How can data solve communication problems in business?

Whenever there is deadlock among the top level decision makers, then the right data becomes a game a changer. It’s always difficult to take big and novel decisions at big corporations, and majority of boards are usually in favour of conventional methods and ways. The relevant data - and its right interpretation - leaves no room for personal choices, and leads the management teams to the right and pragmatic choices during such times.

Identificar e medir lacunas e problemas de comunicação é essencial para o sucesso de qualquer organização. A chave está em utilizar dados confiáveis como bússola. Ao analisar métricas de comunicação, como taxas de resposta, feedbacks e engajamento, podemos mapear eficientemente as áreas de oportunidade. Dados confiáveis revelam não apenas as lacunas, mas também a eficácia das mensagens e a percepção da equipe. Ao incorporar uma abordagem baseada em dados, as organizações podem ajustar suas estratégias de comunicação, promovendo um ambiente mais transparente e produtivo. A análise de dados confiáveis é a chave para uma comunicação organizacional eficaz. #ComunicaçãoEmpresarial

Here are few ways data can solve communication problems in business: *Data can be used to avoid communication bottlenecks by analyzing internal communication data, such as email exchanges and Minutes. Based on this flow of information can be streamlined * Customer communication gaps can be identified proactively by measuring the effectiveness of communication based on KPIs like CSAT, demographics and behavior patterns. Based on this necessary adjustments can be made to improve communication strategies. *Data from various sources like social media, can help to anticipate customer needs, proactively address their concerns, provide personalized communication, thereby enhancing customer satisfaction and loyalty.

It's important to understand the process by which data leads to wisdom, before beginning analysis of any kind. Data is just the bits and the bobs; it has characteristics but little shape, and it is not an explanation unto itself. Cleaning up the data turns it into information, giving it a usable shape. Taking that shape and transforming it into a visual medium creates the story found in the data. At this point, your work as the analyst is done. Your hope is that your audience will then translate the information you've provided into knowledge which will inform their decisions. And if you're very very lucky, a few may incorporate that knowledge into their worldview—and this is when knowledge becomes wisdom.

It can provide you with insights, feedback, and guidance on your audience's preferences, needs, and expectations, allowing you to tailor your communication style and content.

Data is a tool that can be used for good or for ill, just like any other tool out there. You can use it like a scalpel or a sledgehammer, but finding the happy medium between those two extremes is where you'll have the most success communicating the message. (Sometimes the extremes are necessary, but those use cases are rare.) The last thing you want to do is to hold information gleaned from data analysis like trump cards, only to be used to win debates. Information should be shared freely. Data transparency is crucial to maintaining a healthy conversation about one's business.

Los ''datos'' son muy relevantes a la hora de comunicar, ya que tener la información adecuada de que tipo de audiencia, como edad, genero, interés, comunicada, esta frente a ti permite enfocar y dirigir adecuadamente lo que queremos transmitir, llegando en muchos caso a conectar emocionalmente de manera adecuada, empática con tu audencia.

Minha experiência confirma a importância vital de incorporar dados em mensagens orientadas por dados. Ao apresentar um projeto a investidores, o respaldo em dados concretos fortaleceu nossos argumentos e facilitou a compreensão do potencial do empreendimento. Ao criar histórias envolventes, combinei narrativas emocionais com dados impactantes, destacando resultados mensuráveis. Essa abordagem não só gerou empatia, mas também transmitiu uma mensagem poderosa sobre a eficácia comprovada de nossos produtos. Em resumo, integrar dados em mensagens não apenas estabelece credibilidade, mas também aumenta o envolvimento do público, conduzindo a resultados mensuráveis e construindo relacionamentos duradouros.

Utilizing data-driven messages significantly enhances the efficacy of communication. Particularly within the decision-making processes and the evaluation of internal procedures, data assumes a pivotal role. Comprehensive consideration of data from diverse perspectives is imperative for ensuring the optimal functionality of systems. Whether approached from a technical, operational, or analytical standpoint, effective communication necessitates the inclusion of pertinent points relevant to each of these perspectives.

Data is only information until it is translated into a compelling story for the audience. As we learned from Chip Heath and Dan Heath in their book Switch, you don't need power to have influence: you simply need the data and an impactful story that shows the value and need discovered in the data. This comes with a massive caveat. You won't always win everyone over, even if you have the most compelling data. For example, take the remote work situation. Corporations learned that remote work boosted productivity, increased profitability, and impacted the climate positively. Yet in spite of that data, they are compelling their employees to return to the offices. Sometimes the audience doesn't care. That isn't your fault.

