Why Data Pushback Is Often About Trust and Identity

We had a conversation recently with someone that leads data and analytics for procurement at a large enterprise. Every week, he is being asked by procurement colleagues: - “Can we get better supplier insights?” - “Can we trust our spend?” - “Can we roll this up to the parent?” - “Can we use this for AI?” All reasonable questions. And on the surface, they sound simple. He has the systems. He has the data warehouse. He has the reporting layer. He has a strong team. So the expectation is: “We should be able to do this.” But here is what that actually looks like from his side. - Hundreds of thousands of vendor records. - Multiple ERPs. - Different formats. - Different naming conventions. - Missing identifiers. - Inconsistent hierarchies. - The same supplier… five, six, sometimes ten different ways. And no reliable way to validate any of it. At one point, he said: “Everyone keeps asking for better data… but they do not realize what it takes to get there.” So the team does what every data team does. - They try to fix it. - Fuzzy matching. - Internal logic. - Manual reviews. - Exception handling. Weeks turn into months. There are no light at the end of the tunnel. Because this is not just messy data. It is unresolved identity across systems. And then the pressure comes back. - “Why is this not accurate yet?” - “Why can’t we trust the numbers?” - “Why does this not match across reports?” He said something that really stuck with us: “We are spending more time fixing the data than using it.” This is the part that is often misunderstood. Procurement is asking for better insights. Better analytics. More automation. But what they are actually asking for is: A clean, reconciled, trusted supplier identity layer And that is not something you can build with workflows. Or dashboards. Or another tool on top. Because if you cannot answer: “Who are we actually doing business with?” Nothing downstream really works. The most advanced teams are stepping back and recognizing this is not something they can “clean their way out of.” They are reframing the problem entirely: 👉 Not “how do we fix the data?” 👉 But “how do we fix the foundation?” Because once supplier identity is resolved: 1. Spend actually rolls up 2. Hierarchies make sense 3. Data becomes consistent across systems 4. Insights become usable And the pressure on data teams… finally lifts He put it better than I could: “We thought we had an analytics problem. We actually had a supplier identity problem.” If you are in procurement or data, I am curious: Do your teams fully understand the complexity behind “better data”? Or are you still being asked to solve it without the right foundation?

I keep seeing the same pattern. People don’t lose trust in data because the numbers are wrong. They lose trust because they can’t see the story behind them. That’s why the discussion at the GSS Conference hit home. Analysts and comms teams often feel like they’re running in parallel lanes. One pushes for speed. The other pushes for precision. But the public only sees one thing. A number that either feels clear and honest. Or confusing and questionable. Online platforms make this even sharper. A single chart can fly across TikTok or X with no source, no context and no clue who produced it. When that happens, even good data gets treated with suspicion. And once trust slips, the damage spreads fast. Intelligent transparency is the fix. Not layers of paperwork. Not more disclaimers. Just simple clarity. Show where the number came from. Show how it was worked out. Give people enough to check for themselves without burying them in detail. When information is open and traceable, confidence rises naturally. But transparency isn’t something you bolt on at the end. It starts early. Comms teams need the runway to explain data clearly. Analysts need the space to publish without political pressure. Leaders need to set the expectation that honesty beats spin every single time. Three behaviours make the difference. Equal access to the data for everyone. Clear explanations of what a figure means and what it doesn’t. And release decisions made by experts, not political calendars. Get those right and something powerful happens. Data stops feeling like ammunition. It becomes a shared tool people can use to make informed decisions. Where could your organisation make its data story easier for the public to follow? #data #datasharing #transparency #UK

Two clients. Two contracts. Two different reactions from me. Client A brought me in as a strategic partner. I was thinking with them, treated as an expert even. Pay reflected that. Client B hired me to execute. Clear scope and clear deliverables. Pay was...lower. Both contracts had the usual obscure legalese, standard for large firms. Me though, I wasn't standard. With Client A, I skimmed the terms, signed, moved on. I pushed back only where necessary, and they accepted. With Client B, I found myself negotiating every clause, questioning timelines, protecting my scope like it was under threat. My brain ran to the worst-case. Now, I pride myself on delivering the same quality regardless, but the energy I brought to protecting myself..same clauses with low likelihood of mattering. Why did I act differently? One relationship made me feel like a partner, while the other made me feel like a vendor. Vendors protect themselves because nobody else will. Guess what? Your customers do the same thing. When someone feels valued by your brand, they forgive the friction. Clunky checkout? Fine. Unclear refund policy? Alright. They trust your intent. When someone feels like a transaction, they scrutinize everything. Now every friction point feels like a trap. Trust is built in the moments before someone even encounters the fine print. How you make people feel determines how they respond to your ask. Every "why are customers pushing back?" conversation should start with: do they feel valued or processed? Anything processed is not good for the long-term :)

