One ground rule that was created was to utilise the data which has been double checked centrally. While BI and other tools help, to have a unified and fruitful discussion without worrying on date or time of the download, missing returns from sales data or the way the particular P&L format is been looked at, can be addressed by having standardised reporting format. A lot of time would get wasted just verifying why the difference? Hence it was a structured dissemination of information on which presentation or discussions were centred. The above not only saves time but helps business and teams to focus on what matters.

Data is sacrosanct, interpretations are not. Why call different interpretations a "conflict"? Various interpretations are sure to enrich the outcome of the team result. Requirement is of allowing members to express their interpretations and logic behind that. A serendipitous moment is sure to emerge.

Why the constant conflicts? Data should lead to more unity behind decisions, not discord. Possible problems to solve: 1. You don't have the right data. Maybe an easy solve. 2. You don't have people who understand the implications of certain data or models. Harder to solve, especially if you aren't sure who on the team is usually right vs. wrong. 3. You don't have a goal in mind when running data reports or analysis. Pretty easy to solve - before looking at the data, write down the potential outcomes of the analysis and outline what action you will take under each outcome, that way nobody can reinterpret data after the fact to fit their biases.

Exactly when interpretation is used instead of scientific investigation and analysis, there is also the possibility of conflict. There is no place for philosophy in scientific methodology. Data and definitions must be completely unified and standardized for all team members. Scientific methodology and targets must be clear. Data must be real and without the slightest distortion. Maximum care must be taken to avoid cognitive biases, orientation, conflict of interest, etc.

Data conveys a story, but interpretation is expected. Hosting collaborative sessions where members submit their analysis promotes open discourse. Align everyone's views with the company goal. By welcoming multiple perspectives, you encourage innovation and make decisions based on a complete picture.