How to Ace GMAT Quant and Data Insights: A Practical Study Plan for 2026–27 Applicants

For many MBA applicants, GMAT prep starts with a familiar thought that I’m good at math, so Quant should be fine. Then the mocks begin, and suddenly Quant feels less straightforward, and the Data Insights section progress feels slower than expected, and the score is not moving in the direction and speed that you anticipated.

That usually happens because GMAT Quant and DI are not really testing school-style comfort. They are testing whether you can stay sharp under pressure, pick the right method quickly, and avoid wasting time on the wrong questions. On the current GMAT, Quantitative Reasoning has 21 questions in 45 minutes, Data Insights has 20 questions in 45 minutes, and both sections matter equally to your total score. Quant is all Problem Solving with no calculator, while DI includes five question types and allows an on-screen calculator. 

The good news is that this is a very trainable part of the exam. In fact, many candidates improve much faster once they stop treating Quant like a hard math section and start treating both Quant and DI like a reasoning-and-process section.

Start by fixing your priorities

One of the most common prep mistakes is spending too much time on the flashy topics. A lot of test-takers obsess over probability, combinatorics, remainders, or rare number-property twists because they feel difficult and “GMAT-like.” Those topics do matter, but they are not where most of your score is won or lost.

In practice, the bigger gains usually come from doing the fundamentals much better- arithmetic, algebra, percentages, ratios, equations, word problems, and clean logical setup. GMAT’s own description of Quant is a section built around algebraic and arithmetic foundational knowledge applied through logic and analytical reasoning, not advanced math. That is also why so many strong students underperform there: they know the content, but their process is loose. 

So if you are planning your prep for 2026–27, spend less time chasing edge-case topics early on and more time asking: Am I consistently accurate on the boring stuff?

Understand what DI is really asking from you

Data Insights feels new to many candidates because it mixes quant, verbal, and decision-making in one place. Officially, DI tests your ability to analyze and interpret data from multiple sources and make informed decisions. The section includes Data Sufficiency, Multi-Source Reasoning, Table Analysis, Graphics Interpretation, and Two-Part Analysis. Some questions are math-heavy, some are more verbal, and many are really about sorting signals from noise. 

That means DI preparation works best when you stop seeing it as one giant mystery section. Data Sufficiency still overlaps heavily with Quant habits. Graphics and tables need comfort with percentages, ratios, averages, and comparisons. Multi-Source Reasoning and Two-Part Analysis require calm reading and structured elimination. In other words, better Quant often helps DI, and better DI often comes from stronger filtering and decision-making.

At LilacBuds, our GMAT tutors have worked with applicants who initially tried to prepare for DI as a completely separate beast. The turning point usually came when they started linking it back to core Quant reasoning, careful reading, and better timing decisions.

The first big shift: Study Topic by Topic, NOT randomly

A practical GMAT Quant and DI plan should move topic by topic. That means you do not just solve mixed sets every day and hope the score rises. Instead, you learn a topic properly, practise it until you are stable, and then move on.

This approach is also strongly supported by strong prep resources and official tools (which our LilacBuds coaches will often provide the students) for deeper expertise development. The current GMAT gives you enough official practice tools to benchmark where you stand, but those tools work best when your prep is structured enough to show what is actually weak. 

A smart sequence for most candidates looks like this: first, rebuild Quant foundations such as arithmetic, algebra, fractions, percentages, ratios, exponents, equations, and word translations. Then move into applied problem solving, including rates, sets, statistics, and harder mixed questions. Run Data Sufficiency alongside this phase because DS rewards the same habits: structure, precision, and logic. After that, move into the broader DI question types, especially tables, graphics, and multi-source sets.

This is much more effective than doing a little of everything and never mastering anything.

The second big shift: Fix your process, NOT just your knowledge

A lot of candidates already know the math they are missing. What hurts them is process.

They misread what the question is asking. They solve for the wrong value. They rush into algebra when estimation would have worked. They keep pushing through an ugly path instead of stepping back and looking for a cleaner one. Or they do not notice that their method is taking three minutes on a question that should be a one-and-a-half-minute decision.