Resistance Is Not the Problem. Misreading It Is. In manufacturing Industry , resistance is often treated as friction. On the shop floor, it is often treated as disobedience. In reality. it is neither. After three decades of leading large-scale transformations, I have come to see resistance differently: It is one of the most underutilized data streams in leadership. A recent HBR insight articulated this well / what leaders often dismiss as “pushback” is rarely irrational. It is usually a signal of something deeper: loss, uncertainty, exclusion, or even a flaw in the change itself. But in the pressure to deliver outcomes, we don’t diagnose - we interpret. We label. We accelerate. We override. And in doing so, we miss what matters. In every transformation I have led, resistance has pointed to one of four realities: • A perceived loss — of control, identity, or relevance • Uncertainty — where clarity has not translated into conviction • Lack of ownership — when change is done to people, not with them • Execution gaps — where strategy looks sound, but reality disagrees Ignoring these doesn’t remove resistance. It only drives it underground. The real leadership test is not eliminating resistance - it is interpreting it without ego. Some of our most critical operational improvements did not come from strategy reviews. They came from uncomfortable questions on the ground: “Will this actually work at scale?” “Have we considered downtime implications?” “Who owns this when things go wrong?” Those questions didn’t slow us down. They saved us from moving fast in the wrong direction. But clarity is equally important. Once you have listened, understood, and refined - you must hold the line. Because leadership is a balance: Empathy for concerns. Firmness on standards. Listening does not mean dilution. It means better decisions before decisive execution. A simple shift I’ve learned to make: Don’t ask → “Why are they resisting?” Ask → “What truth is this resistance revealing?” Because when resistance disappears too quickly, it often means one thing: People have stopped trusting that their voice matters. And that is where transformation truly fails. Great leaders don’t fight resistance. They convert it into insight—and then into action.

Last week I wrote about comms being asked to deliver "quick" tactical without starting with the why. It went a bit viral, which tells me this is the reality for many. I wanted to expand on the newsletter example I shared in that post. I was new to the business, and the R&D leadership team I supported wanted to showcase their team’s achievements. They felt a newsletter would do the job. The intent made sense because recognition matters. But the audience wasn’t really the focus. R&D teams are time-poor. They don’t want long updates. They want content that helps them do their jobs, navigate process, understand what’s changing, or collaborate more easily. And they often prefer content created by peers over anything that comes ‘from the top’. This felt more like visibility for senior leaders than something their teams were asking for. I asked why a newsletter. The answer? “We’ve done it before.” I explained it would take a lot of time – multiple contributors, coordination, editing. I suggested other options, but without data to discourage them, they wanted to try it. They were fairly adamant and I felt I was too new in the role to fully push back. So after a discussion with my manager, I agreed to lead the project on the condition we’d review it after three months. To make that review meaningful, I set up tracking - click-throughs to SharePoint stories and time spent on those pages. The results weren’t surprising: initial interest dropped, stories weren’t being read, and the teams producing them were stretched. It became too hard. So we shelved it. What helped here was having the metrics. Even if you’re experienced, data gives weight to your advice - especially before you’ve built trust. It shifted the conversation from opinion to evidence: time, effort and value. In time, we redirected our focus to Viva Engage where recognition felt more authentic because it was peer-driven. Sometimes it came from leaders, but often it was teams recognising each other. We started to build a community, but it was a better fit for how people want to work and receive content. The more we use data to back our advice, the stronger our position becomes. This is how you build trust and shift the conversation next time.

If you want to understand how your organisation 𝗿𝗲𝗮𝗹𝗹𝘆 works – listen to the language. Having spent hundreds of hours doing discourse analysis, I’ve come to trust this: 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗵𝗼𝗹𝗱𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. Power. Identity. Belonging. Defensive routines. System boundaries. How people make sense of their roles, challenges and change. You can hear in a sentence what a 40-slide deck won’t tell you. So how can you take some simple first steps? It’s easy: pay attention to the pronouns. 𝗪𝗲. 𝗨𝘀. 𝗧𝗵𝗲𝗺. 𝗧𝗵𝗲𝘆. 𝗜. These tiny words carry big meaning. 🔸 Who’s included in “𝘄𝗲”? 🔸 Who’s excluded as “𝘁𝗵𝗲𝘆”? 🔸 When does someone switch from “𝗜” to “𝘄𝗲” – and back again? Every time someone uses those words, they’re drawing a boundary and making a distinction. It reveals how they see the system – and their place in it. Sometimes it’s useful: 🔸 “𝗢𝘂𝗿 job is to deliver quickly for the business – 𝘁𝗵𝗲𝗶𝗿 role is to make sure we’re doing it in a way that’s safe and sustainable.” Often, it’s more loaded: 🔸 “We’re doing everything 𝘄𝗲 can… but 𝘁𝗵𝗲𝘆 keep changing the goalposts.” 🔸 “𝗧𝗵𝗲𝘆 don’t listen.” 🔸 “That’s not 𝗼𝘂𝗿 responsibility.” Social identity research shows how easily humans fall into in-group/out-group thinking – even with arbitrary differences. In organisations, those distinctions become habits. They shape who we trust, where we push back, and how we respond to change. In Organisation Development, listening to language helps you spot the real system beneath the surface: 🔸 Who people feel accountable to 🔸 Where the real alliances sit (formal or informal) 🔸 Where trust sits – and doesn’t 🔸 How change is being positioned 🔸 Where blame, cynicism or learned helplessness have taken root These patterns are often more revealing than structure charts or strategy documents. They’re the front-end of the system logic people are operating from. You don’t need a major intervention to start shifting things. Sometimes, just helping people become more aware of how they’re seeing the world is enough. 🔹 Where they’re making distinctions 🔹 What they’re including – and what they’re leaving out 🔹 Whether they’re caught up in the day-to-day or able to step back and see the bigger picture You can start with simple, well-placed questions: 🔹 “When you say 𝘁𝗵𝗲𝘆, who are you seeing?” 🔹 “What are you paying attention to – and what might you be filtering out?” 🔹 “If someone else told this story, what would be different?” Helping people notice how they’re constructing their view of the organisation – and how it might be limiting their options – is a systems move in itself. It opens up new choices and that’s where real change begins. When was the last time you noticed a “𝘄𝗲” that didn’t quite include everyone or a “𝘁𝗵𝗲𝗺” that quietly encouraged division?

