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AI Agents and Open APIs

AI Agents and Open APIs

How AI Agents and Open APIs Are Unlocking New Rebundling Opportunities While much of the 2023-24 excitement surrounding AI has focused on the capabilities of foundational models, the true potential of AI lies in reconfiguring value creation across vertical value chains, not just generating average marketing content. The Vertical AI Opportunity Most AI hype has centered on horizontal B2C applications, but the real transformative power of AI is in vertical B2B industries. This article delves into the opportunities within vertical AI and explores how companies can excel in this emerging space. Short-Term and Long-Term Strategies in Vertical AI In the short term, many vertical AI players focus on developing proprietary, fine-tuned models and user experiences to gain a competitive advantage. These niche models, trained on domain-specific data, often outperform larger foundational models in latency, accuracy, and cost. As models become more fine-tuned, changes in user experience (UX) must integrate these benefits into daily workflows, creating a flywheel effect. Vertical AI companies tend to operate as full-stack providers, integrating interfaces, proprietary models, and proprietary data. This level of integration enhances their defensibility because owning the user interface allows them to continually collect and refine data, improving the model. While this approach is effective in the short term, vertical AI players must consider the broader ecosystem to ensure long-term success. The Shift from Vertical to Horizontal Though vertical AI solutions may dominate in specific niches, long-term success requires moving beyond isolated verticals. Users ultimately prefer unified experiences that minimize switching between multiple platforms. To stay competitive in the long run, vertical AI players will need to evolve into horizontal solutions that integrate across broader ecosystems. Vertical Strategies and AI-Driven Rebundling Looking at the success of vertical SaaS over the last decade provides insight into the future of vertical AI. Companies like Square, Toast, and ServiceTitan have grown by first gaining adoption in a focused use case, then rapidly expanding by rebundling adjacent capabilities. This “rebundling” process—consolidating multiple unbundled capabilities into a comprehensive, customer-centric offering—helps vertical players establish themselves as the hub. The same principle applies to vertical AI, where the end game involves going vertical to later expand horizontally. AI’s Role in Rebundling The key to long-term competitive advantage in vertical AI lies not just in addressing a single pain point but in using AI agents to rebundle workflows. AI agents serve as a new hub for rebundling, enabling vertical AI players to integrate and coordinate diverse workflows across their solutions. Rebundling Workflows with AI Business workflows are often fragmented, spread across siloed software systems. Managers currently bundle these workflows together to meet business goals by coordinating across silos. But with advances in technology, B2B workflows are being transformed by increasing interoperability and the rise of AI agents. The Rebundling Power of AI Agents Unlike traditional software that automates specific tasks, AI agents focus on achieving broader goals. This enables them to take over the goal-seeking functions traditionally managed by humans, effectively unbundling goals from specific roles and establishing a new locus for rebundling. Vertical AI Players: Winners and Losers The effectiveness of vertical AI players will depend on the sophistication of their AI agents and the level of interoperability with third-party resources. Industries that offer high interoperability and sophisticated AI agents present the most significant opportunities for value creation. The End Game: From Vertical to Horizontal Ultimately, the goal for vertical AI players is to leverage their vertical advantage to develop a horizontal hub position. By using AI agents to rebundle workflows and integrate adjacent capabilities, vertical AI companies can transition from niche providers to central players in the broader ecosystem. This path—going vertical first to then expand horizontally—will define the winners in the AI-driven future of business transformation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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UX Principles for AI in Healthcare

