Fortune Buchholtz’s Post

Less can be more, especially with metrics. In a world obsessed with data, we often fall into the trap of measuring everything. But not all metrics matter equally. I recommend a simple approach to metrics. Imagine a pyramid. At the peak, only a handful of metrics for the entire company. These are your north stars, guiding the ship. As you descend, metrics get more specific, tailored to each department's unique role in reaching those top goals, yet still only a handful per department. Some department's may only have one metric that matters. Maybe only one metric matters at the top. This isn't about reducing importance. It's about clarity and focus. When each team understands their specific targets and how they ladder up to the company's overarching goals, alignment isn't just a buzzword. It's reality. Simplicity in metrics fosters unity, eases implementation, and ensures everyone's rowing in the same direction. Ever tried trimming down your metrics? Share your experience or the impact it had on your team's performance and alignment.

Problem-Solving in 3 Easy Steps (Or not) 1) Identify the root cause 2) Gather and analyze data 3) Collaborate with the team on a solution Done! But wait… - Are you solving the right problem? - Can you solve it using your current resources? - What are the consequences of not solving it at all? Solving problems is actually not that easy. But considering whether you can (and should) do it and the impact of not doing it at all on your team can help you choose the right problem to work on. And that's the actual first step of problem-solving! #innovation #problem-solving

Many advantages can be manifest in your organization when promoting a data-driven culture. #talentretention #clientretention

Shila, an experienced data analyst, is a star performer in the company. Her reports are dependable and she is always on time. Every spreadsheet she produces for the manager is gleamed with flawless tabulation and analysis. Yet, her manager, Lisa feels that Shila can do better. Lisa feels that Shila can do far better with data if she knows the current trends of AI-embedded data analysis processes. Sometimes, Lisa needs certain trends from different angles that Shila couldn’t fetch. The market is getting more competitive now. The competitors are analyzing data from newer aspects for greater insight. Today, expert data analysis offers a competitive advantage. As a manager of the company, Lisa needs that competitive advantage. She knows that Shila is brilliant but somehow, she is in an “action loop” with no further improvement. Lisa just needs to figure out how to unlock her potential.  #managementconsulting https://lnkd.in/gFuKxyMj

𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗻𝗲𝗲𝗱𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗱𝗮𝘁𝗮 In this insightful post, 𝗠𝗶𝗸𝗸𝗲𝗹 𝗗𝗲𝗻𝗴𝘀ø𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝘁𝗵𝗲 𝗿𝗲𝗹𝗶𝗮𝗻𝗰𝗲 𝗼𝗻 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗮𝗻𝗱 𝗲𝗺𝗽𝗵𝗮𝘀𝗶𝘇𝗲𝘀 𝘁𝗵𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝗰𝗲 𝗼𝗳 𝗶𝗻𝘁𝘂𝗶𝘁𝗶𝗼𝗻 and exploration. Dengsøe shares anecdotes that show how perseverance and out-of-the-box thinking led to breakthroughs in different scenarios and advocates for a holistic approach. 𝗛𝗲 𝗲𝗺𝗽𝗵𝗮𝘀𝗶𝘇𝗲𝘀 𝘁𝗵𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝗰𝗲 𝗼𝗳 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 𝗯𝗶𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀, 𝗺𝗮𝗸𝗶𝗻𝗴 𝘀𝗺𝗮𝗹𝗹 𝗯𝗲𝘁𝘀 𝗮𝗻𝗱 𝗻𝗼𝘁 𝗿𝗲𝗹𝘆𝗶𝗻𝗴 𝘁𝗼𝗼 𝗺𝘂𝗰𝗵 𝗼𝗻 𝗱𝗮𝘁𝗮. Dengsøe also introduces the concept of one-door and two-door decisions and emphasizes the need for flexibility and adaptability in decision-making. Ultimately, he encourages professionals to 𝗲𝗺𝗯𝗿𝗮𝗰𝗲 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗮𝗻𝗱 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝗻𝗼𝗻-𝗹𝗶𝗻𝗲𝗮𝗿 𝗽𝗮𝘁𝗵𝘀 𝘁𝗼 𝗰𝗹𝗮𝗿𝗶𝘁𝘆. #decision making #data #intuition #problem solving #agility #uncertainty #exploration https://lnkd.in/d4bdFu3V

