Here's how you can enhance decision-making processes in business intelligence through collaboration.

1. I believe before we start any analytics exercise, its important to do Data Quality (DQ) exercise on the underlying data on which analytics would work. 2. Secondly, consumers and decision makers should be clearly identified and their buy-in upfront is important. 3. To enable change management, a dedicated team should work with the SI from the beginning. 4. Then, a clear understanding and agreement on the KPIs and visualtization is imperative before you embark upon the analytics journey. Many a times, there is dis-agreement on both at a later stage which causes avoidable time loss. 5. A dedicated team to test the outputs is critical; numbers have to match. 6. Start with a few dashboards and build more within 6 months and mandate adoption

In my point of view, some actions can contribute to promoting collaborative decision-making in BI, such as: Involve key stakeholders from different departments at the beginning of the BI process; Form cross-functional teams made up of BI analysts, data scientists, business users and IT professionals; Collaboratively define clear objectives and key performance indicators (KPIs) for BI initiatives; schedule regular meetings where stakeholders and BI teams collaborate to discuss data insights, interpret findings, and brainstorm solutions to business problems; Continuously evaluate the impact of BI initiatives on decision-making processes.

Sou da opinião de envolver todas as partes interessadas desde o início do processo de tomada de decisão, garantindo que diferentes perspectivas sejam consideradas desde o início.

BI tools sounds a bit pre historic, to be honest. Data as a code to build products - AI, Analytics or whatever relevant to drive impact to the business, which delivered in the right frame from a business problem solving and engineering mindset will naturally drive adoption. Some of the greatest examples we’re all aware - ThoughtSpot (AI for BI a decade back - way ahead of time), Palantir Foundry (ontology, operational analytics with feedback loop to system of record) etc are some of the favorites of business ops, biz execs along with erstwhile products/platform Looker, Tableau, Qlik, PowerBI etc. I know folks love persona construct but they are dynamic in nature hence marketplace approach works much more effective to drive target value.

At this moment, I am supporting several technology fronts for the support and reconstruction of Rio Grande do Sul. In all of them, without exception, data intelligence is crucial! In this case, decisions save lives! There are data startups being created amidst the chaos, where in extreme situations, quick decision-making is the difference between life and death. Tech for Good. Using technology for good, especially in crisis situations, demonstrates the powerful impact that innovation can have in critical conditions. Data intelligence not only guides more informed decision-making but also accelerates responses in times of need.

Transparency in sharing insights is crucial, but equally important is establishing a clear protocol on how these data can be questioned or validated by other team members. This not only promotes a culture of healthy questioning but also ensures that decisions are based on robust and verified data.

📊 Establish a structured framework for sharing insights that ensures relevance, clarity, and accessibility to all stakeholders. Develop standardized templates or formats for reports and presentations to streamline the communication of insights. Tailor the content and level of detail to the specific needs and preferences of different audience groups, providing actionable insights that directly support decision making.

Effective insight sharing involves presenting findings clearly and understandably, often through visualization tools like graphs and charts. Narrative reports offer a detailed overview of key insights and recommendations, while presentations enable live engagement and discussion. Interactive dashboards empower users to explore data independently, and storytelling can make data more relatable and memorable. Data stories, whether in blogs or articles, provide context and relevance to the findings. Infographics combine text and visuals to convey insights in a visually appealing manner. Choosing the right method depends on the audience and the complexity of the data being shared.

Effective insight sharing involves presenting findings clearly and understandably, often through visualization tools like graphs and charts. Narrative reports offer a detailed overview of key insights and recommendations, while presentations enable live engagement and discussion. Interactive dashboards empower users to explore data independently, and storytelling can make data more relatable and memorable. Data stories, whether in blogs or articles, provide context and relevance to the findings. Infographics combine text and visuals to convey insights in a visually appealing manner. Choosing the right method depends on the audience and the complexity of the data being shared.

