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Why don’t you just delete the value statement from the consulting homepage? Why? Because nobody really cares! (I know, I am a bit mean.) Here’s a tip if you are not convinced it’s a useless thing: Move the consultancy’s value statement on a separate page on the consulting website and check the traffic to that page over a longer period (e.g. 6, 12, or even 24 months). Here’s what you will find: ZERO TRAFFIC !!! In his recent post, Florian Heinrichs explains why there’s no traffic to such ‘value statements’. Enjoy reading.

The Uncomfortable Side of Consulting Proposition Design We’ve learned that designing a stronger consulting proposition is often the easy part. The real test starts when leadership has to live with the choices that come with it. That’s where strategy meets behaviour, discipline and commercial reality. The Uncomfortable Side of Consulting Proposition Design.pdf A few uncomfortable observations in this carousel. Enjoy reading!

“What do people do with your product?” Product marketing is 95% about asking the right questions with the exact right wording. When trying to uncover the Use Case of a product, changing a single word of that question can take you down a bunch of (misguided) paths. If you ask “WHY do people use your product?” ...you’re likely to hear a bunch of outcomes (i.e. “we use it to help us grow our business”). If you ask “HOW do people use your product?” ...you’re just as likely to hear a use case, a product capability, or an outcome. If you ask “what do people do with your product?” ...you’ll be more likely to hear the use cases! Test this with ChatGPT: Ask “what do people do with....” and then insert a software product of your choice, and you’ll get a list of use cases supported by the key product capabilities. I’ve shared some example use cases below: (and before anyone freaks out, these are not the ONLY use cases of these products, just sample ones I found using a combination of ChatGPT and their websites). | 26 comments on LinkedIn

𝗙𝗼𝘂𝗿 𝗔𝗰𝗾𝘂𝗶𝘀𝗶𝘁𝗶𝗼𝗻𝘀. 𝗢𝗻𝗲 𝗩𝗶𝘀𝗶𝗼𝗻. 𝗧𝗵𝗲 𝗘𝗺𝗲𝗿𝗴𝗶𝗻𝗴 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺. Over the last few months, I’ve been paying close attention to a series of acquisitions that, when viewed together, tell a much bigger story about where industrial software is heading. First, AVEVA brought 𝗧𝘄𝗶𝗻𝗧𝗵𝗿𝗲𝗮𝗱 into its portfolio, strengthening its capabilities in predictive operations and industrial AI. Then came 𝗖𝗿𝗼𝘀𝘀𝗲𝗿, adding edge data processing, contextualization, and real-time analytics closer to the source. More recently, Schneider Electric announced agreements to acquire 𝗖𝗼𝗴𝗻𝗶𝘁𝗲 and 𝗔𝗶𝗗𝗔𝗦𝗛, adding industrial data contextualization, knowledge graphs, digital twins, climate intelligence, and infrastructure resilience capabilities to the broader ecosystem. Individually, each of these moves makes sense. Collectively, they reveal something more interesting. 👉 𝗪𝗲’𝗿𝗲 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝘁𝗼 𝘀𝗲𝗲 𝘁𝗵𝗲 𝗽𝗶𝗲𝗰𝗲𝘀 𝗰𝗼𝗺𝗲 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿 𝗳𝗼𝗿 𝗮 𝘁𝗿𝘂𝗹𝘆 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺. The architecture below is my attempt to visualize what that future could look like: 🔹 𝗦𝗰𝗵𝗻𝗲𝗶𝗱𝗲𝗿 𝗘𝗹𝗲𝗰𝘁𝗿𝗶𝗰 providing the operational and energy management foundation 🔹 𝗖𝗿𝗼𝘀𝘀𝗲𝗿 connecting and processing data at the edge 🔹 𝗖𝗼𝗴𝗻𝗶𝘁𝗲 creating context across engineering, maintenance, and operational data 🔹 𝗔𝗩𝗘𝗩𝗔 serving as the industrial intelligence and collaboration platform 🔹 𝗧𝘄𝗶𝗻𝗧𝗵𝗿𝗲𝗮𝗱 turning operational data into predictions and actionable recommendations 🔹 𝗔𝗶𝗗𝗔𝗦𝗛 extending intelligence beyond the plant into sustainability, climate risk, and critical infrastructure management The real challenge is building the foundation that allows AI to deliver meaningful outcomes. Data needs to be connected. Assets need to be contextualized. Information needs to be trusted. Only then can advanced analytics, digital twins, copilots, and autonomous decision-making create real value. For years we’ve talked about IT/OT convergence. What we’re beginning to see now feels like the next step: 𝗢𝗧 + 𝗘𝗱𝗴𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 + 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 + 𝗔𝗜 + 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Whether this exact architecture emerges or not, the direction seems increasingly clear. 👉 𝗧𝗵𝗲 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗶𝘀 𝗺𝗼𝘃𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝘀𝘁𝗮𝗻𝗱𝗮𝗹𝗼𝗻𝗲 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼𝘄𝗮𝗿𝗱 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗺𝗮𝗸𝗶𝗻𝗴. #Industry40 #IndustrialAI #IIoT #DigitalTransformation #SchneiderElectric #AVEVA #Cognite #Crosser #TwinThread #AiDASH #DigitalTwin #IndustrialIntelligence #EdgeComputing #Sustainability #OperationalExcellence