🎯 How do you make decisions? 🤔 Do you rely on gut feeling, off-the-shelf models?   Swipe through to explore the different ways decision-making can be approached:   1️⃣ Gut Feel & ‘Garbage Can: Randomly matching problems with solutions based on social relationships and immediate responses. 2️⃣ Silver Bullet: Applying generalized, off-the-shelf models indiscriminately, often leading to oversimplified solutions. 3️⃣ Modelling: Building tailored models specific to each situation, integrating real-world data for accurate decision-making. 4️⃣ Closing the Loops: Integrating models with real-world data, validating or refuting them based on evidence.   Which method resonates most with your experience? Let's dive into the pros and cons of each strategy and how they impact complex decision-making.   💬 Share your thoughts in the comments! 🔁 Don’t forget to like and share this post with your network! 📌 Follow us for more insights on systems thinking and effective management techniques.   #SystemsThinking #DecisionMaking #Management #OperationsResearch #RealWorldData #Leadership #Modeling #Strategy

I believe in the “principle of least surprise”. This comes from software engineering and API design, where you want your interfaces to be “not surprising at all” most of the time.  But this also applies to what I believe is the best way to drive initiatives and to communicate: managing up, managing down, dealing with customers, and working with coworkers from different functions - all should operate with the “principle of least surprise”.  When managing up, it means keeping leaders informed and aligned with your plans, ensuring no surprises in progress or issues. When managing down, it involves setting clear expectations and providing consistent feedback to your team. With customers, it requires transparent communication and setting realistic expectations to build lasting relationships. When collaborating with coworkers from different functions, it ensures everyone is on the same page up front, reducing misunderstandings down the road. The principle of least surprise is in contrast with “the grand reveal” approach where discussions have to be “hidden” because otherwise the situation would be too political or attract too much noise.  I must be lucky enough that I can adopt “transparency as the best policy” in most places I’ve worked and where I work - environments where you don’t have to worry too much about “first impression” and decisions are made following data and facts.  It’s a perk of being in a company that builds analytics.

Disruptive Thinking. It sounds negative - but it isn't! It's purposefully being the "Devils Advocate" and asking the "What if" questions. It's an intentional shift in the approach to problem identification and #problemsolving. What it isn't: - Smiling and nodding - Floating along - "Not being a team player" Breaking the thinking mold in your teams is a catalyst for growth and next-level achievement. Look for the non-traditional data source, ask outside opinions, re-evaluate #metrics of success that help you get to where you're going, not stay on the course. Disruptive Thinking means you are going to have to speak up to be heard. And that's a good thing!! What problems are you solving right now? What questions are you asking? _________________________________________________ #disruptivethinking #thoughtsoftheday

Translating business-speak into what people actually meant, part 17: "Think tank" 👉 we'll waste time deciding by committee "Data-driven solutions" 👉 here are some numbers, buy our stuff "Best practices" 👉 make it this way b/c I don't have time to think "Authentic" 👉 I don't actually know what I'm talking about "Actionable insights" 👉 useful s*** "Bandwidth" 👉 you probably don't have time, but should make it "Thought leader" 👉 we're going to sell you on something at the end "Holistic" 👉 everyone's time is getting wasted on this "Roadmap" 👉 I need help prioritizing work "Value add" 👉 we aren't clear on the outcomes of our product "Customer journey" 👉 we don't know why our buyers buy "Future proof" 👉 we're scared s***less and hedging against change "Deep dive" 👉 the dive is most certainly not deep, or it's regurgitated "Table a discussion" 👉 I don't want to talk about this now, or ever "Disruptive innovation" 👉 redundancy is easier than being descriptive So... what did I miss? What would you add?

In today's fast-paced world, data is king. Organizations harnessing data-driven decision-making power gain a competitive edge and drive innovation. But how do we foster a culture where data is not just a tool but a guiding principle? 🌱 Training and Education: It starts with investing in our teams. We empower our employees to leverage data effectively by providing data analysis and interpretation training. Let's equip them with the skills they need to thrive in a data-driven environment. 💡 Encouraging Curiosity: Curiosity fuels innovation. Encourage your team to ask questions, explore data, and uncover insights. Fostering a culture of curiosity opens the door to discoveries and opportunities. 🏆 Recognizing and Rewarding Data-Driven Decisions: Celebrate wins that stem from data-driven insights. Whether it's optimizing processes, identifying new market opportunities, or improving customer experiences, let's recognize and reward those who leverage data to drive results. 🔄 Iterative Improvement: Cultivating a data-driven culture is an ongoing journey. It requires continuous learning, adaptation, and refinement. Let's embrace a continuous improvement mindset, where we learn from our data, iterate on our strategies, and strive for excellence. By nurturing a culture where data is valued, respected, and integrated into every aspect of decision-making, we pave the way for success in today's data-driven world. Together, let's cultivate a culture where data isn't just a tool – it's a way of life. #DataDriven #Culture #Innovation #Leadership #LinkedIn