Collaboration and collective intelligence is easier said than achieved. It flows from the top and is a part of the organizational culture and not just for a robust BI strategy. Finding discrepancies, questioning assumptions make most people uncomfortable. Dont get me wrong, the importance of collaboration cannot be over empahsized. However, on the flip side, too many uncontrolled ideas and collective intelligence may also lead to conflicts, deadlocks and lack of decision making and ownership. Its important that collaboration is facilitated and channelized at the right time (the earlier the better) and in the right direction at the appropriate levels (top downwards) within the organization and results can be amazaing.

Tools are enablers; action and co-ordination is human. Leveraging collaboration tools is definately a BIG yes. Tools that enable people to connect, share "credible" information and act will add value to entire decision making process.

From my point of view, the essential thing is to promote a culture of shared data and interdepartmental collaboration, where information is accessible and decisions are made based on collective insights. Integration of different departments and effective communication are key to making the most of BI tools and available data.

Go beyond traditional spreadsheets. Invest in collaborative BI tools that allow real-time data exploration, annotation, and discussion. This streamlines the process and facilitates shared decision-making. Collaborative BI tools can also help visualize complex data sets, making insights easier to understand and act upon.

Choosing the right collaboration-friendly BI tools is essential for optimizing decision-making processes. Let’s explore some key features and considerations when selecting such tools: 1-Real-Time Data Sharing 2-Collaborative Analysis 3-Easy Communication and Discussion 4-Integration with Collaboration Platforms 5-Version Control and Audit Trails 6-User-Friendly Interfaces 7-Security and Access Controls:

Utilizing collaboration-friendly BI tools that facilitate real-time data sharing is crucial for both reactive and proactive decision-making within organizations. These platforms allow team members to quickly analyze data and communicate insights, enabling immediate responses to emerging issues and informed strategic planning. By integrating these tools, organizations can dynamically adjust their strategies and operations, enhancing performance and ensuring they are both responsive to current challenges and proactive in future planning.

Don't just present findings - spark conversation! Hold brainstorming sessions to explore various interpretations and potential actions based on the data. This fosters critical thinking and leads to more robust decisions. Encourage healthy debate and challenge assumptions to ensure all potential angles are considered before making a final decision.

I recall learning that spending time on planning can save a significant amount of time during implementation. For example, one hour of planning can save four hours of implementation without planning. I also remember working with a consulting company to create 360-degree models for a performance dashboard tailored to the organization's needs. This resulted in over 40 performance dashboards, categorized by department, providing insight into the final output, costs, data sources, processing methods, and required formats before implementing a business intelligence system within the organization.

One of the main role of a leader is inspiring their teams, and at the same time encourage healthy discussions. Instead of indicate a simple pathway of execution, why not try to challenge team member with reflective questions? Many leader seek for the easy way, just giving order, avoiding mutual exchange of ideas, in other words, limiting creativity.

Create an environment where open dialogue is encouraged and valued. Encouraging questions, challenges, and discussions around BI reports and dashboards can uncover assumptions and biases, leading to more robust and resilient decisions. This dialogue should be structured to be constructive and focused on achieving the best possible outcomes.

Promoting open communication is key to successful teamwork in business intelligence. It's important to motivate team members to share insights, question premises, and collectively develop solutions, not only during formal meetings but also within everyday work processes. Such a culture of ongoing collaboration fosters innovation and optimizes results for the company.

Construir equipes multidisciplinares e diversificadas, com experiências e habilidades complementares. Diferentes perspectivas podem levar a insights inovadores e decisões mais robustas.

🌍 Incorporate interdisciplinary teams that bring together individuals with expertise in different domains, fostering collaboration and driving innovation in business intelligence initiatives.

Diversifying BI teams is a strategic move that can yield substantial benefits in decision-making. Let’s delve deeper into why diversity matters and how it enhances the BI process: 1-Multiple Perspectives 2-Cognitive Diversity 3-Reducing Bias and Blind Spots 4-Improved Problem-Solving 5-Creativity and Innovation 6-Inclusive Decision-Making 7-Enhanced Data Interpretation

I have formed work teams with people who have performed different but related tasks This has meant that each person contributes a different point of view from their perspective and experience. I like to include people who know the operation in depth, to know the amount of work that has to be done or that it represents. having information at an operational level, also having an area manager to see their concerns and KPI's, as well as a manager to know about all the work they do that is relevant at the management level and how this impacts the results.

