Strategies for Improved Measurement Techniques

One of the most common mistakes that companies make is to focus too narrowly on a small set of metrics while overlooking the broader ecosystem of inputs that drive results. At Amazon, we rejected the conventional wisdom that Executives should focus on just a few high-level metrics. Instead, we spent years developing mechanisms to measure, analyze, and improve thousands of input metrics (actions) based on the impact they have on output metrics (business results). The key lessons from this approach are: 1. Do not limit the number of metrics you monitor – Track a broad set of metrics, add, delete, and edit them over time based on observed results. 2. Review both controllable inputs (leading indicators) and output metrics (results) – They must be reviewed in tandem to understand cause-and-effect relationships. 3. Regularly review, analyze, and adjust metrics – The metrics that Amazon tracks are continuously improved to more accurately represent the speed, quality, and cost of every customer-facing process. 4. Implement new product and process improvements designed to deliver improvements for your input metrics. If you have selected the right inputs, then improvements to your outputs will follow. 5. Control your processes by continuously reviewing all relevant input metrics to ensure they stay within desired tolerances as internal and external factors change over time. Following these steps uses the Six Sigma technique known as DMAIC - Define, Measure, Analyze, Improve, and Control. The typical approach is to focus deeply on metrics like sales and gross margin while spending little or no time measuring or managing elements of the customer experience. At Amazon, this focus is reversed.

"You can’t manage what you don’t measure." Yet, when it comes to change management, most leaders focus on what was implemented rather than what actually changed. Early in my career, I rolled out a company-wide process improvement initiative. On paper, everything looked great - we met deadlines, trained employees, and ticked every box. But six months later, nothing had actually changed. The old ways crept back, employees reverted to previous habits, and leadership questioned why results didn’t match expectations. The problem? We measured completion, not adoption. 𝗖𝗼𝗻𝗰𝗲𝗿𝗻: Many organizations struggle to gauge whether change efforts truly make an impact because they rely on surface-level indicators: → Completion rates instead of adoption rates → Project timelines instead of performance improvements → Implementation checklists instead of employee sentiment This approach creates a dangerous illusion of progress while real behaviors remain unchanged. 𝗖𝗮𝘂𝘀𝗲: Why does this happen? Because leaders focus on execution instead of outcomes. Common pitfalls include: → Lack of accountability – No one tracks whether new processes are being followed. → Insufficient feedback loops – Employees don’t have a voice in measuring what works. → Over-reliance on compliance – Just because something is mandatory doesn’t mean it’s effective. If we want real, measurable change, we need to rethink what success looks like. 𝗖𝗼𝘂𝗻𝘁𝗲𝗿𝗺𝗲𝗮𝘀𝘂𝗿𝗲: The solution? Focus on three key change management success metrics: → 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 – How many employees are actively using the new system or process? → 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 – How has efficiency, quality, or productivity changed? → 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 – Do employees feel the change has made their work easier or harder? By shifting from "Did we implement the change?" to "Is the change delivering results?", we turn short-term projects into long-term transformation. 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀: Organizations that measure change effectively see: → Higher engagement – Employees feel heard, leading to stronger buy-in. → Stronger accountability – Leaders track impact, not just completion. → Sustained improvement – Change becomes embedded in the culture, not just a temporary initiative. "Change isn’t a box to check—it’s a shift to sustain. Measure adoption, not just action, and you’ll see the impact last." How does your organization measure the success of change initiatives? If you’ve used adoption rate, performance impact, or user satisfaction, which one made the biggest difference for you? Wishing you a productive, insightful, and rewarding Tuesday! Chris Clevenger #ChangeManagement #Leadership #ContinuousImprovement #Innovation #Accountability

Stop measuring "productivity" and start measuring flow! Most manufacturing metrics focus on productivity - how busy people and machines are. But being busy doesn't mean you're creating value. In fact, maximizing resource utilization often destroys flow and hurts overall performance. Here are 5 flow metrics that matter more than productivity: 1/ Lead Time ➟ How long does it take for material to move from start to finish? ↳ This is the single most important indicator of your process health. 2/ First-Time Quality ➟ What percentage of work is completed correctly the first time? ↳ Rework is the invisible flow killer in most operations. 3/ WIP Levels ➟ How much material is sitting between process steps? ↳ Lower WIP = faster flow and fewer hidden problems. 4/ Takt Adherence ➟ Are you producing at the rate of customer demand? ↳ Neither too fast nor too slow - just in time. 5/ Response Time ➟ How quickly can you detect and resolve abnormalities? ↳ Fast response prevents minor issues from becoming major disruptions. Implementation steps: Step 1: Make these 5 metrics visible in your area Step 2: Reduce batch sizes to improve flow (even if it seems "less efficient") Step 3: Focus improvement efforts on removing flow barriers, not keeping resources busy Remember: A process at 70% utilization with perfect flow will outperform a 95% utilized process with poor flow every single time! --- Follow me Angad S. for more!

