Ecosystem Strategy Development

A picture is worth a thousand words: Procurement Software vs. the Procurement Ecosystem. When comparing software solutions, many forget a critical aspect: the Procurement Ecosystem. Procurement teams get short sighted with the one biggest pain point they face right now. Here is everything you should consider before you invest: --- 1. Digitisation vs Digitalisation. These terms are often confused and not understanding the difference can be a barrier to delivering maningful progress. The 2 terms defined (Gartner): - Digitisation: The process of changing from analog to digital form. - Digitalisation: The use of digital technologies to change a business model and provide new revenue & value-producing opportunities; the process of moving to a digital business. True adoption of a digital Procurement approach requires - Willingness to change - Change management initiated from within the business whereas digitisation is a straight copy of the existing analog to the digital. When investing in digital, it's important to evaluate your existing process first, or you could end up lip-sticking a pig. Cementing already clunky processes with tech is an expensive mistake. --- 2. What to choose? At this year's DPW Amsterdam 2024, the theme is 10X The need for organisations to think and act ten times bigger than their current capacity. I love the ambition. But how can you 10X your Procurement ecosystem if you don't know what's on the market and you don't have a 10X investment budget? Events like DPW offer a great opportunity to survey the market and request demos of multiple tech vendors. When benchmarking, a few things to keep in mind: - User friendliness; UX/UI - The actual value add of the solution (time/ cost savings) - Integration with the ecosystem - use my picture below to assess - TCO of implementation and continued use - Overlap with existing systems - Scalability This is one area where a traditional requirements led tender is unnecessarily constraining. Narrow down to a few options specific to your industry and business specific needs. But allow the providers to come forward with a solution that still has room for creativity and innovation. A solutions workshop approach beats a straight-jacketed RFP here. --- 3. Build Scalable, Build Agile, Build Data A digital Procurement ecosystem needs some kind of agility & flexibility. The best tech vendors offer scalable solutions and aren't afraid to integrate. Some key differentiators all the best tech has - a strong API-architecture - cloud-based - Speed of adoption/ onboarding. Finally assess how the solutions will gather reliable data sets, visualise the data, push & pull data from other platforms and use data predictively (AI). --- Hope that helps. What are your thoughts? --- P.S. I'm Tom Mills. Follow me and join 12k+ to get 1% better at Procurement every week. You can also get all my deep dive articles and hi-res PDFs for free here: https://procurebites.com/

Decoded: The Architecture of Germany's Federated Digital Twin Ecosystem Germany is not building a single, centralized industrial cloud. Instead, Europe's industrial powerhouse is engineering something far more ambitious: a standardized, federated ecosystem designed for data sovereignty and global interoperability. Moving beyond the buzzwords of Industry 4.0 requires understanding the complex machinery underneath. I have visualized the complete "German Model" in this big-picture infographic, breaking down the stack from political foundation to operational application. Here is a walkthrough of the four critical layers that make this ecosystem function: 🔹 1. The Bedrock (Foundation & Standards) The ecosystem rests on a foundation of political consensus and rigorous theory. It is anchored by Plattform Industrie 4.0 and supported by the German government (BMWK, BMBF). Crucially, it adheres to global standards like RAMI 4.0 and IEC, ensuring it is built for international trade, not just domestic use. 🔹 2. The Core (Governance & The Universal Connector) At the heart of the machine sits the Industrial Digital Twin Association (IDTA), backed by major associations like VDMA and ZVEI. The IDTA manages the Asset Administration Shell (AAS). The AAS is the non-negotiable standard—the "digital USB stick" that allows hardware to describe itself in a language any software can understand. 🔹 3. The Highway (Infrastructure & Data Spaces) If AAS is the vehicle, Manufacturing-X is the highway system. Using Eclipse Dataspace Components, this layer enables sovereign, peer-to-peer data sharing across verticals. It connects domain-specific spaces like Catena-X (Automotive), Factory-X (Production), and Energy Data-X. 🔹 4. The City (Community & Application) The top layer shows the vibrant ecosystem building upon this infrastructure. It highlights the tight integration between Research Engines (Fraunhofer, RWTH Aachen), software Enablers (SAP, Siemens, Microsoft), and hardware Adopters (Festo, Bosch, Harting) that are turning the concepts into operational reality. The Strategic Takeaway: The German approach prioritizes federated standards over proprietary lock-in. By separating the "Type" (design phase) from the "Instance" (operational phase), it enables a true lifecycle synchronization loop, unlocking massive value in predictive maintenance and circular economy. This is the blueprint for a scalable, interoperable industrial future. How do you see the federated approach comparing to centralized hyperscaler models for industrial data? Share your thoughts in the comments. #DigitalTwin #Industrie40 #ManufacturingX #IDTA #AssetAdministrationShell #IndustrialIoT #DataSovereignty #SupplyChain #Siemens #SAP #Fraunhofer

