After collecting and analyzing data, researchers should make recommendations that guide quick-serve restaurant decisions.

After you’ve gathered data and given it a good look, what’s the next move? If you’re studying DECA Quick-Serve Restaurant Management topics, you already know the power of turning numbers into action. The answer, in a marketing-research context, is to make recommendations based on what you found. Not just “hmm, interesting,” but specific, grounded steps that help leaders decide on what to do next. Let me explain why this matters and how to do it well.

Why recommendations are the real payoff

Think of data as a map. It shows you streets, shortcuts, and potential hazards. Recommendations are the route you propose to get from where the map marks you now to where you want to be. For a quick-serve restaurant, those recommendations translate into concrete moves—adjusting menus, tweaking prices, changing hours, reshaping promotions, or shifting store operations. Without recommendations, the insights sit there like a good idea that never gets anywhere.

Yes, presenting data graphically can make the story clearer. Still, the core value comes from translating findings into actionable steps that leaders can sign off on, budget, and implement. Publishing results or starting a new project might be relevant in some contexts, but they usually come after you’ve linked the data to decisions. In short: data informs decisions, decisions require recommendations, and recommendations drive action.

From insight to impact: a simple framework

If you want your recommendations to stick, structure matters. Here’s a practical, restaurant-friendly way to frame them:

• Tie each recommendation to a finding. It sounds obvious, but it’s easy to loose the thread. For example, if data shows more breakfast traffic on weekends, a recommendation might be to extend weekend breakfast hours for a limited period.

• Be specific and actionable. Instead of “consider a price tweak,” say “raise the breakfast combo price by 0.50 and test for 4 weeks with a 10% uptake target.” Specifics reduce ambiguity and speed up decisions.

• Prioritize by impact and feasibility. Not every insight deserves equal weight. Rank suggestions by expected revenue lift, customer satisfaction, or cost of implementation, then map them to a realistic timeline.

• Include a rationale grounded in the data. A recommendation without a reason feels flimsy. Show the link: “data shows X; we expect Y impact because of Z.”

• Outline metrics to track success. Identify what you’ll monitor to know if the action works—daily sales, item-level performance, guest feedback, or labor costs.

• Offer alternatives. For some decisions, provide a best-case, a conservative option, and a fallback. That gives leadership flexibility if conditions change.

Common-sense language with a dash of flair

While you’re keeping it practical, you don’t have to sound robotic. A touch of narrative helps. You can paint a picture of how customers might respond or how staff will adapt. For instance, “If the morning rush shows a lull in the 9:30–10:30 window, we propose a two-week pilot of a mid-morning value bundle that’s easy to roll out on the drive-thru line.” The goal is clarity, not cleverness for its own sake.

How to craft recommendations that stand up to scrutiny

• Start with the objective. Remind readers what problem you’re trying to solve. This keeps the recommendations focused and aligned with what stakeholders care about.

• Use evidence to back every point. Reference the data that supports each move. If possible, attach a quick data note or chart in the appendix—something decision-makers can check without hunting for it.

• Be realistic about costs and benefits. Proposals should include rough costs, resources needed, and a reasonable time frame. If a suggestion requires new equipment or a staff shift, spell it out.

• Consider risk and contingency plans. Every plan has trade-offs. Acknowledge potential downsides and offer a contingency.

• Present a clear rollout plan. Outline steps, owners, and milestones. A risky idea becomes manageable when you lay out who does what and when.

Where to place recommendations in your storytelling

There’s a natural rhythm to a solid marketing-research narrative. Start with a quick, digestible summary of the key findings. Then move into the recommendations, each tied to a finding and followed by the rationale and success metrics. Finish with a note on monitoring and next steps. If you’re presenting to a diverse audience, consider a two-track approach: a concise executive brief for leaders and a detailed appendix for the team that will implement the changes.

Practical examples you can relate to

• Menu optimization. If analysis shows a rising demand for a popular breakfast item on weekends, recommend extending the breakfast menu hours by two hours in the weekend, paired with a small price tweak and a limited-time combo. Include expected lift estimates (based on comparable periods) and a plan to measure daily item sales.

• Promotions that move the needle. Suppose the data reveals that family meals outperform individual combos during late afternoons. Propose a limited-time family bundle during that window, with a clear target for uplift and a budget cap for marketing. Add a simple A/B test plan so you can compare performance against the standard bundle.

• Operational tweaks. If traffic surges in the lunch hour but wait times spike, suggest a pilot of two lane-saving steps: a streamlined order pickup area and a dedicated pickup window for pre-orders. Tie it to a projected reduction in wait time and higher guest satisfaction scores.

• Staffing and training. Data showing longer service times with new staff on weekends could lead to a recommendation for a focused weekend onboarding session and a quick-reference guide for popular items. Include a cost estimate and a success metric like order accuracy or speed of service.

The human side: stakeholders and decisions

Recommendations aren’t just about numbers; they’re about people. Marketing teams, store managers, operations, finance, and even vendors will weigh in. Engaging stakeholders early makes a big difference. Share the data story in plain language and invite feedback. When teams see their input reflected in the plan, they’re more likely to own the implementation. And that ownership is what turns insight into impact.

A quick note on presentation formats

Yes, charts and graphs can help storytelling, but the message must come through loud and clear in the words you choose. A well-phrased recommendation list carries more weight than a wall of numbers. If you include visuals, use them to support the point, not to overwhelm. Think of visuals as the breadcrumbs that guide readers to the destination you’ve laid out with your recommendations.

Avoiding common missteps (so you don’t trip at the finish line)

• Don’t rush to conclusions. It’s tempting to connect every data blip to a dramatic change, but being patient and precise pays off.

• Don’t present data without a take-away. Every chart should have a clearly stated implication.

• Don’t overwhelm with options. A long list of recommendations can stall progress. Prioritize a handful of high-impact moves.

• Don’t forget the operational reality. A brilliant idea won’t work if it clashes with how the kitchen runs or with labor laws and budgets.

• Don’t neglect the follow-through. Plans without owners and timelines fade away. Assign responsibilities and set a realistic schedule.

Bringing it back to the DECA Quick-Serve world

In fast-foot restaurants, decisions are executed fast too. The framework you use to translate data into recommendations mirrors how store leaders think: what should we do, why this, what will it cost, and how will we know we’re succeeding? When you present recommendations grounded in data, you’re not just proving you did your homework; you’re helping a team move from insight to action—quickly, cleanly, and with confidence.

A closing thought to keep you grounded

Data tells you what happened. Recommendations tell you what to do about it. The best researchers in the DECA Quick-Serve Restaurant Management space know that the moment you finish the analysis, you’ve only just started the work of shaping a smarter, faster business. It’s the practical bridge between numbers and measurable results—the kind of bridge that keeps customers happy, employees informed, and owners optimistic about tomorrow.

If you’re ever unsure which direction to take, circle back to the objective the data was meant to address. The right recommendation will feel natural, defendable, and doable. And when leaders nod, you’ll know you’ve done more than study a scene—you’ve helped write the next page of the restaurant’s story.