Productisation starts with value definition, not process standardisation. The strongest consulting firms do not begin by designing SOPs. They first decide which business problems are worth building expertise around, which outcomes they want to influence repeatedly, and where expertise should compound. Those choices create the foundation for repeatability, stronger value articulation and better value monetisation. Productisation then becomes a logical consequence rather than a forced SOP exercise.

A surprisingly good video about something that goes beyond the format itself. Vinyl, CDs, Spotify, good speakers, collecting music, or just listening more intentionally. The interesting part is what happens when you start caring about the music again instead of treating it as background noise. Worth watching if you’re into music, audio, or collecting things for reasons you can’t entirely explain.

🚀 Bridging Legacy Rockwell PLC Data to Modern OPC UA Systems – Securely Across Firewalls! Many industrial plants still rely on Rockwell ControlLogix, CompactLogix, and MicroLogix PLCs connected to OPC DA servers for SCADA and HMI applications. But how can this valuable data be shared securely with modern IT, MES, Historian, Cloud, and IIoT platforms? ✅ Solution: OPC Tunneller + OPC UA Architecture: 🔹 Rockwell PLC → Ethernet/IP 🔹 OPC DA Server → Data Collection 🔹 OPC Tunneller → Secure DA-to-UA Conversion 🔹 Firewall → Encrypted Communication 🔹 OPC UA Client → SCADA, MES, Historian, Cloud & Analytics Key Benefits: ✔ Secure communication across firewalls ✔ No need to open inbound ports ✔ Convert legacy OPC DA data to modern OPC UA architecture ✔ Reliable data exchange between OT and IT networks ✔ Ideal for Industry 4.0 and IIoT applications This approach helps industries extend the life of existing automation systems while enabling secure digital transformation. #Rockwell #ControlLogix #CompactLogix #OPCDA #OPCUA #OPCTunneller #IndustrialAutomation #SCADA #IIoT #Industry40 #MES #Historian #EtherNetIP #OTIT #DigitalTransformation

TOP 10 SCADA PLATFORMS - 2026 EDITION SCADA remains a critical part of modern industrial automation, connecting field devices, PLCs, RTUs, control systems, operators, and enterprise applications. Here is my editorial list, based on industrial adoption, capabilities, scalability, and application fit: 1. Honeywell Experion HS 2. Inductive Automation Ignition 3. AVEVA Plant SCADA 4. Siemens WinCC 5. Schneider Electric Geo SCADA Expert 6. Rockwell FactoryTalk View SE 7. GE Vernova Proficy iFIX 8. COPA-DATA zenon 9. Mitsubishi Electric / ICONICS GENESIS 10. VTScada Of course, there is no universal #1 SCADA platform. The ranking is simply my personal editorial assessment, based on my experience and perspective not a formal market study or statistical ranking. Every platform has its own strengths, and the right SCADA solution depends on factors such as: PLC/RTU ecosystem System scalability Cybersecurity requirements Industry and application High availability and redundancy Integration with existing control systems Overall control-system architecture Which SCADA platform would you rank #1? Share your experience and ranking in the comments. 👇 Personal views only. This ranking is based on my own professional perspective and does not represent my current or past employers. #SCADA #IndustrialAutomation #PLC #DCS #OT #Automation #IndustrialCybersecurity #IIoT #ProcessAutomation #Digitalization | 61 comments on LinkedIn

Positioning for early stage and growth stage are different in five major ways: 1️⃣ Market Difference ES: exploring multiple segments... hoping to conquer ONE of them GS: have fit with one (or more) segments... deepening penetration 2️⃣ Product Difference ES: half-built, partially-functioning MVP GS: one or more products in market and loved by customers 3️⃣ Team Difference ES: tight group of original founders making decisions in lockstep GS: multiple VP-level stakeholders (with potentially different opinions) 4️⃣ Brand Difference ES: nobody has heard of you GS: you have recognition (and ideally some clout) 5️⃣ Execution Difference ES: exploring growth strategies GS: exploiting working growth strategies Key: ES = Early Stage GS = Growth Stage | 26 comments on LinkedIn