The Canalys Channels Ecosystem Landscape offers an in-depth look at the technologies shaping competitive advantage for channel and partnership leaders. With 261 companies driving US$7.46 billion in revenue in 2024, this ecosystem is rapidly evolving towards a projected US$13.48 billion by 2028, highlighting the crucial role of automation and data-driven decision-making in partnership success. For 8 years, this unique “tech stack” research brings focus to the underlying technologies that will drive competitive advantage for channel and partnership leaders in the decade of the ecosystem. The hundreds of software companies represented in the landscape are providing automation and advanced digital capabilities to help companies design, develop, execute and manage a broad channel partner and alliance ecosystem. There are increasing demands on channel leaders to find, recruit, onboard, develop, incentivize, co-sell, co-market, co-innovate, measure, manage and report on partner value at scale. Automation of partner-related workflows, deeper integrations and data-driven decision-making create measurable competitive advantages (through partnerships) and are quickly becoming table stakes in the industry.

Digital Transformation Tip 24/2025: How to Redefine Enterprise Architecture (EA) for Smart Manufacturing?
 Core Principle: Transition from a static, process-centric EA to a cognitive, data-driven, and ecosystem-integrated architecture that enables autonomous decision-making, hyper-agility, and self-optimizing production systems.   Step 1: Transition from a Monolithic to an Agile, API-Driven Architecture ·     Break Down Silos: Move away from traditional, centralized IT/OT structures. Architect a decentralized, microservices-based ecosystem where new digital capabilities (e.g., IoT, AI, digital twins) are plugged in as discrete, interoperable components. ·     Practical Approach: Adopt API-first design principles that allow seamless integration between legacy systems and next-gen digital tools, ensuring rapid adaptability to market shifts.   Step 2: Embed a Data Fabric and Digital Twin Framework ·     Data Fabric: Redefine your EA to incorporate a unified data layer that connects disparate data sources (sensors, ERP, MES) across the shop floor and the corporate system. This fabric enables real-time visibility and decision-making. ·     Digital Twins: Create digital replicas of physical assets to simulate, monitor, and optimize production in real time. ·     Example: Implement digital twins of critical production lines, allowing you to run simulations that predict maintenance needs or process optimizations before any physical intervention is required.   Step 3: Integrate Real-Time IoT and Edge Computing ·     Dynamic Data Streams: Redesign your architecture to support continuous data ingestion from IIoT devices at the edge. This supports instantaneous analytics and operational adjustments. ·     Edge Processing: Deploy edge computing to reduce latency and offload critical computations from the central data center. ·     Practical Example: Deploy edge nodes that pre-process sensor data on-site, ensuring that anomalies are flagged and resolved in real time, reducing downtime and improving production efficiency.   Step 4: Establish an Adaptive Governance Model for Continuous Innovation ·     Agile Governance: Replace static governance frameworks with dynamic, risk-based models that allow for rapid testing, learning, and iteration. ·     Decentralized Control: Empower cross-functional teams to own parts of the digital ecosystem, enabling faster responses to operational challenges. ·     Example: Set up an “innovation sandbox” where teams can quickly prototype new solutions, measure performance against key KPIs, and seamlessly integrate successful pilots into the main architecture. Detailed information is available in Premium Content Newsletter. Image Source: Research Gate Transform Partner – Your Digital Transformation Consultancy