𝗪𝗼𝗿𝗸 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗺𝗲𝗻𝘁 𝗠𝗮𝗱𝗲 𝗦𝗶𝗺𝗽𝗹𝗲 𝘄𝗶𝘁𝗵 𝗣𝗠𝗧𝗦 Struggling with inconsistent workflows and lost time? Predetermined Motion Time Systems (PMTS) simplify work measurement by providing precise, data-driven standards. It’s a straightforward way to streamline tasks, reduce waste, and boost productivity. Here’s how PMTS simplifies work measurement with the SIMPLE Framework: Standardize, Improve, Measure, Plan, Learn, Execute. 𝟭. 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗲: 𝗖𝗿𝗲𝗮𝘁𝗲 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 PMTS removes variability by setting clear standards. Define Precise Tasks: Break down work into measurable steps. Align Teams: Ensure everyone follows the same process. Reduce Errors: Consistency minimizes mistakes and confusion. Standardization ensures every motion has a purpose. 𝟮. 𝗜𝗺𝗽𝗿𝗼𝘃𝗲: 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 PMTS helps refine workflows for maximum efficiency. Eliminate Waste: Remove non-value-added motions. Enhance Layouts: Simplify workstations for smoother operations. Balance Workloads: Distribute tasks evenly across teams. Improvement leads to faster and more effective workflows. 𝟯. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲: 𝗧𝗿𝗮𝗰𝗸 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝘁𝗲𝗹𝘆 PMTS provides precise metrics for work measurement. Set Benchmarks: Use PMTS data to establish realistic targets. Monitor Progress: Compare performance to time standards. Identify Gaps: Spot areas needing improvement. Accurate measurement drives meaningful action. 𝟰. 𝗣𝗹𝗮𝗻: 𝗕𝘂𝗶𝗹𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 With PMTS, you can design processes that work better. Organize Tasks: Plan workflows based on PMTS data. Minimize Downtime: Create smooth transitions between steps. Forecast Needs: Use standards to allocate resources effectively. Planning with PMTS saves time and resources. 𝟱. 𝗟𝗲𝗮𝗿𝗻: 𝗚𝗮𝗶𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗿 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 PMTS is a tool for continuous learning. Analyze Data: Use results to refine processes. Test Changes: Validate improvements with PMTS metrics. Adapt Quickly: Stay responsive to shifting demands. Learning ensures operations evolve with your needs. 𝟲. 𝗘𝘅𝗲𝗰𝘂𝘁𝗲: 𝗧𝘂𝗿𝗻 𝗣𝗹𝗮𝗻𝘀 𝗶𝗻𝘁𝗼 𝗔𝗰𝘁𝗶𝗼𝗻 PMTS simplifies execution with clear, actionable steps. Provide SOPs: Equip teams with clear work instructions. Train Workers: Teach techniques based on PMTS standards. Track Results: Use PMTS to ensure goals are met. Execution is efficient when everyone knows the plan. 𝗧𝗵𝗲 𝗦𝗜𝗠𝗣𝗟𝗘 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 The SIMPLE Framework shows how PMTS makes work measurement easier: Standardize tasks for consistent results. Improve processes to boost efficiency. Measure performance with accuracy. Plan workflows to minimize waste. Learn from data to drive progress. Execute with clarity and confidence. PMTS turns work measurement into a straightforward, results-driven process. Ready to simplify your operations with PMTS? - Insightful ? ♻️ Repost and inspire your network!

