Your team is focused on short-term gains. How can you ensure long-term Business Intelligence success?

BI means strategy , analisys and results. Considering thoses principles, we can define strategy alignment as a goal to achieve long therm results, what is posible with a multidisciplinary team, engaged on the same vision.

Es imprescindible que los equipos de data entiendan el negocio y sus palancas para lograr sostenibilidad en el tiempo deben de focalizar 3 cosas: 1) Ejecutar simple y con sentido… no hay que buscar asombrar para resolver temas sencillos que el negocio requiere con urgencia 2) Innovar e investigar… el mundo de los datos es amplio y los equipos deben de estar buscando nuevas formas de datos y tipos de análisis que aporten al negocio 3) Equivocarse rápido y barato… es importante reconocer rápido un error y rectificar el proyecto o al equipo… la resiliencia gana partidos

Long term BI is the task of strategic ldrship . Team goals are aligned by managers and team leaders . Regular feedback n analysis of broad vision or goals will keep team focused on long term BI

In my opinion, Data Analyst on Long-Term BI Success: Aligning Goals Short-term wins are great, but for long-term BI success, we need aligned goals! Understanding how BI supports the organization's long-term vision helps us prioritize projects that build a foundation for future growth, not just instant gratification. This fosters team buy-in and ensures BI delivers lasting value.

In my experience getting a dashboard built, providing adhoc insights, or even creating a self service tool will also be short-term oriented if you're not including the end users and their vertical management. Ensuring the end users are involved and their management are involved in the requirements gathering will help align the Short-term goal of the BI team with he long-term goal of the end users and their management. It is also very important to iterate with the end-user and their management during the initial feedback cycle and UAT. The tricky part come with managing scope creep and ensuring the project isn't derailed Everytime you iterate with he end user and their manager. Feel free to reach out for some useful tips around that.

To ensure long term Business Intelligence success, it's crucial to focus on data quality. Reliable and accurate data serves as the foundation for meaningful insights and strategic decisions. Invest in data cleansing, validation processes, and regular audits to maintain high quality data. This commitment to data integrity will help your team move beyond short-term gains and build a good BI framework that supports sustained growth and informed decision making. By prioritizing data quality, you set the stage for long term success in your Business Intelligence efforts.

In my View, Data Analyst on Long-Term BI Success: Data Quality Data quality is king! For lasting BI success, prioritize accurate, complete, and consistent data. Invest in data governance, cleansing, and management tools. Remember, good BI hinges on reliable data for strategic decisions.

Ensuring high data quality requires strong data management practices, regular data audits and continuous monitoring. Investing in data management tools and training employees can help maintain data quality in the long term.

Invest in Scalable and Flexible BI Solutions: 1. Choose Scalable Tools: Invest in BI tools and technologies that can grow with your organization, ensuring they can handle increasing data volumes and complexity over time. 2. Promote Flexibility: Encourage the adoption of flexible BI solutions that can adapt to changing business needs and technological advancements. This helps future-proof your BI infrastructure.

This effort should be done long before the BI team gets involved. Many times have I had clients that had BI built on data they "didn't fully trust" but would "get them pointed in the right direction". This mistake is a core issue with most companies today. They are to eager to pull the insights without ensuring the data is quality. Some lack the budget or want to use budget to ensure the foundation of their Data Operations is properly established before diving into the data.

Finally it’s always about how much is used and how can the workforce be enticed to use. Organisation should invest in persons who can articulate the value to the workforce, provide practical examples, demonstrate real capability to create the confidence in the workforce, who then are inclined to try the same. Building champions within groups also helps since the teams look up to the actions of their leaders and often work to emulate them. This reaching success at adoption. Be human and not simply enforcers and transactional.

For Data initiatives to succeed in the long term and be adopted by clients, it is crucial to involve them in the creation and development of machine learning models or data dashboards.

In my opinion, Data Analyst on Long-Term BI Success: User Adoption Don't just build BI, get people using it! User-friendly tools, training, and clear value propositions are key for long-term adoption. Foster a data-driven culture by showing how BI empowers better decisions.

This ties back to ensuring the end user is involved from the onset of the initiative. Would you rather use a tool that was made by some team you've never interfaced with who has never held your role Or Would you rather have insight and input to building that tool?

Training and constant use of BI tools are essential for the evolution of your knowledge, and always share so that it expands even more.

In my opinion, Data Analyst on Long-Term BI Success: Continuous Learning BI is ever-changing! To stay ahead, prioritize continuous learning for your team. Encourage training, conferences, and keeping up with trends. A learning team leverages BI for lasting success.