Agentic Era of UX

The Agentic Era of UX The future of digital experience has arrived, but it’s fragmenting into countless micro-applications. The missing piece in AI user experience? The experience itself. It’s been almost a year and a half since generative AI burst onto the scene, heralded as transformative. But what have we actually seen in terms of user experience? Many companies released AI-powered summaries or search features, claimed them as revolutionary, and received applause—until the applause faded. The so-called “next era” of tech hasn’t yet delivered on its promise. We were given “the most profound technology since fire,” yet many implementations feel like candles that barely flicker. Many UX designers continue advocating for AI to solve genuine user needs. Technology must serve users, not just exist for its own sake. The core issue now is broader: AI has often been treated as a quick fix rather than a true UX transformation. Where user experience traditionally supports the entire journey, AI is being wedged into small, isolated tasks, losing the holistic perspective. For most companies, AI feels like a string of individual “use cases” rather than a full, cohesive UX meal. Many consulting firms push companies to prioritize use cases in terms of complexity and value, often resulting in chatbots that address a handful of user needs. There are notable exceptions, though. For example, Loom went beyond simple AI features to enhance the user’s entire workflow, supporting end-to-end functionality for video recording, transcription, editing, and even task management. Welcome to the Agentic Era of AI We’re now on the verge of the “agentic” era of AI. Industry leaders are abuzz with the potential of AI agents. OpenAI’s Sam Altman calls agents AI’s “killer function,” while other leaders predict this future is within reach, possibly within 3–18 months. The agentic promise is profound: AI agents, or “agentic workflows,” break down complex tasks into manageable steps, helping users complete intricate projects with autonomy. As Ezra Klein describes, imagine telling an AI to plan your child’s dragon-themed birthday party in Brooklyn, and the agent handles everything from booking to ordering the cake—transforming a casual AI prompt into tangible results. Today’s general-purpose models can’t handle this level of complexity independently. But agentic workflows make this possible by chaining AI actions, allowing systems to execute tasks step-by-step. A Vision for Agentic UX Design’s role in this era is to bring a vision of agentic UX to life. In traditional digital experiences, we build systems that assist users along their journey, but we still expect users to navigate the journey themselves. With an agentic UX, an AI partner supports the user at every step. This vision means UX will be defined by three pillars: Early examples are emerging, like Adobe’s Gen Studio, Intercom’s Copilot, and Dovetail’s Magic Experience, each taking steps toward a future where AI provides ongoing, meaningful support to users. An agentic UX doesn’t necessarily need to label itself “agent-powered.” Dovetail, for instance, offers a suite of “Magic” features where the AI partner plays a supporting role, from summarizing transcripts to highlighting key points. Over time, as AI evolves, these agents will assume greater responsibility in user journeys, shifting from supportive to proactive. Strategically Reinvent for the Agentic Era Adapting to the agentic era presents an opportunity—and a risk for those who ignore it. Currently, organizations are focused on laying the infrastructure for “AI readiness.” While that’s essential, it can obscure the longer-term vision of what’s possible. Until business leaders fully grasp the agentic UX’s potential, it’s up to design to step into a strategic role and make this vision vivid, relatable, and exciting. This requires more than launching a quick proof of concept; it demands a reimagining of digital experience. Here’s a recommended approach: It’s been a challenging year for design, with layoffs and value debates. But with the agentic era approaching, the strategic potential for UX is immense. Now is the time to rally, to guide organizations into a new era of digital experience where users are truly supported every step of the way. 4ox Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Rise of AI Agents

