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By:

Rahul Kulkarni

30 March 2025 at 3:32:54 pm

Why the Majority Doesn’t Matter

Most change fails not from resistance, but from weak coalition design. Even if you negotiate well, you can still fail for a boring reason: You built the wrong coalition. This week we step into the third act of this series: modernize without backlash. Most leaders walk into an MSME thinking change is a vote. If most people agree, you win. That’s corporate thinking. In legacy Indian SMEs, the majority is usually passive. The people who matter are the ones who can stop the flow.   Which Seat...

Why the Majority Doesn’t Matter

Most change fails not from resistance, but from weak coalition design. Even if you negotiate well, you can still fail for a boring reason: You built the wrong coalition. This week we step into the third act of this series: modernize without backlash. Most leaders walk into an MSME thinking change is a vote. If most people agree, you win. That’s corporate thinking. In legacy Indian SMEs, the majority is usually passive. The people who matter are the ones who can stop the flow.   Which Seat Inherited seat: you may have authority, but you still need backing beyond the family name. Hired seat: you may have ideas, but you don’t have a home team yet. Promoted seat: you may have relationships, but you don’t automatically have permission.   In cricket, you don’t win because you have 11 batsmen. You win because the field is set right for the plan. A bowler can be doing everything right and still leak runs if the field leaves gaps. Singles become boundaries. The team blames the bowler. But the real issue was field setting. That’s how change fails in MSMEs.   Veto Players A small blocking group can stall you even if everyone nods in meetings. They don’t argue. They sit at gates: - Money release - Purchase approvals - Dispatch control - Owner access They can delay, create exceptions, raise “data doubts,” or ask for “one more confirmation.” And then they do the most effective thing of all: quietly wait for your energy to fade.   Own Work In one assignment, I thought I had the room. People smiled, agreed, even said, “Very good”. Two weeks later, nothing had moved. Two gatekeepers kept adding small speed-breakers. Every objection sounded reasonable. Over a month, the pilot died … no drama, just suffocation. That’s when I learned: in MSMEs, you’re rarely battling resistance. You’re battling veto power.   Coalition Math Political scientist William Riker had a simple idea: you don’t need everyone, you need a coalition that’s just big enough to win and hold. In a company, that means: enough of the right people so the new way becomes unavoidable. And people don’t jump alone. Most switch only when they see others switching because nobody wants to be the first person who looks foolish. So, your job is not “get buy-in from 50 people”. Your job is: 1. Build a small winning coalition 2. Neutralise the blocking coalition 3. Make it visible so the passive majority follows Politics Drama Name the gates Write the 3–5 gates your change must pass through (money, approvals, dispatch, data). Then write who controls them in real life. Pick your first five supporters Not supporters in principle. People who will act. Five is enough to cover gates without becoming a crowd. Pay the coalition cost upfront Each supporter needs one thing to stay aligned: respect, safety, credit, clarity, control of exceptions. Ignore this, and support disappears the first time pressure comes. Neutralize blockers calmly You have three moves: Convert: give them a dignified role and protect the interest they fear losing. Bypass: redesign the workflow so their veto reduces. Contain: limit their veto to exceptions, not the main flow. What you should not do is start a public fight too early. That creates camps. Camps create long wars. Wars kill modernization.   Field Test Name your first five supporters for your next change. Against each name, write ONE concession they need to stay aligned. Example: “You chair the weekly ritual.” “Pilot data won’t be used for appraisal.” “You control exceptions, but exceptions must be logged.” “Your method becomes the base standard.” “Your role is made explicit.” If you can’t name five, you don’t have a coalition yet. You have a hope.   In MSMEs, the majority is tired, busy, and risk-sensitive. They won’t lead your change. They will join it when it feels safe and inevitable. So, stop trying to convince everyone. Set the field properly. Build alignment with five. Neutralise the two who can block.   (The writer is a co-founder at PPS Consulting. He is a business transformation consultant. He could be reached at rahul@ppsconsulting.biz.)

AI in Sperm Sorting: An Unbiased Decision for A Better Outcome

Artificial Intelligence or AI is revolutionising fertility treatments of the future. The inclusion of AI enhances the accuracy, efficiency, and objectivity of sperm selection, hence potentially improving fertility outcomes by leaps and bounds. Traditionally, sperm sorting through manual methods is subjective to judgments. Processes like centrifugation and swim-up methods are used to separate sperm based on motility and morphology. Although they are effective, they have their limitations, leading to human errors that affect the success rates of fertility treatment. For instance, studies have shown that traditional sperm sorting techniques can have variability in success rates, with reported live birth rates ranging between 15 per cent to 25 per cent per cycle depending on the method and quality of sperm. Hence the introduction of AI helps in maintaining consistency in evaluations of sperm, using the same data set for every sample which leads to better judgments.


Automation and Standardisation- Automation of sperm selection and also introduction of AI in the process have improved the results in ART. AI-assisted sperm selection improves the accuracy in choosing high-quality sperm for fertilisation purposes, and also, pregnancy and live birth rates might be improved. Technologies like Intracytoplasmic Morphologically Selected Sperm Injection along with AI ensure the chances of pregnancies increase by about 10-20 per cent compared to the standard procedures. AI and Automation will decrease time taken to analyze sperm and increase opportunities to select better sperm with DNA integrity for better development and higher success rates in embryo selection. These processes ensure that the sperm selection process follows consistent criteria, reducing variability in outcomes caused by human error.


Analysing Complex Data for Better Outcomes- AI plays a crucial in improving IVF outcomes by analysing complex data and providing tailored recommendations. AI-driven tools and models such as those on SpOvum.ai point towards an opportunity to optimise ovarian stimulation decisions by assessing patient characteristics and follicle growth patterns. A study revealed that the use of AI in IVF improved egg yield and reduced medication costs. AI enables fertility specialists to make data-driven choices, improving overall IVF success rates and streamlining treatment processes.


Reducing Human Error- AI models can continuously learn and refine their performance by being trained on newer data. This adaptability ensures the technology remains unbiased and up-to-date with the latest scientific insights into sperm quality and fertility success rates. Studies have shown that AI-driven sperm sorting can decrease human-related errors by up to 25 per cent, improving sperm selection quality in terms of morphology and motility.


Reduction of Sperm Damage- The new AI-driven sperm sorting techniques also include microfluidic systems that are known to exhibit several advantages over the most commonly used conventional method, which is centrifugation. Traditional centrifugation methods, such as density gradient centrifugation, also cause severe oxidative stress and DNA fragmentation of the sperm because of the very high mechanical forces involved. The AI-infused microfluidic sorting minimises this damage significantly by involving gentler processes that mimic the natural pathway of sperm selection. The studies show that the process of microfluidic sorting decreases DNA fragmentation in sperm, which gives improved opportunities for success for IVF. For example, DNA fragmentation is 20 percent lower in sperm sorted using microfluidic processes than in traditional processing methods.


AI is bound to play an increasingly definitive role in fertility treatments, which will improve the outcomes for couples experiencing infertility.


(The author is a Co-Founder & CEO at SpOvum® Technologies. Views personal.)

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