Effective Use of Trusted Research Data in Business

Can You Trust Your Data the Way You Trust Your Best Team Member? Do you know the feeling when you walk into a meeting and rely on that colleague who always has the correct information? You trust them to steer the conversation, to answer tough questions, and to keep everyone on track. What if data could be the same way—reliable, trustworthy, always there when you need it? In business, we often talk about data being "the new oil," but let’s be honest: without proper management, it’s more like a messy garage full of random bits and pieces. It’s easy to forget how essential data trust is until something goes wrong—decisions are based on faulty numbers, reports are incomplete, and suddenly, you’re stuck cleaning up a mess. So, how do we ensure data is as trustworthy as that colleague you rely on? It starts with building a solid foundation through these nine pillars: ➤ Master Data Management (MDM): Consider MDM the colleague who always keeps the big picture in check, ensuring everything aligns and everyone is on the same page.     ➤ Reference Data Management (RDM): Have you ever been in a meeting where everyone uses a different term for the same thing? RDM removes the confusion by standardising key data categories across your business. ➤ Metadata Management: Metadata is like the notes and context we make on a project. It tracks how, when, and why decisions were made, so you can always refer to them later.     ➤ Data Catalog: Imagine a digital filing cabinet that’s not only organised but searchable, easy to navigate, and quick to find exactly what you need.     ➤ Data Lineage: This is your project’s timeline, tracking each step of the data’s journey so you always know where it has been and is going.     ➤ Data Versioning: Data evolves as we update project plans. Versioning keeps track of every change so you can revisit previous versions or understand shifts when needed.     ➤ Data Provenance: Provenance is the backstory—understanding where your data originated helps you assess its trustworthiness and quality.     ➤ Data Lifecycle Management: Data doesn’t last forever, just like projects have deadlines. Lifecycle management ensures your data is used and protected appropriately throughout its life.     ➤ Data Profiling: Consider profiling a health check for your data, spotting potential errors or inconsistencies before they affect business decisions. When we get these pillars right, data goes from being just a tool to being a trusted ally—one you can count on to help make decisions, drive strategies, and ultimately support growth. So, what pillar would you focus on to make your data more trustworthy? Cheers! Deepak Bhardwaj

Most brands say they want to be seen as thought leaders. But few have a system for actually earning that authority. Here’s the 5-step process I use to help brands go from “just another voice” to trusted authority—using original research and content people actually pay attention to 👇 STEP 1: Start with data-driven insights Nothing strengthens credibility like unique, data-backed insights. I work with brands to conduct original research that resonates with their target audience, positioning them as a source of valuable, hard-to-find information. → Identify relevant, high-impact research topics → Use data to answer pressing questions in the industry STEP 2: Create a powerful narrative Good research is more than just numbers. To stand out, we craft a compelling story that makes the data memorable, meaningful, and actionable for the audience. → Translate complex findings into clear, impactful messages → Use storytelling to engage, educate, and build trust STEP 3: Share insights on the right platforms Where and how you share matters. Choose channels and formats that put the research in front of decision-makers and influencers, ensuring it reaches the audience that needs it most. → Determine high-ROI channels and platforms → Tailor content formats for different stages of the buyer journey STEP 4: Build long-term credibility Authority isn’t built overnight, and maintaining it requires a steady flow of fresh insights. To keep the brand top of mind, we design a plan for consistent research investments—whether annually or quarterly—releasing findings that reinforce the brand’s expertise over time. → Develop a research cadence to keep insights relevant and impactful → Repurpose findings across blogs, social posts, and webinars, building authority with each new study STEP 5: Measure and refine Tracking results is essential to understanding what works. By analyzing engagement, lead generation, and brand sentiment, we refine the strategy and keep enhancing the brand’s authority. → Track key metrics like brand sentiment, engagement, and lead impact → Adjust strategies based on audience response and goals With this process, brands can build real, lasting authority—one valuable insight at a time. #BrandAuthority #ThoughtLeadership #ContentMarketing

“When considering internal data or the results of a study, often business leaders either take the evidence presented as gospel or dismiss it altogether. Both approaches are misguided. What leaders need to do instead is conduct rigorous discussions that assess any findings and whether they apply to the situation in question. Such conversations should explore the internal validity of any analysis (whether it accurately answers the question) as well as its external validity (the extent to which results can be generalized from one context to another). To avoid missteps, you need to separate causation from correlation and control for confounding factors. You should examine the sample size and setting of the research and the period over which it was conducted. You must ensure that you’re measuring an outcome that really matters instead of one that is simply easy to measure. And you need to look for—or undertake—other research that might confirm or contradict the evidence. By employing a systematic approach to the collection and interpretation of information, you can more effectively reap the benefits of the ever-increasing mountain of external and internal data and make better decisions.”