Rise of AI Agents

The Rise of AI Agents in Enterprise Automation Rise of AI Agents… It sound a bit like a B grade satire movie. But its not satire or scary. AI Agents, powered by large language models (LLMs), represent a groundbreaking paradigm shift in software. Unlike previous automation technologies, AI agents can reason, collaborate, and act in ways similar to human behavior. This new era of Enterprise AI Agents marks a significant evolution from traditional Robotic Process Automation (RPA), expanding the scope from simple task-level automation to enhancing complex knowledge work. RPA stands for Robotic Process Automation, which uses software bots to automate digital tasks and streamline processes. RPA can help reduce costs and improve efficiency. There are three main types of RPA: attended, unattended, and hybrid From RPA to AI Agents: A Strategic Shift A decade after the emergence of RPA, the enterprise landscape is poised for another transformation with intelligent AI agents. These agents are not merely incremental improvements but a revolutionary technology requiring new skills and tools. They transcend the limitations of RPA, moving beyond rule-based automation to dynamic, context-aware operations. Transitioning from RPA to AI agents is a strategic initiative necessitating executive sponsorship. This shift also offers automation leaders and Centers of Excellence (CoEs) the chance to reimagine their roles as strategic enablers within the enterprise. The Evolution of Enterprise Automation Automating Tasks: RPA RPA gained popularity in the mid-2010s through companies like UiPath, leveraging record-and-playback style UI automation. Despite early skepticism about its fragility, RPA established itself as a cornerstone of low-code business applications. Automating Processes: Intelligent Automation (IA) IA extends beyond RPA by incorporating techniques like API automation and OCR. It signals a shift from point-and-click automation to process automation, often blending coding with low-code tools. However, IA remains rule-based, suitable for structured processes. Automating Work: Intelligent AI Agents AI agents introduce a new agentic planning and execution workflow. They natively understand unstructured data and processes, making them ideal for tasks described in natural language rather than rigid rules. AI agents can self-correct and seek human feedback, enhancing resilience compared to pre-programmed bots. Strategic Applications of AI Agents AI agents expand the possibilities of enterprise automation. While RPA remains effective for repetitive, structured tasks, AI agents bring new capabilities to areas requiring flexible reasoning and decision-making. Tactical Automation AI agents can augment existing RPA workflows, addressing tasks that precede or follow RPA routines. This initial integration helps expand automation’s reach within the enterprise. Standard Decisions in Standard Contexts For work involving standard decisions within platforms like ServiceNow or Salesforce, AI and automation solutions from these vendors are beneficial. These platforms continue to innovate, enhancing their data and process capabilities. Strategic Core Business Workflows The most significant impact of AI agents lies in complex, custom-context tasks central to the enterprise’s operations. Here, built-for-purpose enterprise AI agents can drive substantial value, allowing human workers to focus on more strategic activities. Implementing AI Agents: Steps to Get Started The Urgency of Adopting AI Agents The rapid pace of AI advancements necessitates immediate action. Traditional strategies that plan for future technology must pivot to embrace AI today. Forward-looking companies are already reaping significant benefits from AI, and delaying adaptation risks losing competitive advantage. AI agents are not just the next step in automation; they are a transformative technology redefining enterprise workflows. By acting now, businesses can harness AI agents’ full potential, driving innovation and maintaining relevance in an ever-evolving market. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Impact of AI Agents Across Key Sectors in 2024

Impact of AI Agents Across Key Sectors in 2024

Sophisticated autonomous digital entities are already transforming our lives, industries, and the way we engage with technology. What will be the Impact of AI Agents Across Key Sectors in 2024? While much attention has been given to Generative AI (Gen AI), the next major leap forward comes from AI Agents. This emerging technology is set to revolutionize how we work and interact with the world. How AI Agents Will Shape Daily Life AI Agents: An OverviewAI Agents, also called digital assistants or AI-driven entities, are advanced systems designed to perform tasks and provide services autonomously. They use machine learning, natural language processing, and other AI technologies to understand user needs, solve problems, and complete tasks without direct human intervention. The Impact of AI Agents Across Key Sectors in 2024 Personalization and AssistanceAI Agents are increasingly embedded in our personal and professional routines. By learning our preferences, habits, and needs, they offer personalized recommendations, such as curating music playlists, suggesting films, or creating custom workout plans. Their ability to deliver tailored assistance makes everyday life more seamless and enjoyable. Healthcare AdvancementsIn healthcare, AI Agents are making a significant impact. They can analyze medical records, provide diagnostic insights, and assist with treatment planning. Multi-modal agents even process medical imaging to aid in diagnoses, marking a groundbreaking advancement for both healthcare professionals and patients. Efficiency in BusinessAI Agents are transforming business operations by improving customer service through 24/7 automated chatbots and streamlining processes in supply chain management, human resources, and data analysis. These systems help optimize operations and support more informed decision-making. Education and LearningIn education, AI Agents offer personalized learning experiences tailored to each student’s needs, helping them learn at their own pace. Teachers also benefit, as AI Agents provide insights to customize instruction and track student progress. Enhanced CybersecurityAs cybersecurity threats evolve, AI Agents play a key role in identifying and mitigating risks. They detect anomalies in real-time, helping organizations protect their data and systems from breaches and attacks. Environmental ImpactAI Agents are contributing to sustainability by optimizing energy consumption in buildings, improving waste management, and monitoring environmental changes. Their role in addressing climate change is increasingly critical. Research and InnovationIn fields like drug discovery and climate modeling, AI Agents accelerate research by processing and analyzing vast amounts of data. Their involvement speeds up discoveries and innovation across multiple domains. Impact of AI Agents Across Key Sectors in 2024 In 2024, AI Agents have become much more than just digital assistants; they are driving transformative change across industries and daily life. Their ability to understand, adapt, and respond to human needs makes technology more efficient, personalized, and accessible. However, as AI Agents continue to evolve, it is crucial to consider ethical concerns and promote responsible use. With mindful integration, AI Agents hold the promise of a more connected, sustainable, and innovative future. If you are ready to explore AI Agents in your business, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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ai voice agent