Top 10 PLC basics every beginner should understand. 1. PLC hardware 2. Digital inputs 3. Digital outputs 4. Ladder logic 5. Timers 6. Counters 7. Analog signals 8. PLC communications 9. Diagnostics and troubleshooting 10. Program structure These are the fundamentals that help build a strong foundation in PLC programming and industrial automation. If you are starting your PLC journey, save this poster and use it as a quick reference. #plc #automation #basics

The B2B market segmentation that most people forget about... Product ‘adoption mentality’. It’s a simple concept: Companies (and the leaders that work at them) have different approaches to buying new technology products. Some are more aggressive in trying the bleeding edge “new thing”, and others are very risk averse, waiting to see how things pan out for the early adopters before making a decision. Most marketers and founders know this, but shockingly few put it into practice with their positioning strategy. In practice, you MUST position for these unique audiences SEPARATELY. Take Salesforce for example (see image) *Note of how the messaging strategy shifted as they penetrated the early market and moved into the mainstream market. 🟧 EARLY MARKET The audience: Tech Enthusiasts and Innovators The strategy: Explain the technology and the potential for game-changing outcomes. These early adopters are risk takers that are looking for breakthrough competitive advantages. They’ll be the ones to pull the technology you’ve built out of your hands and figure out the best way to use it. They’ll also shoulder a lot of the implementation and change management work to bring the technology into their business. 🟩 EARLY MAJORITY The audience: Struggling Pragmatists The strategy: Pick a beachhead segment and message on a specific use case. These folks don’t want to adopt new technology, but are forced to because they are struggling with their current way of doing things. They won’t care about your vision or how cool the technology is. The key here is delivering such a specific message that the prospect goes: “Holy cow, that’s exactly what I’m struggling to do”. You’ll also have to make a promise to support what Geoffrey Moore calls the “whole product”. This is all the supporting pieces that help integrate the new tool into the organization (documentation, training, integrations, etc.) The goal of this strategy is to land a well-known logo to adopt your new thing, so you can use them as a point of reference for the mainstream market to follow. For Salesforce, that lighthouse customer was Sun Microsystems. 🟦 LATE MAJORITY The audience: Pragmatic Followers The strategy: Show them how much success your existing pragmatic customers are having with your use cases. This is the tipping point, and in some ways it’s the easiest to execute because you’ve already had success with a lot of customers (and have the whole product working). So it’s really about creating FOMO for these late adopters to come along. - - - The key takeaway for early stage B2B founders? Be extremely aware of your ideal audiences approach to adopting new products. It is easy to get lost in the B2B tech bubble, assuming everyone is willing to adopt a new approach. #b2bmarketing #positioning #messaging *If you are looking to go deeper into this concept of adoption. I highly recommend you read Geoffrey Moore’s ‘Crossing the Chasm’. It’s pure gold. | 12 comments on LinkedIn

Does consulting have a revenue quality problem? For decades, consulting firms have grown by selling expert capacity. Smart people, organised into projects and teams, monetised through hours and days. It has been an extraordinarily successful business model, and it still generates most of the revenue in many consulting firms. But there are good reasons to start changing that revenue mix. So, why now? We see 4 pressures coming together. 1. The AI double squeeze. AI reduces the labour required for certain consulting activities, while enabling clients to perform more lower-stakes work internally. Both put pressure on labour monetisation. 2. Commercial sameness. Consulting firms increasingly look and sound alike. AI accelerates this by making polished content, frameworks and thought leadership easier for everyone to produce (see my post from y-day - link in comments). 3. Buyer hesitation. Buyers are overwhelmed with similar messages and increasingly cautious about consulting spend. They want greater confidence in the path towards outcomes. 4. Budget pressures. Consulting budgets face greater scrutiny. Loosely defined work becomes harder to defend when buyers need a stronger economic case. This is why we believe consulting firms need to progressively move a larger share of their revenue from capacity-led towards value-led work. We call this “The Shift.” Value-led work starts with greater specificity around the problems a consulting firm repeatedly solves, the context in which it creates the most value, the outcomes it can credibly influence and the path it repeatedly uses to get there. That specificity has important commercial consequences: - delivery becomes more repeatable and less variable - expertise, data and IP accumulate across engagements - proof becomes stronger and more relevant - buyers gain greater confidence - pricing becomes more strongly connected to value - growth becomes less dependent on proportional labour growth None of this requires consulting firms to walk away from existing capacity-led revenue. For most established consulting firms, that would make little commercial sense. The opportunity is in the rebalancing. 👉 𝗛𝗘𝗥𝗘’𝗦 𝗠𝗬 𝗔𝗗𝗩𝗜𝗖𝗘 Keep monetising valuable capacity-led work while deliberately building a growing value-led revenue engine alongside it. Then measure whether that engine delivers stronger pricing, better margins, higher revenue per FTE, and superior commercial performance. One question deserves a place on the leadership agenda: “How much future growth should continue to come from adding labour, and how much can come from getting better at monetising expertise and intellectual capital?” ‘The Shift’ is the progressive redesign of a consulting firm’s revenue architecture around specific, repeatable client value.