Integration Architecture, Orchestration & AI: Redefining Digital Banking As banks accelerate investments in Digital Banking, Open Banking, and fintech ecosystems, the challenge is no longer connecting applications. The real objective is orchestrating data, APIs, business processes, and AI-driven decisions across the enterprise. Modern customer journeys span Core Banking, Payments, LOS, LMS, CRM, AML, Fraud Monitoring, and Digital Channels. Success depends on an architecture that enables real-time interoperability through APIs, event-driven processing, microservices, and cloud-native platforms such as Kubernetes, Kafka, Azure API Management, and MuleSoft. The next transformation wave is being driven by Artificial Intelligence and Machine Learning. AI is no longer a standalone capability. It is becoming embedded within every business process, powering intelligent onboarding, fraud detection, credit scoring, next-best-offer recommendations, customer service automation, and predictive risk management. This requires integration architectures capable of seamlessly orchestrating AI services built on platforms such as Azure AI, Databricks, Snowflake, MLFlow, TensorFlow, PyTorch, RAG frameworks, Vector Databases, and Large Language Models (LLMs). The focus is shifting from system integration to intelligence integration, where AI insights are operationalized in real time within business workflows. Organizations that can unify APIs, events, data platforms, and AI models into a single intelligent ecosystem will gain significant advantages in customer experience, operational efficiency, risk management, and innovation velocity. The future of banking will not be defined by the number of applications deployed, but by how effectively organizations orchestrate data, AI, and business capabilities across the digital ecosystem. Applications enable services. Data enables insights. AI enables decisions. Orchestration turns them into business outcomes. #IntegrationArchitecture #EnterpriseArchitecture #ArtificialIntelligence #MachineLearning #GenerativeAI #LLM #DigitalTransformation #OpenBanking #Fintech #DigitalBanking #APIM #Microservices #EventDrivenArchitecture #CloudNative #DataArchitecture #TechnologyStrategy #EnterpriseIntegration #AITransformation #BankingInnovation #FutureOfBanking

𝗧𝗵𝗲 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝟰.𝟬 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝗪𝗮𝘀 𝗪𝗿𝗶𝘁𝘁𝗲𝗻 𝗬𝗲𝗮𝗿𝘀 𝗔𝗴𝗼. 𝗪𝗵𝘆 𝗔𝗿𝗲 𝗪𝗲 𝗦𝘁𝗶𝗹𝗹 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝘁𝗼 𝗘𝘅𝗲𝗰𝘂𝘁𝗲? Henrik von Scheel’s Industry 4.0 ecosystem map clearly outlined how smart manufacturing would evolve through three waves: 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 (𝗪𝗮𝘃𝗲 𝟭), 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 (𝗪𝗮𝘃𝗲 𝟮), 𝗮𝗻𝗱 𝗖𝗼𝗻𝘃𝗲𝗿𝗴𝗲𝗻𝗰𝗲 (𝗪𝗮𝘃𝗲 𝟯). The roadmap was never unclear. Yet many organizations remain stuck in early-stage transformation, not because they lack technology, but because execution breaks down in three common patterns: Von Scheel’s ecosystem map (below) shows why: every technology depends on integrated layers beneath it. Yet many organizations still deploy these as disconnected initiatives. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 #𝟭: 𝗧𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗪𝗮𝘃𝗲𝘀 𝗮𝘀 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗖𝗵𝗲𝗰𝗸𝗹𝗶𝘀𝘁𝘀 Look at Wave 1 (blue layer). It is not a collection of individual technologies but an integrated foundation of cybersecurity, connectivity, cloud platforms, sensing infrastructure, and enterprise data architecture. Implementing these separately does not create a scalable digital backbone. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 #𝟮: 𝗝𝘂𝗺𝗽𝗶𝗻𝗴 𝘁𝗼 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗕𝗲𝗳𝗼𝗿𝗲 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 Look at Wave 2 (orange layer). Launching AI, automation, and autonomous systems without fully operational cloud, sensing, and security foundations (blue layer) creates fragile systems — analytics without trusted data pipelines, machine learning without scalable infrastructure, and automation initiatives that cannot move beyond pilots. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 #𝟯: 𝗣𝗶𝗹𝗼𝘁𝘀 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 The map shows that sensing, cloud intelligence, automation, transactions, and marketplace platforms must function as a connected operational architecture, enabling both “Run the Operations” and “Develop the Business.” Isolated pilots rarely deliver ecosystem-scale value. 𝗪𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗪𝗼𝗿𝗸𝘀 Leaders progressing toward Wave 3(purple layer) Convergence focus on sequencing transformation deliberately: foundation integration → intelligence scaling → ecosystem convergence, where advanced technologies enable connected value chains and Consumer 4.0 experiences. The difference between stalled pilots and scaled transformation is not vision; it is the discipline to complete each wave before advancing to the next. Which wave is truly operationalized across your organization, not piloted but integrated at scale? Ref: Moving beyond the hype of Industry 4.0- Henrik Von Scheel #Industry40 #SmartManufacturing #DigitalTransformation #ManufacturingLeadership