In order to provide objective insights on employee engagement, customer behaviour and market trends, data eliminates ambiguity and personal biases with its ability to cut through them. It eliminates the need for speculation by providing concrete evidence, so paving the road for well-informed decisions and transparent communication. It is possible to adjust your message to resonate with diverse groups of people if you conduct an analysis of the demographics and preferences of your audience. Data enables you to communicate in a language that is understood by both your employees and your consumers, so increasing your influence and establishing trust.

A different approach to data-driven story telling can be seen in actuarial/ insurance claims. With data obtained, rates for policies can trend as a correlation between many factors, like ages, gender, weight, height, medical history and such. A good news story would be something akin to 96% of claimants successfully paid out in claims process. Then this data can be used in superannuation or other sectors accordingly where similar information or vectors are obtained to differentiate cohorts of member base and again help with creating products to improve quality of life into retirement (superannuation example).

Herein, it is imperative to consider implications from behavioral economics and more specially dual-processing theories. The literature allows us to understand how individuals process information and why they tend to fail to accurately interpret probabilities that refer to measures of uncertainty. Kahneman and Tversky (1974) have outlined the concepts of heuristics and biases. They also highlight that individuals tend to lack the ability to correctly apply statistics to everyday-situations, e.g. due to the base rate fallacy. Communicating data is therefore more than creating a compelling narrative or visualization. It’s also a matter of psychology and framing techniques.

A data-driven culture requires two crucial things: transparency and listening. Many companies who insist they are a "data-driven culture" are pretty good at the transparency piece: they do routine surveys of their workforce, share the data out, and talk about the insights found. But these same companies don't always listen to what the employees are telling them through the data. When this happens, employees feel ignored and demoralized. Worse still, if employees know they have been telling the company one thing but don't see it reflected in the insights, they may question the transparency altogether. This leads to lack of trust, and that's an even worse problem.

Eine Northstar-Metrik unterstützt die datengetriebene Kulturentwicklung im Unternehmen. Der Vorteil des Northstar ist die Komplexitätsreduktion auf eine wesentliche Kennziffer, an der sich das Unternehmen mit seiner Leistung ausrichten kann. Die Kultur und Zusammenarbeit entwickelt sich jedoch nur mit dem Handeln. Das bedeutet, der Northstar braucht 100% Sichtbarkeit und Bekanntheit im Unternehmen, um integraler Bestandteil des täglichen Tuns zu sein. Jeder Unternehmensteil wiederum sollte diesen Northstar auf sein Verantwortungsgebiet runterbrechen - in weitere Performance-Ziele, die wiederum auf Daten fußen. Sind diese realistisch und motivierend, entwickelt sich die datengesteuerte Kultur wie von selbst.

Data is important but it is also always changing. Make sure you have the most up to date information or if not, be sure to be clear and transparent if the data is limited or caters to a specific group of people. If you make a mistake reporting the data, make sure to inform the group or give credit where it’s due if someone manages to point it out.

Compartir la información de manera trasparente, honesta y real, permiten fomentar una cultura de colaboración, por ejemplo: en una empresa de comercio internacional, compartir los KPIs o resultados de la gestión comercial de cada ejecutivo puede generar compromiso de los demás así como motivación por alcanzar los objetivos asimismo promueve un espíritu competitivo sano lo que contribuye en el logro de los objetivos de la empresa.

Data and emotional influence are two side of the same coin. You can’t influence all of your customers with just one or the other. It’s important to make the customer feel good about their purchase, but it’s also important that they can justify it with data. Data backs up the emotional response, creating a powerful combination that will draw your customer in and make them feel at peace and confident with their purchase.

Unique Ways Data Can Solve Communication Problems in Business: 1. Sentiment Analysis in Real-Time: Analyze customer feedback (emails, chats, social media) to detect negative sentiment and proactively address concerns before they escalate. Imagine a bot detecting an upset customer during a chat and instantly prompting a human agent to intervene. 2. Data-Driven Storytelling: Combine data with visuals and narratives to create impactful presentations and reports that resonate with audiences. Use infographics, charts, and even AI-generated narratives to present data in a digestible and engaging way.

Transparency is really important, especially if you've been touting a particular data point as a key fact to support your project. In one of my previous jobs, my team and I spent a year and a half saying that the vast majority of people who performed searches on the website were NOT logged in, when in fact, the opposite was true. When we learned we were wrong, we tracked our error back to the source and were properly horrified at how such a small misunderstanding about how the analytics system worked could cause such a major error. But it's better to move forward with the error admitted and the corrected information disseminated as widely as possible. You don't have to assign blame; you just collectively take a deep breath and move on.