What are the best ways to align BI solutions with your company's timeline?

In my experience, the BI transformation starts with the understanding of the current system: 1. How is the data managed currently? - Is it source to staging to a Data Lake/ Data Warehouse - Is it directly source to a database with custom tables 2. How is data quality ensured? 3. Is there a MDM in place? 4. Are there data governance mechanisms? A detailed analysis across these areas help in defining the gaps and what toolset will be needed to take the next big step in BI transformation. Then comes strategizing on KPIs/metrics for which BI is devised. Is there a Common Data Model which cuts across all functions? If not, the missing pieces here will be another starting point. Then data sourcing, ingestion, creating a lake/mart as reqd.

Define BI goals with a clear vision with your business strategy & identify KPIs that will track your progress towards those goals. This will help you prioritize the most important & urgent BI projects & allocate resources Assess your data sources & BI tools to create effective BI solutions, access to reliable, relevant, & timely data from various sources. Choose a right BI tool Create a BI roadmap: Is a document that outlines steps, milestones, deliverables of your BI initiatives. It helps you plan, communicate, execute your strategy in a structured & realistic way. You should create a BI roadmap that reflects your BI goals, KPIs, data sources & tools This will help you align your solutions with your company’s timeline & avoid scope creep

Here are a few points: 1) Understand the different datasets used within the organisation and assess current state. 2) Engage stakeholders to understand top insights that would add value to the business. 3) Align with Organisation timelines and objectives. 4) Define scope. 5) Choose BI solution and begin build. 6) Follow Agile processes to build and release. 7) Monitor and evaluate. 8) Continuous improvement with each release.

Desde mi punto de vista, las organizaciones deben empezar por dedicar algo de tiempo a analizar su situación actual en D&A en general, no solo en BI, si quieren establecer una base sólida para su crecimiento futuro. Hay diversas metodologías para ello, por ejemplo las 5 etapas de madurez analítica de Gartner. A partir de ese análisis de Gaps entre su AS-IS y el TO-BE deseado, la implementación de cualquier BI debería llevar a asociado el foco en la calidad de datos y la participación de negocio para superar las expectativas. De paso, les servirá para sentar las bases de una evolución constante de su plataforma BI, con AI y aprendizaje automático, que a mi entender es lo que realmente les permitirá adelantarse al mercado.

Na minha opinião, entender onde sua empresa está no momento é crucial. É como fazer um diagnóstico médico antes de prescrever um tratamento. Olhe para os sistemas de dados atuais, os processos de negócios, e as necessidades de informação. Identifique os gargalos, as ineficiências e as oportunidades de melhoria. Por exemplo, se você está usando planilhas Excel para relatórios, pode ser hora de pensar em algo mais robusto.

Aqui, é sobre saber para onde você quer ir. Defina objetivos claros e tangíveis para sua solução de BI. Pergunte-se: o que queremos alcançar com o BI? Melhorar as vendas, otimizar a produção, ou talvez aprimorar o atendimento ao cliente? E lembre-se, mantenha o escopo realista; não tente abraçar o mundo de uma vez.

Costumo aplicar metodologias para identificar as métricas essenciais, aquelas que realmente vão fazer com que o ponteiro do negócio mude. North Star metric é uma delas, uma dinâmica que faz você junto ao cliente repensar sobre quais métricas são essenciais; avaliando essa situação podemos definir melhor o que ser considerado no escopo de trabalho, com o foco de gastar energia e tempo no que realmente será efetivo para o resultado da companhia.

Goals has to be defined by the business leaders of the organization in terms of what they are aspiring to do with the BI systems. If they are willing to be just informed about the state of business then things are pretty simple for the BI team. But, if the aspiration is to understand the actionable points and correlated factors through powerful computation visualization then the organization has to be ready with the required timelines and the cost associated with the development of an efficient BI solution. There are some powerful tools in the market like QlikSense which empowers the BI team to produce great results if data engineers have provided them with a well organized data model and data mart to connect to.

Defining what you want to accomplish big picture is the best starting point. Then define smaller goals toward the big objective. Also, make sure to cross departmental goals so that you architect the solution in a way that it can be extended across the organization.

I found that once you understand the business objectives and have aligned your HR strategy, it can be tough to determine and map out what you need to include in your BI solution. I found that using a metrics library which could be a simple Excel spreadsheet or Word table with the following headings could give you a great picture and also make your engagement with the implementation partner a lot easier: 1)Metric 2)Required data and what is the source of the data (e.g. payroll system) 3) Calculation 4)Target/Benchmark 5)Tolerance levels - it helps when you define the tolerance levels up front especially if you want to use the BI tool to support exception reporting, so what is the highest high or what is the lowest low 6)Audience

Na minha opinião, esta é uma das etapas mais críticas atualmente. O mercado está cheio de ferramentas de BI, como Tableau, Power BI, Looker, Quicksight ou Qlik. Cada uma tem seus pontos fortes e fracos. A escolha depende das suas necessidades específicas, orçamento e compatibilidade com os sistemas existentes. Não se esqueça de considerar a facilidade de uso e a capacidade de integração.