Voice Agents

A voice agent, also known as a voice AI agent, is a system that uses artificial intelligence (AI) to understand, interpret, and respond to human speech, enabling natural, conversational interactions for tasks like answering questions, providing information, or completing actions. Functionality:Voice agents use technologies like natural language processing (NLP) and machine learning to engage in conversations, answer queries, and perform tasks, much like a customer service representative would. Voice AI agents represent a transformative leap in how humans interact with technology. These sophisticated systems combine speech recognition, natural language understanding, and human-like speech synthesis to enable fluid, real-time conversations. Unlike traditional AI tools, voice AI agents can autonomously reason, make decisions, and execute tasks—revolutionizing industries from customer service to healthcare. What Are Voice AI Agents? Voice AI agents are autonomous software systems that:✔ Understand spoken language (speech recognition).✔ Reason like humans (powered by large language models).✔ Respond with natural-sounding speech (text-to-speech synthesis).✔ Perform tasks with minimal human intervention (agentic workflows). They excel in 24/7 interactive services, such as customer support, personal assistants, and accessibility tools, offering human-like interactions at scale. How Voice AI Agents Work Voice AI agents integrate multiple AI disciplines: 1. Speech Recognition (ASR) 2. Natural Language Understanding (NLU) 3. Decision-Making & Task Execution 4. Speech Synthesis (TTS) Key Advancements Over Traditional Assistants Feature Virtual Assistants (Siri, Alexa) Modern Voice AI Agents Reasoning Limited, scripted responses Dynamic, LLM-powered decisions Task Complexity Single-step commands Multi-step workflows Adaptability Static knowledge Learns from interactions Personalization Basic user profiles Context-aware responses Architecture of a Voice AI Agent A typical client-server setup includes: Client-Side Server-Side Communication Protocols: Challenges & Limitations Despite rapid progress, voice AI agents still face hurdles: 🔹 Accents & Dialects – Performance drops with underrepresented languages.🔹 Speech Disorders – Struggles with stuttering or atypical speech patterns.🔹 Continuous Learning – Requires frequent retraining to stay current.🔹 Privacy Concerns – Handling sensitive voice data securely. How to Build a Voice AI Agent Real-World Applications ✅ Customer Service – Automated call centers (Vapi, Skit.ai).✅ Healthcare – Voice assistants for patients & diagnostics.✅ Education – Personalized tutoring & language learning.✅ Accessibility – Assistive tech for visually impaired (Be My AI).✅ Smart Homes – Voice-controlled IoT devices (Alexa, Google Home). The Future of Voice AI Agents As LLMs, speech synthesis, and agentic frameworks improve, voice AI will: However, ethical AI development remains critical to address biases, privacy, and security. Final Thoughts Voice AI agents are reshaping human-computer interaction, moving beyond rigid chatbots to true conversational partners. Businesses adopting this tech early will gain a competitive edge—while those lagging risk obsolescence. The era of talking machines is here. Are you ready? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Prompt Builder Einstein

