January 2025 posts#

💡 10-Jan-25#

In the world of today, learning is a superpower, and that’s why it’s very important to learn how to cut through the noise, trust your Maker and keep growing consistently.

Irrespective of the size of your business, the following remains true:

  1. Your business is a system that requires:

    • A particular mindset held by each team member within the business

    • Processes that help you maintain compliance, reliably deliver quality goods and services and mitigate your environmental impact

    • Proactive data analytics to drive real-time business decision-making

  2. Mathematical reasoning will never cease to lack relevance in our increasingly volatile world.

  3. People are at the heart of all businesses, and people connect with captivating stories; stories, whether told visually, orally or in writing, help us simplify an increasingly complex world. Stories help bridge the gap between lack of awareness and effective implementation of documented processes - they also help us build processes that empower the process owner, not cripple them.

  4. It is important to keep practicing how to anticipate both risk and opportunity so that we can save cost through the mitigation of risk and grow revenue through the capitalization of opportunity. Effective management of both is what allows sustainable growth in both EBIT and positive cashflows, building a business that can remain for generations to come.

Working in Supply Chain has been quite an experience, and I hope to continue to leverage both Performance Management (concerned with reporting and analysis of business performance) and Quality in ensuring customer focus and data-driven decision-making is maintained within my sphere of influence.

💡 13-Jan-25#

In any ISO standard you encounter, you will encounter Deming’s simple but powerful flow of Plan-Do-Check-Act. You can take it down to the process and sub-process level, leveraging data as follows:

✍🏾 Plan: Do you systematically have sessions where you look at data associated with your process and use it to analyze risk and opportunity?

💪🏾 Do: As you do your routine activities, do you make sure you maintain your records in such a way that they can be analyzed using generative AI or spreadsheets / databases? It has been famously said that 80% of data science is data cleaning; being deliberate about data quality during production stage can help you identify insights much faster.

🧐 Check: Do you consistently monitor data from your process / sub-process and evaluate it by holding data-driven discussions during your performance reviews?

🎯 Act: Do you learn from your data and consistently make your process better? Do you learn from challenges experienced to identify root causes and make strong action plans?

Remember, data science / data analytics / AI is not an end, improving your process / sub-process and faster data-driven decision-making is the ultimate goal. As I ask you these questions, I am also asking myself the same.