How can you encourage data-driven decisions?

Utilizing the SMART criteria for your organization allows goals to be obtainable. Making data-driven decisions is solely based on the quality of the data and understanding the business rules. Also, understanding what metrics should be measured and monitor for adequate decision making skills. Data allows you to not “estimate” based on previous trends, but gives stakeholders factual information that they can trust.

As we all race towards a value driven data world, there is no shortage of tips to share but here are a few to get you started: 👉Visibility Priority: Like the air we breathe, data's importance is often inconspicuous. So, highlight its value consistently 👉Real-time Relevance - Move towards utilizing real-time data for timely interventions and proactive decision-making 👉Decision Options - Present multiple data-value-backed scenarios to accelerate decision-making processes 👉Feedback Loops - Continuously refine decisions based on data feedback, ensuring adaptability 👉Resource Optimization - Use data value to direct resources effectively, maximizing ROI and minimizing wastage

Create a data democratization by enabling the organization to understand what data means. Then comes creating a common language. Being able to look data is one thing, but interpreting it is another. Data needs to be standardized and a business glossary with common standards and definitions created, or everyone will draw decisions based on their own siloed view. Then comes visualization which is an important part in the data democratization - everyone should be able to get insights into data with the help of user-friendly tools.

Understand and clearly articulate the problem! Only if you know what you are trying to solve, will you be able to define SMART objectives. Question yourself WHY you are doing something and HOW an objective is contributing to the cause

Encouraging data-driven decisions in an organization is essential for making informed choices and driving success. You can use the "DATA" formula to promote a data-driven culture: Data Accessibility: Ensure that relevant data is readily accessible to decision-makers. Invest in data collection, storage, and retrieval systems. Create user-friendly dashboards and reporting tools to make data easy to find and interpret. Data Analysis Skills: Equip your team with the necessary data analysis skills. Foster a culture of transparency and accountability. Encourage open discussions about data findings and insights. Actionable Insights: Emphasize the importance of generating actionable insights from data.

Love the idea of measurable but let's not forget instinct. I once worked in a plant the made extruded plastic to be ground into toner for Xerox. The room was hot, noisy and vibrated ....a lot. I was proud of the data collection and the statistics we used to measure performance. One day the operator, a hard core biker, told me we were making "junk". But the data says we're not I said proudly. He said trust me. We took a sample and he was right. His instinct and sensitivity to vibration measured the performance. My statistics missed. Does that mean we were flawed. No. It means we didn't consider everything. Never rule out instinct from those people who live the process. They feel goodness in their bones.

Data-Driven analysis is a competent way to do informed decision, in my world the advisory world, the due diligence exercises are using trend analysis either manually by using excel or power PI, or automated like using “Plateau“. By analyzing monthly/quarterly data per each line item of the I/S or B/S, peaks and troughs, seasonality, unreasonable jumps, etc. This gives good understanding about all trends, depict anomalies and determine adjustments.

For any strong competitive organization to be capable of making decisions , predictions and long range plans among many other determinations, the data analysis must be a priority. Many tools have been developed and are available for organizations to incorporate them as needed but they must continuously invest to bring them to their teams . Not only the tools will make a difference , but also the people skills and capabilities , then trainings should be always available at all levels and functions . Business or organizations not willing to invest in tools to move toward a data- analysis driven culture might to be able to develop, anticipate , innovate nor transform as markets change.

It is important to remember that the "right" decision will not always lead to a positive outcome. Evaluate the decision and the circumstances surrounding how the decision was made, not just the outcome.

Decisions always yield results or consequences. Tools are available to help us make the best-informed decisions for a specific challenge or idea. While a decision may work for the present moment, it may not be suitable for the future. Therefore, it's crucial to validate the decision through feedback and consider necessary adjustments. Leverage data and tools to assist you in the decision-making process, and collaborate with others to gain additional insights and complement your understanding.

It’s very important to make data driven a part of your culture. It shouldn’t be what just the top management is doing but every employee in the company should speak the language of numbers - I with my team say “talk to me in maths and not in English”.

Data-driven corporate culture works like a Swiss army knife: simple to implement and understand, fosters transparency and trust among teams, eliminates bias at all levels, increases productivity, saves costs, and increases business outcomes. Business leaders need to know that the simplicity of the implementation lies in the clear communication of its other benefits to the employees, and top management must lead by example.

Data in and of itself is not terribly useful, it is how you can use the data to inform future decisions and the narrative that the data reveals that is it's truest value. I would also highlight that people need to have the ability to "go past the numbers" if they want to be able to make data driven decisions. Without a "so what?" to the data it is just numbers without any additional meaning.

Reflect on the ethical implications of your data - driven decisions. In a world where data privacy and ethical use of information are increasingly under the spotlight, ensure that your data-driven approach is not just efficient and effective, but also ethically sound and respectful of customer privacy. This can be a unique selling proposition and a trust-building factor with your stakeholders.

Using the US's main economic indicator as an example of what to consider when promoting analytics over emotion as a primary decision-making tool, the nation's stock markets are some of the financial sector's most exhaustive sources of data analytics yet still suffer from an overabundance of instability due to external influences, primarily based on people's emotional reactions to non-relevant news and events. To mitigate these reactions and retain a focus on analytical decision-making, I believe AI and machine-learning should be an integral component of business processes which will, in the future, prevent or lessen the effects of non-rational recessive markets as well as business valuations which scope short- vs long-term in regard to ROI.