Prompt Builder in Salesforce Einstein: Revolutionizing AI-Powered Automation Salesforce Einstein has introduced a groundbreaking feature called Prompt Builder, designed to simplify and enhance the way businesses leverage generative AI for automation and productivity. Prompt Builder empowers users to create, customize, and deploy AI-driven prompts without needing deep technical expertise. This tool is part of Salesforce’s broader vision to make AI accessible and actionable for everyone. Let’s explore what Prompt Builder is, how it works, and why it’s a game-changer for businesses. What is Prompt Builder? Prompt Builder is a no-code/low-code tool within Salesforce Einstein that allows users to create and manage AI prompts for generative AI models. These prompts can be used to automate tasks, generate content, and provide intelligent responses across Salesforce applications. With Prompt Builder, businesses can harness the power of AI to improve efficiency, enhance customer experiences, and drive innovation. Key Features of Prompt Builder How Does Prompt Builder Work? Use Cases for Prompt Builder 1. Customer Service 2. Sales and Marketing 3. Content Creation 4. Internal Productivity Benefits of Prompt Builder How to Get Started with Prompt Builder The Future of Prompt Builder As generative AI continues to evolve, Prompt Builder is expected to become even more powerful. Future developments may include: Conclusion Salesforce Einstein’s Prompt Builder is a transformative tool that democratizes the use of generative AI for businesses. By enabling users to create, customize, and deploy AI-driven prompts with ease, Prompt Builder empowers organizations to automate tasks, enhance customer experiences, and drive innovation. Whether you’re in sales, marketing, customer service, or any other field, Prompt Builder can help you unlock the full potential of AI. Start exploring Prompt Builder today and revolutionize the way you work with AI! Content updated November 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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2024 AI and Machine Learning Trends

2024 AI and Machine Learning Trends

In 2023, the AI landscape experienced transformative changes following the debut of ChatGPT in November 2022, a landmark event for artificial intelligence. 2024 AI and Machine Learning Trends ahead, AI is set to dramatically alter global business practices and drive significant advancements across various sectors. Organizations are shifting their focus from experimental initiatives to real-time applications, reflecting a more mature understanding of AI’s capabilities while still being intrigued by generative AI technologies. Key AI and Machine Learning Trends for 2024 Here are the top trends shaping the AI and machine learning landscape for 2024: 1. Agentic AIAgentic AI is evolving from reactive to proactive systems. Unlike traditional AI that primarily responds to user inputs, these advanced AI agents demonstrate autonomy, proactivity, and the ability to independently set and pursue goals. 2. Open-Source AIOpen-source AI is democratizing access to sophisticated AI models and tools by offering free, publicly accessible alternatives to proprietary solutions. This trend has seen significant growth, with notable competitors like Mistral AI’s Mixtral models and Meta’s Llama 2 making strides in 2023. 3. Multimodal AIMultimodal AI integrates various types of inputs—such as text, images, and audio—mimicking human sensory capabilities. Models like GPT-4 from OpenAI showcase this ability, enhancing applications in fields like healthcare by improving diagnostic precision. 4. Customized Enterprise Generative AI ModelsThere is a rising interest in bespoke generative AI models tailored to specific business needs. While broad tools like ChatGPT remain widely used, niche-specific models are increasingly popular for their efficiency in addressing specialized requirements. 5. Retrieval-Augmented Generation (RAG)RAG combines text generation with information retrieval to boost the accuracy and relevance of AI-generated content. By reducing model size and leveraging external data sources, RAG is well-suited for business applications that require up-to-date factual information. 6. Shadow AIShadow AI, which refers to user-friendly AI tools used without formal IT approval, is gaining traction among employees seeking quick solutions or exploring new technologies. While it fosters innovation, it also raises concerns about data privacy and security. Looking Ahead to 2024 These trends highlight AI and machine learning’s expanding role across industries in 2024. Organizations must adapt to these advancements to remain competitive, balancing innovation with strong governance frameworks to ensure security and compliance. Staying informed about these developments will be crucial for leveraging AI’s transformative potential in the coming year. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce analytics insurance