𝐒𝐭𝐮𝐮𝐫 𝐣𝐢𝐣 𝐟𝐨𝐭𝐨’𝐬 𝐯𝐚𝐧 𝐣𝐞 𝐭𝐞𝐥𝐞𝐟𝐨𝐨𝐧 𝐨𝐨𝐤 𝐧𝐨𝐠 𝐰𝐞𝐥𝐞𝐞𝐧𝐬 𝐧𝐚𝐚𝐫 𝐣𝐞𝐳𝐞𝐥𝐟 𝐯𝐢𝐚 𝐖𝐡𝐚𝐭𝐬𝐀𝐩𝐩 𝐨𝐟 𝐦𝐚𝐢𝐥 𝐨𝐦 𝐳𝐞 𝐨𝐩 𝐣𝐞 𝐥𝐚𝐩𝐭𝐨𝐩 𝐭𝐞 𝐤𝐫𝐢𝐣𝐠𝐞𝐧? 🙈 Ik deed dat dus. Want ik hou van mijn iPhone, maar óók van mijn Windowslaptop. 😅 Totdat ik PairDrop ontdekte. Je opent gewoon pairdrop.net op je telefoon én laptop en kunt je foto’s rechtstreeks overzetten. Zonder kwaliteitsverlies. Hoe het werkt: Open pairdrop.net in de browser op beide apparaten Zorg dat ze op hetzelfde wifinetwerk zitten Klik op je laptop die op het scherm van je telefoon verschijnt Selecteer op je telefoon de foto’s die je wilt versturen Accepteer ze op je laptop En klaar. 🙌 Geen account, geen app en geen kabel nodig. Misschien kende iedereen dit allang behalve ik, maar ik vond het dus echt handig. 😅 👩‍💻 Ik ben Anne en ik help bedrijven aan meer klanten door online ads 💡 www.bureaubloeiwerk.nl

Not all “benefits” are created equal: Some belong in your website. Some belong in your sales deck. Some belong in your investor pitch. Benefits (or “outcomes”) cascade into each other. Ideally, one benefit causes another benefit. We refer to these causal chains as “1st order benefits,” “2nd order benefits,” “3rd order benefits,” and so on. There are also different benefits for individuals/teams, companies, and even the industries as a whole. Take a company like Figma. Depending on the audience, the benefits shared can (and should!) vary wildly. Try filling out this canvas in the picture below for your own company to see which benefits you should use (and where!) | 26 comments on LinkedIn

Brilliant founders often struggle with content strategy. Average thinkers often nail it. Why? How to build an audience on LI is a bit misleading. You might think it’s about... → the quality of your thinking → the strength of your product → your years of experience But it has little to do with that. It actually depends on where you create on the spectrum. Here’s what I mean (and how people get this wrong): Content exists on a spectrum. → On one end it’s high-level & outcome-oriented → On the other it’s tactical & action-oriented → And everything in between Roughly 7 layers total. Here’s what it looks like at a glance. High Level / Abstract ↑ | Layer 1 - The outcomes you provide | Layer 2 - Your main point of view | Layer 3 - Strategic-level content | Layer 4 - Framework content | Layer 5 - Simple guides | Layer 6 - Tactical help | Layer 7 - Micro-hacks ↓ Detailed / Practical Here’s what happens when you roll the content out: → The top of the spectrum attracts stakeholders. → The bottom of the spectrum attracts practitioners. → The top of the spectrum can help close deals. → The bottom is what actually grows your audience. Here’s the problem for smart people: Brilliant people often prefer layers 1, 2 & 3. → They think that anything else is “dumbing it down.” → So they focus there... and their reach stays tiny. Average thinkers often prefer layers 5, 6 & 7. → It feels fun and intuitive to them. → So they focus there... and their audience grows. Yes, you need all 7 layers for a long-term business. But it’s generally best to build from the bottom up. → Focus on the bottom of the spectrum. → Build an audience by helping people win. → Then monetize it as it grows. There’s a lot of debate on this. “You don’t need to have a big following!” “Just reach the RIGHT people.” There’s some truth to that. But think about it this way: You can sell to people who barely know you. | or | You can sell to people who already follow you. I recommend the second option. - Check the graphic for ideas for the bottom layers - Save this post for content inspo for later | 41 comments on LinkedIn