The biggest barrier to AI adoption? It's not skill, time, or tech. It's identity and fear. A few years ago, I was working on an internal tool to automate part of a technical team's work. The resistance was enormous. I couldn't understand it. The tool would save them hours on boring tasks. Why weren't they excited? I assumed they were stuck in their ways and didn't want to learn anything new. In reality, I just needed to sit with them to learn that: 1 - Their incentives weren't aligned Their KPIs were tied to the process I wanted to automate. To get buy-in, I had to change how their success was measured. 2 - I was talking features, not benefits I focused on what the tool did (automation) instead of what it gave them (time saved, deeper insights). 3 - They were afraid This wasn't about one tool. It was about what came next. If I could automate this, what else could I automate? Would their jobs disappear? Would their expertise become worthless? No amount of stakeholder management, product adoption strategy, or talking points work when someone is in fear. In fear of losing their job and seeing their experience - their identity - thrown away. What helped was showing an alternative path. I mapped out what else the team was needed for. Work that added more value. Work that couldn't be automated. I'm seeing the same pattern now with AI. The pushback isn’t due to a lack of understanding of the technology, but to fear of what it means for them. So this is a reminder for empathy. Assume people are smart and want to succeed. And instead of starting by talking about the automation, take the time to listen. See if there’s a shared understanding of what the future can look like for everyone involved. Show them a future where they're thriving, not just surviving.

You can’t build trust technology with a “move fast, break things” mindset. ❌ This approach might work when a broken feature only causes temporary friction, not real financial or security consequences. It stops working the moment trust, identity, or security sit at the core of how your business operates. In banks, telecoms, and regulated environments, breaking things does not lead to learning. It creates exposure. When trust is lost, it is rarely a local problem. It affects customers, partners, regulators, and reputation all at once. 💥 I have seen this play out more than once. Teams push for speed, celebrate quick delivery, and only later realize that early shortcuts quietly shaped systems in ways that are difficult and expensive to unwind. What often gets missed is how trust systems actually fail. It is rarely loud or obvious. More often, issues show up in edge cases, fallback flows, and assumptions that were never tested at scale. ⚠️ In practice, a “move fast” mindset in organizations where trust is central often leads to: 👉 progress that looks successful on the surface but hides real risk 👉 ownership becoming unclear as work spans multiple teams and partners 👉 risk being postponed instead of addressed intentionally 👉 processes that work in normal situations but fail under stress The alternative is not moving slowly or avoiding ambition. It is moving with clear intent. Designing with accountability, strong defaults, and the assumption that systems will be tested under pressure, at volume, and across borders. 🔐 This matters most in industries like financial services and telecommunications, where identity and access are tied directly to money, services, and everyday customer trust. 💸 Speed still matters. Shipping still matters. But in trust-critical infrastructure, responsibility has to be part of the design from day 1, not a reaction after something breaks. This mindset may feel slower at the start, but it is the only one that truly scales when trust is at stake. 🎯 #DigitalIdentity #TrustInfrastructure #RegulatedIndustries

The brands that win won’t be the ones collecting the most data— but the ones customers choose to share it with. Today, I opened a website on my phone and was greeted with a full-screen consent prompt. Not once, but again—despite having visited before. This isn’t friction. It’s fatigue. For users, for marketers, for developers, for regulators. And the core problem isn’t just cookies or pop-ups. It’s the underlying architecture of the internet—where identity is fragmented, consent is siloed, and users are treated like strangers at every touchpoint, even if they’ve already verified once before. Even worse, users are missing out on recognition and losing trust with how (and where) brands are managing their data (ex. The latest massive data hack, 23andme, etc…). Latest data suggests up to 30% conversion fallout on a first-time site visit. But change is here. 🔐 Users expect control over their data—and transparency from the brands they engage with. 🤖 AI is raising the bar—demanding real-time personalization and verified identity signals for both humans and agents. 📉 The cost of low trust—abandonment, churn, wasted spend—is too big to ignore. In this new era, identity and consent aren’t checkboxes. They’re a relationship. Reusable. Interoperable. Owned by the user. And for companies that want to remain relevant—or simply survive—this shift isn’t optional. It’s why we’re building trust ID.