Obviously the main elements are: scalability needed, implementation for a golive aligned with the company project goal, solution that takes in consideration innovation and company stability and finally the scope (if it is a reporting, analysis, what if scenarios, visualization or multidimensional)

An effective approach to aligning BI solutions with the company's timeline involves several fundamental steps. First and foremost, it's crucial to clearly define the goals and scope of the BI project, identifying specific time requirements. Next, selecting the appropriate BI solution should consider various aspects such as the type of data to be analyzed, the level of necessary customization, and integration with existing systems. Additionally, it's essential to evaluate the solution's ability to provide timely insights to support business decisions. Thus, choosing the right BI solution can ensure timely and effective analysis aligned with the company's temporal dynamics.

Penso que para escolher a solução de BI ideal é preciso identificar necessidades específicas do projeto, como: tipo de dados, requisitos de integração e segurança. Em seguida, pesquise e avalie diferentes opções de soluções no mercado, levando em consideração fatores como custo, escalabilidade, facilidade de uso e governança. É importante realizar testes pilotos das soluções para garantir que atendam adequadamente às suas necessidades e expectativas. Nem sempre o mais barato é mais conveniente, dê oportunidade para entender o que cada uma oferece adicionalmente. Se o seu foco for apenas montar um gráfico no Dashboard, não terá em plenitude uma visão do que é possível de ser entregável além do próprio Dashboard. Pense nisso.

In my opinion, almost all current BI systems have tools, security, integration, and costs that are quite competitive, so I would focus much more on the visualization solution. Understanding that a company has various data approaches, the BI solution must therefore be tailored to the company's analytical culture.

Implementar a ferramenta escolhida é só o começo, você precisa garantir que ela funcione como esperado. Muito importante: Teste com dados reais e cenários de uso. Outro ponto importante: veja como ela se integra com outros sistemas e treine sua equipe. A preparação e o treinamento adequados são essenciais para garantir a adoção pela equipe.

La implementación exitosa obviamente requiere entre otros, una escucha activa a los “stakeholders”, pero suele olvidarse que sin un partner que conozca las últimas innovaciones tecnológicas de una forma holística, con enfoque de conocimiento real de negocio, y no solo las que ofrecen unos fabricantes u otros, el proyecto no será lo abierto que debe ser para seguir siendo válido el trimestre que viene. Hay que pensar en plataformas más flexibles, porque me parece complicado disponer de un buen BI si no está soportado por una plataforma que cubra toda la cadena de Valor del Dato, y que incorpore la flexibilidad como ADN. Solo así la empresa podrá incorporar el futuro que requiera, huyendo de dogmas y proyectos que nacen caducados.

Prioritise data scope based on the intended outcome of the BI delivery - don't boil the ocean when needing to fit into a predefined timeline. When time is tight, get your hands on the data as soon as possible to mitigate risks of alignment between requirements and data.

Before selecting a BI tool, I'd recommend creating a dummy dashboard or a sample prototype that reflects the specific data metrics you intend to measure. Define the frequency at which these metrics should be monitored. It's crucial to visualize how these data points contribute to key business indicators, such as profitability, sales growth, cost optimization, expense reduction, sustainability improvement, or efficient use of ecological resources. While having information is straightforward, achieving tangible improvements in meeting goals requires a thorough analysis. Make sure your chosen BI solution aligns with this strategic approach for meaningful insights and actionable outcomes.

Essencial para a continuidade da solução de BI é o aprimoramento da observabilidade e governança. Isso inclui a verificação dos pipelines de engenharia e a adequação de acessos. Um ambiente de homologação bem estruturado é fundamental para validar o acesso, compreender métricas e homologar dados. Fundamental também é a análise crítica sobre se os dados fazem sentido e se estão preparados para escalabilidade e integração de novas funcionalidades, garantindo assim, a evolução constante e a aderência às necessidades do negócio

Uma vez que tudo está funcionando, não relaxe... monitore continuamente o desempenho da sua solução. Veja se está atendendo às expectativas, ajudando a alcançar as metas definidas. Esteja aberto ao feedback dos usuários e esteja pronto para fazer ajustes conforme necessário. #adaptabilidade

Continuously monitoring and evaluating the performance and impact of a BI solution is crucial for its effectiveness. Tracking KPIs and metrics against defined goals, baselines, and benchmarks provides insight into its performance and allows for course correction if needed. Analyzing user feedback and satisfaction helps identify areas for improvement and ensures the solution meets stakeholder needs. Reporting results and findings to stakeholders fosters transparency and trust, while celebrating achievements boosts morale and reinforces the value of the BI initiative. Testing solutions and striving to deliver the best outcomes to stakeholders are fundamental principles in the journey towards data-driven decision-making excellence.