“A good decision is based on knowledge and not on numbers”     – Plato The above quote of the week made me think long and hard about how metrics and benchmarks are used - here are some of those thoughts... "What we measure starts with understanding "why" we are measuring it, "what" affects it, and "how" to improve it Let's use CAC Payback Period (CPP) as an example: 👉 CPP tells us how long it will take to break-even (payback) the cost of acquiring a new customer after factoring in the cost (COGS) of delivering the service 🤔 But after calculating CPP - how do you use it to make a decision on IF there is a need to improve it and then HOW can we improve it  ✔️ First- understand how your current CPP compares to your internal CPP trends and to external benchmarks for companies like yours ✔️ Second - segment CPP by target market segments including ICP, to see if one particular segment performance is trending better/worse than others ✔️ Third - Identify and then Analyze the primary input variables that directly impact CPP including (will not discuss correlation or regression analysis here)   - Win Rate (using trends over at least 5 quarters)   - ACV (using trends over at least 5 quarters)   - CAC Ratio (Sales, Marketing and Sales Development)   - Pipeline Velocity (using trends over at least 5 quarters)      - Sales Cycle Length (from qualified opportunity to Closed-Won)      - Qualified Lead to Qualified Opportunity - Gross Margin ((using trends over at least 5 quarters)   - Best practice is to do this per segment IF applicable (CAC Ratio is harder) ✔️ Fourth - Now you have the numbers - but what about the knowledge of WHY the input variables (leading indicators) are trending negatively and impact the lagging indicator (CPP)    - What has changed in each of the negatively trending input variables        - Internal Process(es)       - Internal Resources       - External Market Conditions ✔️ Fifth - if identifying the one primary root cause is easy - develop 2-3 strategies/tactics to change it and then create "phased experiments" to test the hypothesis - but be careful at doing multiple things all at once:     - Making big bets that take a lot of time can be risky     - Changing MULTIPLE variables all at once will not provide clarity of what          is/was causing the issue ✔️ Sixth - almost every SaaS Metric being measured has multiple causal and/or correlated relationships and typically across more than one department/function    - Try not to BLAME one function, role, person, or input variable    - Identify the input variables upfront FOR every SaaS Metric being        measured and assign those as measurable goals/objectives (metrics) up      front        - Having a well-defined SaaS Metrics Framework is an excellent place to          start 👆 Knowing the metric and benchmarks is a great starting point - but the magic is having the knowledge of what impacts it and how to improve it 🙋♀️ What say you? #b2bsaas #metrics #benchmarks

Step-by-Step Guide to Measuring & Enhancing GCC Productivity - Define it, measure it, improve it, and scale it. Most companies set up Global Capability Centers (GCCs) for efficiency, speed, and innovation—but few have a clear playbook to measure and improve productivity. Here’s a 7-step framework to get you started: 1. Define Productivity for Your GCC Productivity means different things across industries. Is it faster delivery, cost reduction, innovation, or business impact? Pro tip: Avoid vanity metrics. Focus on outcomes aligned with enterprise goals. Example: A retail GCC might define productivity as “software features that boost e-commerce conversion by 10%.” 2. Select the Right Metrics Use frameworks like DORA and SPACE. A mix of speed, quality, and satisfaction metrics works best. Core metrics to consider: • Deployment Frequency • Lead Time for Change • Change Failure Rate • Time to Restore Service • Developer Satisfaction • Business Impact Metrics Tip: Tools like GitHub, Jira, and OpsLevel can automate data collection. 3. Establish a Baseline Track metrics over 2–3 months. Don’t rush to judge performance—account for ramp-up time. Benchmark against industry standards (e.g., DORA elite performers deploy daily with <1% failure). 4. Identify & Fix Roadblocks Use data + developer feedback. Common issues include slow CI/CD, knowledge silos, and low morale. Fixes: • Automate pipelines • Create shared documentation • Protect developer “focus time” 5. Leverage Technology & AI Tools like GitHub Copilot, generative AI for testing, and cloud platforms can cut dev time and boost quality. Example: Using AI in code reviews can reduce cycles by 20%. 6. Foster a Culture of Continuous Improvement This isn’t a one-time initiative. Review metrics monthly. Celebrate wins. Encourage experimentation. Involve devs in decision-making. Align incentives with outcomes. 7. Scale Across All Locations Standardize what works. Share best practices. Adapt for local strengths. Example: Replicate a high-performing CI/CD pipeline across locations for consistent deployment frequency. Bottom line: Productivity is not just about output. It’s about value. Zinnov Dipanwita Ghosh Namita Adavi ieswariya k Karthik Padmanabhan Amita Goyal Amaresh N. Sagar Kulkarni Hani Mukhey Komal Shah Rohit Nair Mohammed Faraz Khan