We have been witnessing a seismic shift in how organizations transform in today’s AI-driven world.   Gone are the days of single-vendor solutions dominating the landscape.   Modern transformation demands ecosystem collaboration—coordinating multiple vendors, solutions, and players across the value chain, architecture stack, and even industries. In consulting, mastering this approach is critical to delivering client value.   Organizations now leverage diverse solutions, from cloud platforms like AWS to AI tools like Microsoft Copilot, requiring seamless integration across data, applications, and infrastructure. This complexity necessitates collaboration with vendors, partners, and clients across sectors—think healthcare providers partnering with tech firms or retailers aligning with logistics platforms. Without coordination, fragmented solutions fail to scale or deliver.   As consultants, our role is to orchestrate this ecosystem. Understand the client’s value chain, from procurement to customer delivery, and map solutions to pain points. Engage stakeholders—vendors, internal teams, and industry partners—to align goals. For example, a supply chain transformation might involve IoT vendors, AI analytics firms, and logistics providers working in sync. Facilitate clear communication, align on shared objectives, and leverage your industry knowledge to bridge gaps.   Ecosystem collaboration amplifies impact, driving efficiency and innovation. To succeed, build cross-functional expertise, and foster trust among partners. In this interconnected world, your ability to navigate and unite ecosystems will define your success and transform organizations.   Follow me for more reflections on tech strategy, AI, and consulting in a connected world.   #EcosystemThinking #DigitalTransformation #AIinConsulting #TechStrategy #FutureOfWork  

There’s an important conversation happening about what “modern” really means in data and identity. It’s easy to mistake signals like email, IP, and behavioral data for the strategy. They’re not. They’re the inputs. What matters and what’s changed materially is how those inputs are connected, governed, and activated across today’s fragmented ecosystem. A modern data and identity approach is about enabling three things: First, interoperability and federation The ability to federate both identity and data, connecting Acxiom’s Real ID with other identity frameworks while also federating the underlying data including first-party, transactional, media, and behavioral signals that power discovery, engagement, and conversion across cloud platforms, clean rooms, media ecosystems, and walled gardens without forcing everything into a single system. All of this is grounded in a privacy by design approach that ensures data is used responsibly and compliantly from the start, and anchored in a durable data and identity layer that connects individuals, households, and devices across both digital and physical environments. Second, real-time adaptability Identity that can flex across channels like retail media, social, CTV, and emerging AI-driven environments, not lag behind them. Third, measurable outcomes Not just knowing who someone is, but understanding which signals and data are actually driving discovery, engagement, and conversion across the journey. This also includes deep integration with platforms like YouTube, TikTok, Instagram, and retail media networks, as well as owned channels like email and brand websites, enabling measurement and intelligence within the environments where consumers are actually spending time. These ecosystems don’t replace identity. They increase the need for a durable, privacy-first foundation that can connect signals across them. That’s the new standard for how value is realized. From static profiles to dynamic, interoperable identity From siloed data to connected intelligence From assumptions to measurable outcomes And perhaps most importantly, this isn’t about introducing another piece of technology into an already complex ecosystem. It’s about helping enterprises realize the full value of the technology they’ve already invested in by making it work together. The future of marketing isn’t less identity. It’s better identity, built for an open, complex ecosystem. That’s what modern looks like. And it’s exactly what we’re building at Acxiom.