You need to execute your BI roadmap and action plan, and monitor the progress and performance of your BI solutions using the KPIs you defined earlier12. You also need to collect feedback, measure the outcomes, and identify the areas for improvement and optimization of your BI solutions

Você precisa estabelecer um sistema de acompanhamento contínuo dos KPIs utilizando ferramentas de monitoramento automatizadas sempre que possível. No início pode parecer nebuloso, mas pense simples: colete regularmente o feedback dos usuários e conduza pesquisas de satisfação para identificar áreas de melhoria. Realize análises periódicas dos dados e compare os resultados com os objetivos estabelecidos, ajustando a estratégia conforme necessário. Comunique os resultados às partes interessadas e celebre os sucessos alcançados, incentivando o envolvimento contínuo e aprimorando a eficácia da solução de BI ao longo do tempo.

Revise suas métricas periodicamente de acordo com metas e resultados estabelecidas em seu planejamento estratégico. Raise the bar, como dizem os americanos.

Como habréis visto en mis artículos los que me sigáis, yo tengo claro que vivimos en un mundo donde el dato es rey y la IA es la reina. En este entorno competitivo, las empresas deben entender que la mejora continua de las soluciones de BI en concreto y de D&A (Data&Analytics) en general, ahora ya no es opcional, es esencial. Me atrevo a decir crítico para el negocio. Integrar Inteligencia de Negocio, al igual que integrar Inteligencia Artificial, no solo les ayudará a anticipar tendencias y mil posibilidades más, es que les va a transformar su negocio profundamente. Y por supuesto mantener su plataforma actualizada y alineada con sus objetivos empresariales, es la clave para, no solo competir, sino liderar su segmento/sector.

In the ever-evolving landscape of Business Intelligence, it's crucial to stay ahead of the curve. Just like a coach fine-tuning a team's strategy mid-game, we must constantly assess and tweak our BI tools. Remember, a static BI solution is as good as last season's playbook! Keep an eye on emerging tech and user feedback. It's not just about collecting data; it's about inspiring action and driving results. Stay playful with the data, but serious about the insights. Keep your BI solution as dynamic and forward-thinking as your business strategy!

This is actually one topic that is often overlooked. Don't ignore the need for evaluating the performance of you BI solution. This is not only about technology but usability and value for business.

I agree to @michael Andersen that this topic is often overlooked. Any solution inhouse or to client needs to follow a continuous improvement and risk mitigation path. Couple of times when you deliver 2x in quality then the scope gets redefined and hence the business engagement flavors more and more. Technology of course boost the BI dashboards but its upgradation on business logic accelerates the growth. After all only beautiful dashboards do not rock the show, its the continuous improvement to the business logic accompanied by BI , attracts the stakeholders.

Knowing what are goals that are needed for both short & long term Before jumping to BI , data collection is crucial, because of you are not collecting data then no tool can help Once that is done , to the minimal we they should have database & excel to start with Having an in depth analysis, before moving towards tool is essential, but an organisation should

Problem Statement: Identify your stakeholders and work with them to define a clear problem statement that is aligned to the business strategy. This problem statement must be your point of departure. Then you can pursue the source data experts to determine whether an ETL process is even required, you may find that the source data can be obtained easily and used to build reliable dashboards, unless the data volumes necessitate thorough incremental extraction and transformation processes to be put in place.

Aligning BI solutions with your company's timeline involves understanding business goals, prioritizing initiatives, setting realistic timelines, allocating resources, implementing agile methodologies, fostering collaboration, monitoring progress, and promoting a data-driven culture. By following these steps, you can ensure that BI projects are aligned with strategic objectives and deliver value within the desired timeframe.

The analytical culture of a company will be an important pillar for the BI solution. We can have the best solution, and we can also have the worst results, and it is relevant to train the management on the BI solution. The highest levels of the organization must have an in-depth understanding of the solution, statistical concepts, and how to manage it, so they can translate it into actions for their teams. Therefore, the solution must be implemented according to the analytical level of the leadership.

- sometimes you have to critically ask yourself, your stakeholders do they really need big, enterprise grade BI solution or say now a days good to have AI element in it? As having seen from last 20+ years even though new tools have comeup but still basic necessities (say up to 80%) are satisfied by existing but robust solutions already in place. - Look for actionable insights rather than too many data points.