A LOT of consulting services were designed “inside-out” ... and it’s a real issue. See, here’s how a lot of consulting services spring into existence: A firm starts with what it knows, what its people are good at, and how its practices are organised around this expertise. Then, it packages its capabilities into structure- and category-aligned services ... and hopes clients can connect the dots and spot the differences. But, alas: Most of the time, clients can’t (or won’t), which, usually, means the firm has to compete on existing relationships, price, or simple luck. And in some cases (I’ve been involved in a few), it means it doesn’t get to compete at all, because starting from your capabilities can mean you’re putting something together for which there’s simply no pressing need in the marketplace at all... ... and so the response you get is *crickets*. There’s a better starting point, though - and it’s almost the reverse of everything I’ve just described: 1️⃣ Start with the fully resolved outcome, i.e., the ideal end state you’re trying to get clients to through your service: what does their clients’ “world” look like when the issue is completely behind them? 2️⃣ Then work backwards. What had to happen for that to be true? And before that? And before that? 👉 What you end up with is a map of the client’s journey from problem to resolution... including a set of natural inflexion points where progress tends to stall unless specific support is available. (Luk Smeyers and I refer to this as the - idealized - Client Success Journey and its milestones). Those milestones, then, are where your services belong. Not “here’s what we can do” - but “here’s where clients usually struggle or get stuck on this journey, here’s what they typically need in this situation, and here’s how we often help them through it.” This reframe changes what a service is: not a packaged capability, but a designed intervention at a specific, predictable point in a journey the firm understands better than anyone. And it changes what a service portfolio looks like: not a menu of loosely related things the firm can do, but a sequenced set of offers that map to real client needs, in the right order, with a clear logic connecting them. Luk and I have written, like, a lot about designing these systems in practice; I’ve tried to package the high-level gist of it in the document below. As a friend of mine always put it: You can either sell time, or a solution... the important thing is to choose and commit. Hope this helps!

PLC Data Types: Mastering PLC programming starts with understanding its foundational building blocks: Data Types. Whether you’re working with Siemens SIMATIC controllers or other IEC 61131-3 compliant platforms, knowing your data sizes, ranges, and structures is critical for writing efficient, error-free automation code from handling simple bits to processing complex floating-point math and timestamps. I put together this quick-reference cheat sheet covering: Signed & Unsigned Integers (SINT, INT, DINT, LINT & their USINT counterparts) Bit & Bit String Data Types (BOOL to LWORD) Real / Floating Point Types (IEEE-754 Single & Double precision) Character, String, Time & Date formats Save this post for your next PLC project, and let me know in the comments what is your most frequently used data type in your day-to-day programming? Personal views only; not representative of My current and past employment experiences. #PLC #Automation #IndustrialAutomation #Engineering #Siemens #ControlsEngineer #Manufacturing #IEC61131 | 10 comments on LinkedIn

Consulting firms must reduce their labour-growth dependency. The commercial model will not change overnight. But the direction should be deliberate: progressively move more revenue from capability- and capacity-led work towards focused, repeatable consulting propositions. As AI increases pressure on labour-based economics, consulting firms should accelerate this switch and connect more revenue growth to value monetisation rather than additional labour effort.

Ten trends in Silicon Valley that have kept surfacing this summer. --- 01. The age of abundance is ending - but not for everyone. 02. The era of abundance created the “inbound seller.” 03. The market wants outcome-based, but most can only deliver usage-based. 04. Retention is not killing SaaS. The collapse in acquisition is. 05. GTM teams fund AI Fluency and mistake it for Productivity. 06. Applying AI in GTM is harder than applying it in Product. 07. We have entered the era of refounding: Fin vs. Airtable. 08. SaaS is splitting into SaaSpocalypse, SaaSurrection, and a silent majority. 09. Pipeline is increasingly built one small, local event at a time. 10. The Valley acts as if the AI race is over. Is it? --- | 56 comments on LinkedIn

Positioning = segmentation + categorization + differentiation | 24 comments on LinkedIn