If you aren't using Reasoning and Deep Research daily - you need to start today. Deep research is a powerful tool that businesses can use to gain a competitive edge, optimize decision-making, and uncover hidden opportunities. Here are ways businesses can leverage deep research and reasoning to their advantage: 📌 Market Analysis & Trend Prediction - Identify emerging trends before competitors. - Understand shifting consumer preferences through sentiment analysis. - Forecast industry disruptions and plan accordingly. 📌 Competitive Intelligence (🎥 below breaks this one down) - Analyze competitors’ strategies, pricing, and product launches. - Identify gaps in the market that competitors haven’t addressed. - Reverse-engineer successful marketing campaigns and tactics. 📌 Customer Insights & Behavioral Analysis - Understand what truly drives customer decisions beyond surface-level feedback. - Use deep-dive research on customer complaints to improve satisfaction. - Segment audiences based on behavioral patterns, not just demographics. 📌 Product Development & Innovation - Identify unmet needs through ethnographic research and user testing. - Analyze patent filings to stay ahead of innovation trends. - Use scientific and technical research to improve product materials or designs. 📌 Pricing Optimization & Revenue Strategy - Analyze pricing psychology and competitors’ elasticity models. - Use conjoint analysis to determine which product features customers value most. - Conduct deep pricing research on customer willingness to pay. 📌 Supply Chain & Vendor Optimization - Research alternative suppliers for cost savings and sustainability. - Analyze geopolitical risks that could impact supply chains. - Use blockchain data to verify ethical sourcing and compliance. 📌 Mergers, Acquisitions & Partnerships - Perform due diligence on potential acquisitions to uncover hidden risks. - Analyze company financials, market position, and employee sentiment. - Research cultural fit and integration risks before making a deal. 📌 Marketing & Advertising Effectiveness - Conduct A/B testing research beyond surface-level data. - Use neuromarketing studies to optimize ad creative and messaging. - Analyze long-term brand sentiment rather than just short-term ad clicks. 📌 Expansion & International Market Entry - Research cultural and legal differences before entering a new country. - Identify local consumer behaviors and preferences. - Analyze macroeconomic trends that could impact expansion success. It isn’t just about gathering information—it’s about extracting insights that drive strategic decision-making. Businesses that invest in rigorous research don’t just react to change; they anticipate it and capitalize on it before anyone else does.

Do you want to ensure your stakeholders use your data results? Here is how to make sure your results drive action: 1. 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗡𝗲𝗲𝗱𝘀: Start by truly understanding what your stakeholders need. Ask them about their goals, challenges, and what decisions they hope to make with your data. Tailor your work to align with their priorities.     2. 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝘆 𝗬𝗼𝘂𝗿 𝗠𝗲𝘀𝘀𝗮𝗴𝗲: Avoid overwhelming stakeholders with technical jargon and complex statistics. Instead, compress your findings into clear, actionable insights. Use visuals and adjust your language to make your message stick.     3. 𝗣𝗿𝗼𝘃𝗶𝗱𝗲 𝗖𝗼𝗻𝘁𝗲𝘅𝘁: Explain why your results matter. Show how your analysis or models impact the business and support decision-making. Connect the dots between your data and the stakeholder's objectives.     4. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗔𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀: Don’t just present data, but offer concrete, actionable recommendations. Clearly outline the steps stakeholders can take based on your findings. This bridges the gap between data and business outcomes.     5. 𝗘𝗻𝗴𝗮𝗴𝗲 𝗶𝗻 𝗙𝗼𝗹𝗹𝗼𝘄-𝗨𝗽: Stay involved after presenting your results. Schedule follow-up meetings to discuss implementation and address any questions or concerns. Continuous engagement ensures your insights are not only understood but also used to drive business decisions.     6. 𝗕𝘂𝗶𝗹𝗱 𝗧𝗿𝘂𝘀𝘁 𝗮𝗻𝗱 𝗖𝗿𝗲𝗱𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Consistently deliver accurate and valuable insights. Building a reputation for reliability and expertise makes stakeholders more likely to trust and use your results. By focusing on these strategies, you’ll ensure your results are not just heard but also put into action, driving real impact in your organization. Thoughts? ---------------- ♻️ Share if you find this post useful ➕ Follow for more daily insights on how to grow your career in the data field #dataanalytics #datascience #stakeholdermanagement #datadrivendecisions #careergrowth

