Wie können Sie die Datenanalyse nutzen, um effektiver mit Kollegen zu kommunizieren?

Adjust your communication to match the level of understanding of your audience and their interest in the data. Break down complex concepts into simpler terms. Minimize the use of technical language that might be confusing to your colleagues who are not familiar with the topic of discussion.

O conhecimento do seu público é fator primordial antes de iniciar o planejamento da apresentação, isto porque para se envolver o público necessita de conexão profunda com o tema apresentado, sendo assim é necessário investir em dados e estratégias personalizadas, para oferecer uma experiência certeira e marcante na análise de dados. Além disso, conhecendo seu público, é possível estabelecer uma comunicação eficiente através dos dados, definir uma estratégia e oferecer uma experiência marcante para essas pessoas.

Using data analysis can greatly enhance communication with colleagues by providing evidence-based insights, fostering better understanding, and supporting decision-making. Here are some ways you can leverage data analysis to communicate more effectively with your colleagues: Visualize Data: Presenting data in visual formats such as charts, graphs, and infographics can make complex information more digestible and engaging for colleagues. Use data visualization tools to create clear and visually appealing representations of your findings. Tell a Story: Instead of simply presenting numbers and statistics, use data analysis to tell a story that resonates with your colleagues.

Using data analysis enhances communication with colleagues. It provides evidence-based insights supporting ideas. Visualizing data creatively makes complex information engaging. Tailoring communication to the audience ensures clarity. Data helps anticipate objections, addressing them proactively. Storytelling with data adds depth and memorability. Ultimately, data analysis empowers effective communication, fostering collaboration and informed decision-making.

Wielding data analysis to communicate effectively with colleagues can be a puzzle. Because presenting data that doesn't resonate with them, might make your presentation fall flat. Understanding your colleagues is the key. Start with a deep dive into your audience. Who are they, and what makes them tick? Tailor your data analysis to match their expertise, interests, and expectations. For a technical team, dive into the nitty-gritty details and methods of your analysis. But with senior management, it's all about the big picture—highlight those key insights and recommendations. Know your audience, and your data will speak their language. It's not just about numbers; it's about crafting a narrative that resonates.

Delivering lackluster data analysis happens when the chosen format doesn't align with your purpose and message. Avoid! If your data isn't hitting the mark, it's probably not about the insights; it's about how you present them. Look closely into the purpose and message of your analysis. ➜ Is it about trends over time? Opt for a sleek line chart. ➜ Need to compare proportions? Cue the pie chart. ➜ Unveiling correlations? A scatter plot takes the spotlight. Different insights demand different formats. Select the one that speaks the language of your data and bolsters your argument.

Sempre importante lembrar que os números sozinhos tornam-se difícil de interpretação e sem uma análise correta, são apenas números. Sendo assim, é necessário organizá-los e saber o que seu público precisa enxergar, para que sejam organizados de forma que contem uma história. A apresentação de dados, é como contar uma história, que precisa ter enredo, ou seja, fazer sentido para o público, através de gráficos e/ou tabelas.

As ferramentas desenvolvidas podem ser aperfeiçoadas para uma melhor gestão do time. Em uma área comercial é possível gerenciar o time na realização de visitas a clientes, e na conversão de negócios que geração de resultados. Tudo depende do propósito da usabilidade da ferramenta e o meio de gerenciamento da mesma.

Complexity and vagueness is the enemy of a clear, concise story. Adding too much information and going off track will derail your message. This is true both from both a written and visual perspective. Focus on what is important, key learnings, and outcomes. Ensure that you back it up with data. Don't deviate from your story, graphs should convey what is most important as the narrative. Start with what you want to share, then share that information and end with a summary and key takeaways.

