Here's how you can enhance your problem-solving approach with data and analytics.

Here is something I have experienced: We all know the need for relevant, high-quality, and accurate data. You don't need to work for big data companies to see how industries are doing. Using a service company's dataset is a gold mine. For example, analyzing printer usage data can reveal which industries are thriving and which are slowing down with multiple data points in each industry. This allows us to tailor different marketing strategies effectively and do collaborations with rising industries. Increasing profits close to 200%. I call that a data driven win.

La recopilación de datos de alta calidad es esencial para lograr un correcto análisis estadístico. Es por eso que es muy importante identificar las operaciones estadísticas que estamos trabajando, ya que pueden ser encuestas, censos o registros administrativos. Esta identificación es fundamental para comprender la metodología estadística y interpretación de los datos.

Here are the key points about analyzing trends in data: 1. Techniques: Use analytical methods such as regression analysis and cluster analysis. Regression Analysis: Examines relationships between variables to uncover patterns. 2. Cluster Analysis: Groups similar data points together to identify trends. Insights: Reveals hidden patterns and insights not immediately apparent. 3. Predictive Power: Helps predict future outcomes and understand root causes. Strategic Advantage: Enables data-driven decision-making and effective solution development. 4. Competitive Edge: Keeps organizations responsive and competitive in dynamic environments.

Something I found useful, Always try to break down your trends per categories to be able to identify how trends are different or compared to each other , also consider always using rolling Averages to eliminate noises and identify if there is a change happening or it’s just regression to the mean Use Always ML like Regression to identity what are the key factors that effects your data and how important is it to be able to make a model that can increase your visibility about changes and improvements planed

I always find it usually about visibility of lines of KPIs to always visual two related to business KPIs to enhance your visuals like for example it’s important to show your unit sales but also how much returns , or showing sales alone with profit margins Also when using bars; if you have many categories always use horizontal bar , because it’s always Pareto principle works here and your first categories contributes to around 80% and it makes the scrolling experience better from up to down better than from left to Right

Always remember Data is not always everything, you need to effectively work and communicate with all people to understand how business is working, i always gets insights from my mates talking about how out product is performing and keep updates with all as Data may show you numbers and trends but with effective communication you would be able to make decisions and stories from decision makers

Embracing the mindset that AI can exponentially enhance aspects like communication, empathy, and active listening opens new vistas for problem-solving. By integrating data and analytics, we amplify our ability to understand complexities deeply. This fusion empowers us to discern patterns, anticipate challenges, and innovate solutions with unprecedented precision and empathy. It's about leveraging AI to augment our innate abilities, fostering deeper connections, and crafting solutions that resonate with profound understanding and impact.Through this synergy, we navigate challenges with a blend of human insight and technological prowess, ensuring solutions are not only effective but also resonate deeply with those we serve.