Want to transform business outcomes? Make sure you can trust your data. Seriously. Accurate data storytelling ensures crucial insights are trustworthy and actionable. Because the gap between inaccurate data and informed decision-making can severely impact your ability to respond to market changes, optimize operations, and drive growth. And traditional data approaches using aggregated data are inaccurate and misleading. Plus, they may overlook key patterns and trends due to inaccuracies. Here’s how to tell your data stories with greater accuracy and improve decision-making: ➡ Trust Your Data: Establish robust data governance to ensure the accuracy and integrity of your data. Trustworthy data is the foundation of every powerful data story. ➡ Ensure Data Accuracy: Regularly validate and cleanse your data to eliminate errors. Accurate data leads to reliable insights that drive confident decision-making. ➡ Provide Real-Time Access: Enable real-time data access to ensure your insights are always based on the most current information. This keeps your data stories relevant and timely. ➡ Simplify Complex Data: Break down complex datasets into clear, precise visuals. Simplifying your data helps stakeholders grasp critical insights quickly and accurately. ➡ Highlight Key Trends: Focus on presenting accurate trends and patterns that are backed by reliable data. This ensures that your stories lead to actionable insights and informed decisions. Effective data storytelling isn’t just about presenting data—it’s about conveying a narrative that is accurate, trustworthy, and drives strategic decisions for business growth. Transform your data into accurate stories that inspire success. ➡ Be sure to follow Incorta (https://lnkd.in/gvbK5gmW) on our company page, to see how we get you decision-ready data faster, simpler, and at scale. ➡ Got insights on Incorta or data analytics? Ask to join our Incorta User Group Community (https://lnkd.in/gjWNSJZH). #digitaltransformation #finance #cfo #data #businessanalytics #genai

The Importance of Data Trust in Data-Driven Decision Making. Improve decision-making in 5 key areas: 1. Data Accuracy Accurate data is the foundation of good decisions. So, ensure it: • Validate data at the point of entry, or as far left as possible. • Remove duplicate records. • Regularly audit your data sources. • Use automated tools to spot errors. 2. Data Completeness Incomplete data can lead to flawed insights. To avoid this: • Ensure all required fields are filled. • Integrate data from various sources. • Regularly update your databases. • Track data lineage to understand its origin. 3. Data Consistency Consistent data ensures reliability across systems. Here’s how to maintain it: • Standardize data formats. • Use consistent naming conventions. • Synchronize data across platforms. • Implement data governance policies. 4. Data Freshness Timely data is crucial for relevant decisions. Make sure to: • Set up real-time data feeds. • Update your data frequently. • Monitor data latency. • Use time-stamped data entries. 5. Data Relevance Relevant data drives meaningful insights. To achieve this: • Align data collection with business goals. • Focus on key performance indicators (KPIs). • Regularly review data for relevance. • Discard obsolete data. There you have it - 5 key areas to ensure data quality. I think about this quote often: "Without data, you're just another person with an opinion." —W. Edwards Deming Many organizations struggle with poor data quality, leading to misguided decisions. Ensuring high data quality is essential for making informed, data-driven decisions. Good news is you don't have to do it manually anymore. Help is available thru Data Quality and Observability solutions that build trust in data and data teams. Be confident. Trust your data. Lean on partners to help you build that Trust. #datatrust #dataobservability #datacatalog #datagovernance