Solution is evaluation. - Need to perform GAP analysis. - It is all about CQS --> Cost, Quality and Speed. - Evaluate your internal competency to bridge the knowledge gap (if any) - Document client's expectations with proper timelines + guidelines along with milestones. Documentation is the bridge between expectation and any data accuracy gap from solution. - Go with some factual analysis to understand the Data Quality issues. - Evaluate the gap of communication to understand data accuracy. Communication is the most important key in confidence building activity. - Put down any assumption and hypothesis if fail to get any clarity. - Finally if not convince, look out for new client and opportunities. World is full of opportunities.

In such situations active listening can play a good role in understanding what ghe customer is actually asking. Sometimes what the customer is asking if you are not paying attention to that can be unrealistic as well. Improve the areas that need some improvement and can be done in a better way. Work in a team with your customer so that you can understand the requirements in a better way. Following the data quality framework and keeping the cost in check and updating the customer of all possible drawbacks of upgrading or degrading the pipeline or the architecture. By doing that we can always come on a common ground with the customer.

This requires combination of clear communication, technical expertise, and stakeholder management skills. 1. Clarify the requirement and educate the client: Talk to the client and understand what "accurate" means and why they need this level of precision. Share industry standards as sometimes clients demand perfection because they lack understanding of the inherent challenges. 2. Expectations setting: Explain the limitations of the data or the process. Use concrete examples or past benchmarks to illustrate what level of accuracy is achievable within the constraints of time, technology, and resources. 3. Leverage Data and Tools: Provide technical insights into the tools or process you're using and explain how they ensure high accuracy.

Clarify Expectations: Engage with the client to understand the exact requirements and define realistic accuracy levels. Set Boundaries: Politely explain the limitations of available resources or data processing constraints. Offer Solutions: Propose alternatives like phased data delivery or enhanced reporting for improved accuracy. Educate on Trade-offs: Help the client understand the balance between time, accuracy, and cost. Document Agreements: Ensure all expectations and commitments are captured in writing to prevent misunderstandings later.

When facing unrealistic data accuracy demands, I focus on clear communication and practical solutions. I explain the limitations honestly, highlight industry standards, and propose achievable compromises that align with their goals. If necessary, I shift the conversation to business impact over perfection. It’s about managing expectations while delivering real value.

Unrealistic client demands for the data accuracy can be challenging, here's few strategies that can be effective, ~ Maintaining detailed documentation of accuracy and project deliverables. ~ Using advanced tools and methods for optimizing accuracy without adding excessive effort, that can enhance outcomes. ~ Helping clients understand the complexities of data collection, processing and analysis. ~ Suggesting realistic compromises, such as phased accuracy improvements and offering solutions that shows commitment while managing expectations. ~ Involving clients in defining data accuracy benchmarks that are meaningful and feasible to achieve.

Below would be my approach- 1. Start by setting clear, realistic expectations aligned with industry standards, emphasizing the potential risks of unattainable accuracy goals. 2. Data-driven insights to demonstrate the feasibility of your approach. 3. Engage in transparent discussions, educating clients on the limitations of data collection and analysis. 4. Offer practical alternatives, such as focusing on actionable trends rather than perfection. 5. Document agreements to manage accountability and ensure alignment.

🔹 Be upfront about what’s achievable based on current standards. 🔹 Explain risks and limitations clearly to avoid surprises. 🔹 Offer realistic solutions that meet their goals halfway. 🔹 Use data or examples to back your points and build trust. 🔹 Focus on solutions, not the pressure