Business Analysis and Project Management Acronyms

Here is a helpful glossary of business analysis and project management acronyms you may encounter when discussing business analysis and project management. Acronym Meaning Definition BPMN Business Process Management Notation “A flow chart method that models the steps of a planned business process from end to end. Its purpose is to model ways to improve efficiency, account for new circumstances or gain competitive advantage.” (source) CCMP Certified Change Management Professional CCMP (Certified Change Management Professional) is aimed at change management professionals, which includes Salesforce Consultants, Business Analysts, Project Managers, Salesforce Admins, and other similar roles. CIO Chief Information Officer The member of the C-suite who takes responsibility for IT systems, especially an organization’s data. DoD Definition of Done “Definition of done” relates to one of the requirements that the user story must adhere to for the Development Team to call it complete. This is following the acceptance criteria being met. FRS Functional Requirements Specification The project documentation where the business requirements are defined from an end user or business perspective. It will specify the expected outcomes. INVEST Independent, Negotiable, Valuable, Estimable, Small, Testable Use the INVEST checklist to assess the quality of a user story. Have you met all the criteria? JTBD Jobs To Be Done JTBD is a methodology for determining what problems users are trying to solve, focused on understanding users in terms of functional, emotional and social needs. JTBD is a core concept in the Strategy Designer Certification. PM Project Manager Project Managers oversee Salesforce projects end-to-end on a variety of Salesforce ‘clouds’ and levels of complexity. Their priority is to ensure the project is successful – delivered on time, and within budget.The responsibilities of a Salesforce Project Manager range from typical organizational tasks and technical acumen, through to work that requires emotional intelligence, tact, solid communication, and many other ‘soft’ skills. PMO Project Management Officers Project Management Officers work with the organization’s leaders to fulfill the same responsibilities as project managers. In addition, PMOs will carry out pre-project planning, such as risk analysis and opportunity analysis. PMP Project Management Professional Project Management Professional (PMP) equips project managers with up-to-date trends and practices with project management tools, processes, and methods. PPM Portfolio Project Management A category of technology that enables project managers to outline, track, and collaborate on a set of ongoing projects. PSA Professional Services Automation A category of technology that combines project management, time tracking, invoicing, resource planning, and more. PSM Professional Scrum Master Scrum helps people and teams deliver value incrementally in a collaborative manner. The entry level PSM-1 is aimed at understanding Scrum best practice when working on Agile projects. You will find this very useful on Salesforce projects. RACI Responsible, Accountable, Consulted, Informed A matrix that delineates who is responsible for what in the context of the business analysis effort. Responsible (person who performs an activity or does the work), Accountable (person who is ultimately accountable for the outcome), Consulted (person who needs to provide feedback or contribute to the activity), Informed (person who needs to know of a decision or action). RFI Request for Information Requests For Information (RFIs) and Requests for Proposal (RFPs) are a useful approach for teams evaluating Salesforce tooling – they allow you to quickly source information on features, workflows, and pricing from a range of vendors. RFP Request for Purchase Requests For Information (RFIs) and Requests for Proposal (RFPs) are a useful approach for teams evaluating Salesforce tooling – they allow you to quickly source information on features, workflows, and pricing from a range of vendors. SIPOC Supplier, Inputs, Process, Outputs, and Customers SIPOC is a type of process map that shows the key elements of a process such as Suppliers, Inputs, Process, Outputs, and Customers. SoW Statement of Work The SoW is a legal document that outlines the work to be carried out (the scope), what’s excluded (out of scope), the client-side responsibilities, and the project schedule and fees. SRS System Requirements Specification The project documentation that details how the complete system should function and enumerates hardware, software, and functional and behavioral requirements of the system. UML Unified Modeling Language Diagramming that uses “a common visual language in the complex world of software development that would also be understandable for business users and anyone who wants to understand a system”. (source) UPN Universal Process Notation A simpler and more engaging diagramming notation that has been designed to be easily understood by all the stakeholders and viewed online. As a hierarchical diagram, you are able to drill down to give more detail (with no limit to the number of levels you can go down). business analysis and project management acronyms Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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