Diversifying Teams is indeed a crucial aspect of effective collaboration in Business Intelligence. My opinion is that diversity should not only be seen in terms of backgrounds and experiences but also in thinking styles and problem-solving approaches. Too often, diversity is limited to demographic factors, but it's equally important to strive for cognitive diversity within teams. This includes bringing together individuals with different perspectives, such as analytical thinkers, creative thinkers, and critical thinkers. Embracing this diverse mix allows teams to approach challenging problems in new and innovative ways, ultimately leading to better decision-making in Business Intelligence.

🔄 Cultivate a culture of reflection and continuous improvement in the decision-making process by regularly reviewing outcomes and evaluating the effectiveness of strategies and approaches. Set aside dedicated time for post-mortem discussions or retrospectives after major decisions or projects to assess what worked well, what didn't, and what lessons can be learned for the future.

No meu ver, é muito importante realizar avaliações regulares do processo de tomada de decisão, refletindo sobre os sucessos e desafios encontrados e adaptando as estratégias conforme necessário para melhorar continuamente.

1. Review Outcomes: Regularly assess the outcomes of decisions made based on BI insights to understand their effectiveness. 2. Solicit Feedback: Encourage team members to provide feedback on decision processes and outcomes to identify areas for improvement. 3. Iterative Adjustments: Use the insights gained from reflection and feedback to make continuous adjustments to strategies and processes.

Finally, it's important to regularly reflect on the collaborative processes within your BI initiatives and adapt as necessary. After each project or decision-making cycle, gather feedback from team members on what worked well and what could be improved. Use this feedback to refine collaboration strategies, ensuring that your BI practices remain dynamic and responsive to the evolving needs of your business.

Regularly reflecting on collaboration processes in BI initiatives and adapting them as needed is essential. Gathering team feedback after each project or decision-making cycle identifies areas for improvement and strengthens collaborative strategies. This approach ensures BI practices evolve with business needs, uncovering hidden issues and providing new perspectives. It fosters an environment where employees feel valued, enhancing team morale and cohesion, which is crucial for long-term success.

I have a story to tell: I had worked on a product which failed in the market. Coming from the engineering team, we did what was right for the product but the end result was a disaster. When we started working project closure report, i happened to go & join the BI team. so, I also started making calls to the dropped-out customers, this was thru my firm's call center. This exercise brought back tons of lessons learnt data for the engineering team. we were just not thinking the way the customer was! So, if anybody from your diverse team has the right soft skills to talk to the end-user, please leverage the opportunity, this will help you build the best products for your firm! These are high risk experiments for firms which have such appetite!

No meu ver, além das estratégias mencionadas, é importante cultivar uma cultura organizacional que valorize a colaboração, a aprendizagem contínua e a abertura à mudança, pois isso contribui para uma tomada de decisão mais eficaz e orientada por dados.

🤝 Foster open communication: Encourage team members to share insights, ideas, and concerns openly. 🔄 Seek diverse perspectives: Gather input from team members with varying backgrounds and expertise to enrich decision-making. 🔍 Utilize brainstorming sessions: Organize brainstorming sessions to generate creative solutions and explore different viewpoints. 📊 Data-driven decisions: Leverage data analytics tools to gather relevant information and insights for informed decision-making. 👥 Establish consensus: Work towards consensus among team members to ensure alignment and commitment to decisions. 💡 Example: Enhancing the decision-making process in business intelligence through collaboration involves fostering open communication🤝🔄🔍📊👥💡

It's good to involve stakeholders and perspectives, however one should not loose track of objective and benefits of any BI report. How much data is too much for a customer needs to be leveraged. So a product manager needs to drive this towards useful outputs.