How do you balance the need for accuracy and timeliness when delivering business insights?

I have a simple mantra with my team... it is better to be "quick and right" than to be "fast and wrong." Knowing and understanding your data and validations is crucial.

It sets the stage for solving issues effectively. It involves figuring out what the problem is, who it affects, and how it fits into the larger picture. For example, let's say a company wants to keep more customers shopping on their website. Understanding this problem means looking at why customers might leave, what the company can do better, and what's important to the people making decisions. By understanding these things, the company can come up with specific ideas, like offering personalized deals or improving how they help customers. These ideas are meant to solve the issues identified and make both the customers and decision-makers happy, ultimately helping the company keep more customers shopping.

Totally agree with the view 💯. Without having a clear idea of the requirement and outcome expected from the client, we can't solve the pain points of the clients.

Balancing accuracy and timeliness in business insights requires finesse, strategy, and understanding of the evolving landscape. To achieve this, businesses should define insights' purpose, consider context, embrace agile analytics, invest in data quality assurance, use visualization, prioritize data security, differentiate strategic planning, assess potential consequences, communicate confidence, and invest in scalable infrastructure.

Both are important. To speed things up , make it a habit to know the business inside out, so that you know what are the key requisites and be targeted in your solutions. A lot of time tend to be wasted when one cannot comprehend the business needs.

Para poder fornecer insights é de extrema importância entender e fazer parte do negócio, só assim, será possível opinar e trazer soluções com assertividade. Entender do negócio vai além de olhar a parte técnica, se faz necessário ter relacionamento e observar como as grandes lideranças agem e tomam decisões.

Choosing the right data source is a big task, but here are some sources one can consider - - Check for the publically available data from government websites or local authorities - Trustworthy news articles or press releases e.g. prnewswire, businesswire etc. - Data sources from international organisations e.g. World Bank, United Nations etc. - And lastly, paid databases, which are always a good source Hope this helps💯

Go for publicly available datasets by established organisations first eg world bank indicators. These data are official, have been cleaned and credible. See what is available and how it can be used for your analysis before going for private data.

In my experience, streamlining the data collection and analysis process can have the most impact on being able to deliver insights more quickly without sacrificing accuracy. Automation tools and techniques such as data visualization, machine learning, and natural language processing can help to speed up the analysis process while actually improving accuracy. Continuous monitoring of data sources can help to identify data quality issues and anomalies quickly, enabling timely action to address any issues. Implementing a real-time data monitoring and alerting system can help to catch any issues immediately and address them before they cause delays.

Make sure key stakeholders like sponsors and senior management has "skin on the game". Quantifying and reporting the correct benefits (goals) need to be addressed in a top - down approach.

Absolutely, validating and communicating findings is crucial. It involves thorough checks on assumptions, rigorous testing of results, and ensuring clarity on conclusions. Documenting data sources, methods, and limitations is key for transparency. When it comes to communication, tailoring your message to the audience is essential. Using clear and concise language ensures that your insights are easily understood. Presenting findings in a compelling and actionable way adds impact. It's also important to anticipate questions, feedback, and objections—being prepared to explain and defend insights enhances the credibility of your work. Keep up the great work in ensuring the robustness and effective delivery of your findings!👍

What worked for me is to make this step a continuous feedback loop rather than a final step. Validating assumptions at the problem understanding step, reviewing available data at the collection step, this will help in refining the request accordingly.

This is a very important one for me. One must always have a scope of the task i.e. time that will take to complete the task. It will give an idea to distribute the task into smaller parts and one can effectively utilise the resources available to work on each parts in a timely and effective manner.

Certainly! Remaining flexible and adaptable is key as business needs evolve. Continuously monitor the business environment and track the performance of your insights. Stay open to new data sources, methods, and perspectives that can enrich your analysis. Be prepared to pivot or iterate your analysis if the business landscape shifts or new opportunities and challenges emerge. This dynamic approach ensures that your strategies stay relevant and effective in the ever-changing business landscape. Keep up the agility!

Dont be afraid to take a step back, restrategise, or even drop some parts of your analysis altogether when circumstances change especially in the innovation and technology world where everything is happening very fast. One example for me is crypto. Always think how your insights can contribute to the team/organisation’s objectives. When it no longer does so, be ready to adapt/drop.

Poder da adaptabilidade e resiliência fazem parte deste processo. Nem tudo é ganhar ou perder, sim trazer possíveis soluções mediante ao momentos difíceis e conflituosos.

I agree, but while timeliness is essential, accuracy should always be the top priority when delivering business insights. Rushing to deliver insights without ensuring their accuracy can lead to poor decisions and negative business outcomes. To ensure accuracy, data sources should be verified, and any data quality issues should be addressed before delivering insights.

Be clear on what your insights are telling, and not telling. State the “known unknowns” and why you’re unable to do a comprehensive analysis now, and what you’d require to start that. This will show that you’re strategic. You’re aware of the issues, current limitations and steps to address them.

Have you ever wondered why business insights often miss the mark? It's not just about data or methods, it's about prioritizing what really matters. Forget perfection - focus on the real issues that drive decisions. Time waits for no analyst.