Are you in charge of building ecosystems for your company? If so, there are 5 dimensions that you need to manage and mature to create a high-value, sustainable network of inter-dependent partners. These 5 dimensions represent the attributes that, taken together, allow an ecosystem to emerge and thrive. If you don't nurture and mature each element Strategically, Operationally and Culturally, across your ecosystem orchestration framework, your ecosystem won't deliver sustainable value. Here are the 5 Dimensions: 1️⃣ Value - this dimension might seem obvious, but its trickier than it appears. Value Orchestration needs to happen on 4 vectors - value to the 'joint' customer, value to each ecosystem member, value to the ecosystem orchestrator, and value to the entire ecosystem. Note that the best ecosystems deliver network effects 'at the ecosystem level' so the value you orchestrate with the overall ecosystem is the magic that makes the 4-way win so powerful. 2️⃣ Alignment - this is the most difficult dimension to get right because Alignment Orchestration also has to happen on 4 vectors - internal alignment (e.g., tying the ecosystem to a platform business model), alignment with 'each' ecosystem member, alignment 'across' ecosystem members (P-2-P), and alignment between the joint customers and the ecosystem. 3️⃣ Engagement - this is the most overlooked dimension. Engagement Orchestration is where and how we 'relate' to and with each ecosystem member and the ecosystem as a whole. Engagement Orchestration covers the RACI, rules, workflows, tools, data, reporting, incentives, etc. Engagement can't happen without a comprehensive ecosystem platform (aka your ecosystem tech stack) that is designed around the challenges of ecosystem orchestration. 4️⃣ Agility - this is the least understood dimension. Like any other organism (business or natural) survival and sustainability is a function of agility - the ability to successfully adapt to changes in environment in an anti-fragile manner. A top priority for ecosystem leaders is ensuring that the ecosystem continues to adapt its value, alignment, and engagement. Agility Orchestration means, bringing in new ecosystem partners, re-setting commercial terms and rules of operation specified in Engagement above, re-aligning with members of the ecosystem as joint customers ask for new forms of value, etc. 5️⃣ Scale - this dimension is also obvious but means more than just adding more gas and building more infrastructure. Scale Orchestration is a governance job. It is the competency to look at the overall state of the other four dimensions to measure and manage maturity in a concerted fashion. In simple terms that means that the amount of value, alignment, engagement and agility must be matched & coordinated across your ecosystem journey on a Strategic, Operational and Cultural level. Scale Orchestration also helps ecosystem leaders to manage the C-Suite and the Board. #ecosystemorchestration

The connectivity industry is no longer just building networks. It is building a global digital commerce ecosystem. That shift changes everything. AI infrastructure demand, cloud expansion, enterprise transformation, data center growth, and distributed applications are accelerating faster than the industry’s ability to transact connectivity efficiently. For decades, our industry optimized around: - infrastructure - coverage - capacity - transport - manual workflows The next era will be defined by something much bigger: How intelligently ecosystems can discover, quote, order, inventory, and manage spend together. At Connectbase, we believe this future is built around: 3 Clouds 5 Pillars 2 Core Foundations 1 Vision 3 Clouds - Sellers Cloud - Buyers Cloud - Partners Cloud Together, these create the Operating System for Ecosystem Connected Commerce. A platform where providers, enterprises, channel partners, cloud platforms, infrastructure operators, and digital ecosystems can transact, automate, and grow together. 5 Strategic Pillars The lifecycle of connected commerce: - Discover - Quote - Order - Inventory - Spend This is the operating model the industry now requires. A unified lifecycle connecting market intelligence, quoting, ordering, asset visibility, supplier orchestration, and financial management across the ecosystem. 2 Core Foundations Location Truth The trusted intelligence layer for the Connected World. Understanding: - where infrastructure exists - what services are available - who can deliver - how ecosystems connect - what can be automated Federated Ecosystem Fabric A digital framework enabling companies to participate in a connected commercial ecosystem while maintaining control of their: - products - pricing - APIs - workflows - customer relationships - data The future is not centralization. The future is federation with interoperability. 1 Vision To transform how connectivity is bought and sold through Ecosystem Connected Commerce. The winners in the next decade will not simply own infrastructure. They will own: - ecosystem velocity - transaction efficiency - automation - intelligence - interoperability - trust That means: - lower quote fallout - faster order cycles - stronger supplier coordination - better inventory intelligence - improved spend visibility - more intelligent infrastructure decisions This transformation is already underway across carriers, hyperscalers, enterprises, data centers, AI infrastructure providers, and channel ecosystems. Excited to continue these conversations with leaders attending #ITW and the innovation community at #ONUG. The Connected World is becoming programmable. #Connectbase #Connectivity #Telecom #DigitalInfrastructure #AI #Cloud #Networking #Ecosystem #Automation #CPQ #DataCenters #Fiber #EnterpriseIT #Carrier #Marketplace #OSS #BSS #FutureOfNetworking