If you've ever presented data that left your colleagues scratching their heads, it might be because unnecessary complexities cloud the clarity of your analysis. Your insights might be gold, but they get lost in a maze of confusing elements. That's not the way to go. Step 1: ➜ After nailing the format, strip away the unnecessary layers. ➜ Simplify and clarify your data analysis. ➜ Remove anything that might distract or mislead your audience. Step 2: ➜ Clear labels, titles, legends, and scales are your allies. Choose colors, fonts, and sizes that elevate, not complicate. ➜ Enhance your data analysis without overwhelming your audience. Step 3: ➜ Embrace simplicity in language. Instead of drowning in jargon, use straightforward terms.

What do you REALLY want people to remember from that table? Giving people access to large pools of data might seem like a great way to show the bigger picture and be more persuasive and transparent, but it often gets the opposite effect. In a presentation, your audience may not have the time, attention span or knowledge required to take in all those details. So, realistically, what are 1 or 2 key concepts you'd like them to remember? Highlight those concepts clearly (increasing the size of the label, changing the colour, adding an arrow...) and remove as many other visual distractions as you can. "But what if someone asks for clarifications?" Keep a blank copy of your chart at the end of your slide deck as visual support for your Q&As

Consider noting the business question you are answering in the form of a simple sub-title. This helps set your audience up for success in understanding the accompanying visuals that answer this question. This is especially important when a presentation includes complex data sets that have been "sliced" in various ways to examine how different variables or factors interact. You may have several slides with similar "titles" but each have examined the data from a slightly different view point.

Nada supera o poder do básico bem feito. A simplicidade e análise de dados simples e clara, é sempre um excelente caminho. Muitas vezes a necessidade de muitas informações, apenas confunde o público e não torna clara as informações.

Choose the sources of data based on what the target audience is interested to understand and analysis about! Tell a marketing data analysis story with financial impact to an audience that understands and deals with finance, etc. Example- Here are the 5 KPIs considered from the recent marketing campaign we ran in the month of October. Based on the analysis, we figure that Financially we’d need a support of $5 million to conduct a pilot only to create an ROI of 6.88% in the next 2 upcoming quarters.

In my view, combining storytelling and data creates the ideal blend for crafting compelling, fact-based narrative that is both credible and relatable. Data counters or removes biases, offers an irrefutable source of truth. It serves not only to communicate outcomes or strategies but also lays the foundation for subsequent investment prioritization and strategic direction. Companies fostering a data-driven culture tend to outperform their competitors, deliver better customer experiences, and develop more effective business growth strategies.

Em vez de simplesmente apresentar números ou estatísticas isoladas, você organiza os dados em uma sequência lógica que segue uma linha de tempo ou uma progressão de eventos. Comece estabelecendo o contexto e apresentando um desafio enfrentado pela equipe, introduza os dados como elementos-chave da trama, destaque sua importância na resolução do problema e revele insights ao longo da narrativa. Ao utilizar personagens (representados pelos dados), a abordagem cria uma conexão emocional, facilita a compreensão e influencia a forma como a equipe percebe e utiliza os dados em suas decisões, culminando em um desfecho convincente com uma mensagem clara e ação sugerida.

Il faut en effet raconter une histoire pour "faire parler ses chiffres". L'enjeu n'est pas tant de savoir présenter des chiffres (les tableaux sont toujours difficiles à comprendre, ardus à lire, etc), mais plutôt de savoir quel message il faut faire passer pour choisir les chiffres qui permettent de l'illustrer. Et non l'inverse !

Transforme seus dados em uma história, que será contata para o seu público, com enredo, sentido e conclusão final e escolha a melhor maneira de contá-la ao público. No storytelling com dados é muito importante seguir passo a passo, onde primeiro você reúne os principais insights para analisar seus dados, pense no seu público e na sua audiência, escolha o formato da sua história, crie contextos, argumentos e o fluxo para sua história. Dessa forma, você transforma relatórios em narrativas e envolve seu público alvo.

I would recommend speaking with key stakeholders prior to starting analysis work to determine their end goal - what is the question(s) they are attempting to answer? Once the initial scope is built out, review this question against the scope to make sure requirements are still aligned or if additional research is needed.

Data Storytelling é a técnica que usa dados na criação de histórias que engajam e conectam com o público de forma mais efetiva.