Estar atento as constantes mudanças, é fundamental quando se trata de Inteligência de Negócios, afinal, é um conjunto de processos e não uma ferramenta. Nos dias atuais, vejo que o Dashboard não é mais suficiente, a informação precisa estar cada vez mais rápida e mais na palma do mão do cliente. Os clientes querem interagir e fazer perguntas aos dados, então combinar a estrutura de dados com IA, é a tendência. Sabemos que isso, não é a realidade de 90% das empresas, mas é o futuro das soluções de BI.

Tech changes New features, bells, whistles are added Some time ago the whole tool moved from pulling only excel to the non physical data center in the sky. The question is do you want to stay in BI or transition to a role that doesn't require constant learning? Unlikely you're in BI. Those that know me know what's coming next. Learn prompt engineering and Gen AI. We are on the cusp of massive change in our roles. Early adopter will have and advantage over the rest. Take the time download the app and just start playing. Give yourself an advantage over those that wait. Send me a message if you'd like some guidance. It's scary to dive into to at first, yet very quickly you can be more productive in your personal and professional lives.

Continuous learning is essential to ensure the long-term success of Business Intelligence (BI). It is advisable to motivate your team to remain abreast of the most recent BI trends, tools, and technologies. Regularly review and update your BI processes based on new insights and advancements. By fostering a learning environment, your team will be better equipped to adapt to changes and drive sustained BI success.

Ninguém sabe tudo e provavelmente nunca saberá! No entanto isso não é motivo para deixar de crescer e evoluir, pois conhecimento é necessário e muito valioso. Neste ponto, conhecimento nunca pode ser tratado como despesa e sim como um valioso investimento.

In my opinion, Data Analyst on Long-Term BI Success: Invest Wisely Don't just buy for short-term! Invest strategically in scalable BI tools. Consider future needs and choose solutions that grow with your business, ensuring lasting value from your BI investment.

Let us take the example of TCS to understand the short-term and long-term goals. Achieving Quick Wins Initially, TCS focused on achieving quick wins by improving its internal reporting system. By leveraging Power BI, TCS was able to create interactive dashboards that provided real-time insights into operational performance. This immediate enhancement allowed managers to make data-driven decisions, significantly improving efficiency and productivity across the organization. Long-Term Scalability and Integration TCS didn’t stop at these quick wins. Recognizing the need for scalable solutions, TCS implemented a comprehensive data analytics strategy that integrated various data sources, including those from cloud and on-premises environments.

I have found checking in with he end-users from time to time also aids in adoption. They can be excited to use what you've created, then try to use it in their day to day role and it doesn't quite work as seamlessly as you demoed it. Documentation is out of the question to read because that'll take to long. Then sometime they don't want to/don't know how to reach out to you for further/reconstruction. Reach back out from time to time.it may just lead to secondary advancements of features and/or more work. I'm not taking about the same old thing either. Sometimes the later phases allow you to expand your career and do the cooler things like forecasting, data science, pytab, new or trending feature you might not have tried out yet, etc

I have discovered it is crucial not only to monitor progress but also to make necessary adjustments in cycled batches. These KPIs should align with the measurable business value defined during goal-setting. By integrating these KPIs into real business workflows within each batch of steps, you gain a true point to monitor all factors. If these measurements are not met by a batch, it triggers an audit to determine where the issue lies. Any adjustments, training, or corrections identified in the audit are then tested in the next batch execution. By establishing measurable factors, aligning them with business value, and integrating them into real workflows in batches, you create a robust framework for long-term BI success.

To ensure long term Business Intelligence success, start by aligning your team's goals with your organization's strategic vision. Prioritize data quality to build a strong foundation. Encourage user adoption through training and support, and foster a culture of continuous learning. Invest wisely in BI tools and technologies, and regularly monitor progress to adapt and improve. Always consider the broader impact of your BI initiatives on overall business growth.

Foster a Data-Driven Culture: 1. Encourage Continuous Learning: Provide ongoing training and development opportunities for your team to stay updated on the latest BI trends, tools, and best practices. This helps ensure the team remains capable of leveraging BI for long-term success. Embed BI in Decision-Making: Promote a culture where data-driven decision-making is valued and integrated into all levels of the organization. Encourage the use of BI insights to inform strategic planning and long-term business decisions.

1) Begin with a well-defined, proven BI goal supported by an executive committee. Ensure these goals are collaboratively agreed upon and tied to measurable business value. Validate their feasibility with a beta case study to confirm they are realistic and attainable. This is essential for everything else to follow. 2. Break Down Goals into Manageable Steps and Integrate into Daily Workflow Using Batches: This batch of steps should be integrated into daily operations using a cycle of [Define, Train, Incorporate, Validate, and Show Value] Where these batches can quickly Show Value achieved at each batch of steps. This process builds full assurance for everyone, increasing momentum and ensuring the success of the long-term BI goal.

One observation was that over a long period of time, new members formed part of the creation, feeding and maintenance of two stories, like this, we created a nucleus to begin directing as a whole, an enormous challenge that we reap great fruits.