet another layer of complexity.

The result is that teams spend the majority of their time just preparing the data, and writing code to perform specific tasks for survey data, instead of analyzing it. It’s frustrating, time-consuming, and often leads to inconsistencies in insights.

Crispin: With research budgets shrinking and teams being asked to do more with less, insight leaders are looking for ways to streamline their workflows. How does Decision Intelligence help solve this problem?

ML: We’re hearing this challenge from research teams across industries. Budgets are tighter, teams are leaner, and yet the demand for fast, high-quality insights has never been higher. Traditional BI tools force researchers to spend too much time on manual work — preparing data, cleaning it, running scripts, stacking survey responses — before they even start analyzing trends. That’s exactly where mTab comes in.

Our Decision Intelligence Platform automates survey data processing, so research teams don’t have to spend hours reformatting, cleansing, and structuring their data. mTab automatically handles multi-response questions, applies weighting and statistical significance testing, and transforms raw data into a ready-to-use format instantly. Instead of spending days preparing data, researchers can jump straight to generating insights.

Another key advantage is that mTab centralizes all insights in one place. Instead of juggling multiple files across different platforms, research teams can access, analyze, and share insights seamlessly, reducing workflow bottlenecks and making it easier for stakeholders to get the answers they need. By automating the heavy lifting, mTab allows teams to focus on strategic decision-making instead of data wrangling.

Crispin: AI has had a profound impact on the insights industry. How is mTab using AI to help companies extract more value from their data?

ML: AI is transforming how insight teams work, eliminating the slow, manual processes of data prep, analysis, and reporting. At mTab, we’re introducing AI that automates dataset harmonization, identifies key trends, and generates insights instantly — freeing researchers from time-consuming summarization.

The impact of AI is huge. Instead of spending weeks cleaning data and creating reports, teams can access actionable insights in minutes. The process is flipped on its axis: find insights immediately, then refine the queries that built that analysis, if needed.  This shift accelerates decision-making and empowers researchers to focus on high-value strategic work, making insights more impactful across the organization.

Crispin: Finally, for insight professionals still relying on BI tools for survey data, why should they consider switching to a Decision Intelligence platform like mTab?

ML: If your team is using a system like Power BI or Tableau for survey analysis, you probably feel the pain — slow, manual, and frustrating processes that require constant workarounds. You might discover a finding, but when the next question comes up, you must find a data scientist to write the code for nuanced analysis. These tools weren’t designed for market research, and teams spend far too much time on data wrangling instead of insight generation.

mTab was built specifically for insights professionals. It eliminates the need for manual data prep, automates statistical testing, accelerates reporting with AI, and brings all your insights into one unified platform. This means faster insights, greater efficiency, and significant cost savings compared to BI tools.

For research leaders looking to modernize their approach and move beyond the limitations of BI, decision intelligence is the answer. It’s not just a better alternative — it’s a fundamental shift in how insights teams work, enabling them to turn data into decisions instantly.

Hot Topic:

Crispin: There are growing discussions from teams across enterprises, from marketing to product development, on having greater access to insights, what are your thoughts on this?

ML: We actually develop our technology around this need. More and more enterprises across industries indeed are asking for immediate access to insights for faster decisions. This empowers the marketing, product development, production, or any number of other teams to make faster decisions. However, it also allows insight teams to focus on the bigger picture to identify larger trends, uncover deeper insights and help develop long-term strategies for the business.

Top Tip - Keeping up with innovation

Crispin: Mark this has been a fascinating conversation, what would your top tip be for readers so they too can lead and innovate in our profession?

ML: We’ve just discussed a lot about technology advancements for the insights industry. The key to keeping up with these ongoing innovations is to plug into the groups at the forefront that identify and cover these tech topics and industry developments. Some of the leaders are Insight250, ESOMAR, Insights Association and Market Research Society, to name a few. Engaging these types of groups that assemble the industry really helps to keep up with the incredible pace of innovation.

Final Thoughts

The insights industry is evolving, and the shift from BI to Decision Intelligence is already underway. Research teams that continue relying on traditional, manual methods will struggle to keep up, while those that embrace AI-driven automation already have a competitive advantage.

If your team is spending more time preparing data than analyzing it, it’s time to make the switch. Decision Intelligence is the future of insights.

Want to learn more? Visit mTab.com to see Decision Intelligence in action.