That is why your review process matters as much as your study process. After every serious practice session, ask three things: What exactly went wrong? Was it a concept gap, a process error, or a reading mistake? And what will I do differently next time?

This is where an error log becomes very useful. Your mock results already tell you a lot if you know how to read them. The goal is to look beyond the total score and notice patterns by question type, topic, and timing.

Candidates who improve steadily are usually the ones who stop saying “I made a silly mistake” and start naming the pattern. Was it careless reading? Weak setup? Bad pacing? Overuse of brute force? That level of honesty changes scores.

Use Official Practice Materials, And Use It Carefully 

Official practice matters because the current GMAT has its own rhythm. The official practice exams use the same algorithm, scoring, and timing as the real exam, and the official starter tools give you real questions across all three sections. That makes them the best benchmark for where you truly stand. 

Of course there are a bunch of other firms (Magoosh, Gregmat, e-GMAT) that offer GMAT mock tests – but how adaptive they are and how closely they represent the actual exam question set, continues to be a mystery for most applicants. Reddit and Quora are filled with mixed reviews on the efficacy of these tests to predict your actual score.  

So remember that since official practice is limited, you cannot burn through it too early. A good rule is to begin with topic-wise learning and targeted practice, then use official mocks as checkpoints. Treat every official mock like a real test. Do it in one sitting, under timed conditions, and review it deeply afterward. 

The goal of a mock is not just to get a score. The goal is to learn where your next 20–30 points can come from.

A Practical Weekly Plan that Actually Works

If you are balancing work, applications, and prep, a realistic weekly structure is better than a heroic but unsustainable one.

A simple version could look like this: on three weekdays, do one focused topic session each day, with learning plus timed practice. On one additional day, do a short DI-focused session with one or two question types. Over the weekend, do a mixed timed set or a sectional drill, then spend proper time reviewing mistakes. Every second week, replace that mixed set with a full mock or a full Quant/DI section, depending on your stage.

If your timeline is tight, keep the plan smaller but sharper. One strong hour with real review is more valuable than three distracted hours of random questions.

In the final stretch, Stop Chasing Perfection everywhere

As test day gets closer, your job changes. You are no longer trying to cover the entire syllabus, rather trying to become more reliable.

That means reducing repeat mistakes, getting cleaner at core topics, and becoming faster at identifying when a question deserves effort and when it deserves a strategic skip-and-return. On DI, it means learning not to drown in information. On Quant, it means noticing sooner when your current path is too long.

It also helps to remember that a strong Quant score on this exam is hard-earned. Many candidates are too harsh on themselves because the scale looks deceptively simple. Focus less on what the raw number “sounds like” and more on whether your performance is improving in the areas that matter. GMAT’s current scoring system is different from the previous edition, and total score comparisons across versions are not meaningful without looking at percentiles. 

Conclusion

If you want to ace GMAT Quant and Data Insights, keep the plan simple. Master the core topics before the exotic ones. Study in a topic-by-topic way instead of randomly. Review mistakes properly instead of just marking them wrong. Practise DI as a reasoning section, not just a data section. Use official mocks carefully and under real conditions. Most of all, keep asking whether your problem is really knowledge, or whether it is process.

That distinction changes everything.

At LilacBuds, our mentors often help applicants build a prep plan around exactly this idea. Some candidates need deeper Quant rebuilding. Some are mostly losing points in DI because of reading and timing. Some are already near their target but need a cleaner review system to push through. A good plan looks different for each of them, but the principle stays the same: focus on what actually moves the score.

For applicants who want structured support, LilacBuds also offers 1-on-1 private GMAT prep with expert tutors, starting at Rs. 3,500 per hour. Many applicants choose our 15-hour Quant package to strengthen their readiness and improve their score with focused guidance. For many, that investment delivers strong ROI, especially when a higher GMAT score can improve scholarship outcomes and admission chances.