By Emilie Ruscoe ( November 15, 2024, 7:20 PM EST) — Semiconductor industry supplier ASML Holding NV has been hit with a shareholder class action alleging that it stunned investors as it significantly lowered its 2025 revenue forecast after earlier brushing off the potential impact of economic headwinds affecting its industry…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Contact center analytics is the systematic collection and analysis of data related to customer interactions. With this data, businesses can assess the efficiency of their contact center and determine the biggest levers they have to improve. At the core are analytics dashboards, which transform call detail records (CDRs) and data from other channels into clear insights about customer satisfaction, agent performance, and operational efficiency. Any decent contact center is going to have built-in analytics, but it’s up to managers to decide what metrics really matter and what the data means in context. With these online analytics tools at your fingertips, you can spot a wide range of problems before they arise and stay one step ahead of your competitors. 1 RingCentral Office Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Enterprise (5,000+ Employees), Large (1,000-4,999 Employees) Medium, Enterprise, Large Features Hosted PBX, Managed PBX, Remote User Ability, and more 1. Low self-service usage Self-service usage refers to customers using automated systems, such as Interactive Voice Response (IVR) and chatbots, to resolve issues without needing to interact with an agent. That’s the key. When callers can help themselves, it reduces call volume and frees up agents to handle more complex inquiries. SEE: Discover why agents and customers alike appreciate IVRs.  When self-service usage is dropping, you’ll see the opposite — higher call volume and overwhelmed agents. Contact center analytics can help you identify opportunities to enhance and promote available self-service options. This not only improves operational efficiency but also provides customers with quicker, more convenient solutions, enhancing satisfaction. For instance, if analytics show a high volume of routine inquiries, such as billing questions or password resets, these can be addressed through automated self-service tools like chatbots or visual IVR. SEE: Explore call center chatbot examples and visual IVR use cases.  Moreover, analytics can track how customers interact with self-service options, identifying where users drop off or abandon the process. For example, if many customers begin using a chatbot but do not complete their inquiry, this can highlight areas where the chatbot may not be providing sufficient information or a seamless experience. By using these insights, businesses can refine their self-service systems — setting up call flows, updating content, and improving usability — and encourage higher usage. This can increase customer satisfaction by offering quicker, more convenient solutions. 2. Low First-Call Resolution (FCR) Low FCR indicates that customers are calling multiple times to resolve the same issue, which leads to dissatisfaction, inefficiencies, and high call queue times — this creates stress for both agents and customers. SEE: Learn the top five causes of high call queue times and how to fix them.  Contact center analytics are a perfect tool for digging into the types of issues that commonly lead to multiple calls, such as billing questions or technical support requests. Once these recurring issues are identified, I would create targeted resources — like FAQs or specific guides — to help your customers before they even call agents. Publishing such online resources is labor intensive, but it can decrease the complexity of questions agents are forced to answer by educating callers ahead of time. But you can’t count on every caller to find and use these resources ahead of time. A consistently low FCR may indicate that agents need more training or improved access to resources for handling these types of cases. Offering specialized training to agents handling these low-FCR inquiries can boost their ability to address complex issues right away. Consider also providing agents with a useful knowledge base that can help them resolve a wider range of customer inquiries on the first try. Giving agents quick access to relevant information will reduce the need for follow-up calls by enabling faster and more accurate solutions during the initial interaction. 3. High call abandonment rates Call abandonment often happens when customers experience long wait times, leading to frustration and, ultimately, a poor customer experience. Contact center analytics can help by pinpointing specific times of day or days of the week when abandonment rates spike. For example, if analytics show a high call abandonment rate during the early afternoon, managers might adjust staffing levels to meet that demand or consider implementing a callback option to reduce customer wait times. To address high call abandonment rates, start by adjusting staffing schedules based on the peak demand times highlighted in your analytics. This ensures that enough agents are available during the busiest periods, reducing wait times and lowering the chances of customers hanging up. Additionally, consider trying some new call queue management strategies, such as enabling virtual queueing or offering a callback option, so customers aren’t forced to wait on hold indefinitely. Real-time dashboard monitoring can further help managers stay informed about current call queues and abandonment trends, allowing them to make immediate adjustments to staffing or prioritize calls as needed. 4. Low customer retention Managing customer retention is one of the most important responsibilities of a contact center. Supervisors need to be able to surface any threats to retention and resolve them quickly. Contact center analytics can improve customer loyalty by identifying issues that might drive customers away and by facilitating proactive service enhancements. Analyzing key metrics such as repeat call rates, resolution time, and escalation frequency, managers can pinpoint and address recurring issues that negatively impact customer experience. For instance, if repeat call rates are high, it may signal that customers aren’t receiving adequate solutions on the first call, which can erode loyalty over time. By analyzing interactions across various channels, you can identify where most of your customers are heading first. Choose one channel to begin with and focus your efforts on creating a supportive problem-solving process for the thorniest issues. Then, if possible, apply what you’ve learned to improve your other channels as well. 5. Low customer satisfaction It’s far easier to keep a satisfied customer than to win back an unhappy one, so fixing any gaps in quality service is essential

Microsoft has also announced the general availability of Fabric Real-Time Intelligence, which provides pro-dev and no-code tools for ingesting high-volume streaming data. Dener Motorsports has been leveraging Real-Time Intelligence to stream data from its race cars during races, giving engineers access to that data in real-time. Microsoft also announced the preview of new capabilities including Fabric events and enhancements to Eventstreams and Eventhouses. The company also announced the general availability of sustainability data solutions in Microsoft Fabric to provide a single place for environmental, social, and governance (ESG) data needs, as well as the general availability of API for GraphQL, an API for accessing data from multiple sources in Fabric with a single query API. Microsoft has also made Azure SQL DB mirroring generally available. Microsoft also previewed a number of additions to Fabric, including Copilot in Fabric for data pipelines in Fabric Data Factory, integration with Esri ArcGIS for advanced spatial analytics, and open mirroring in OneLake, which enables any application or data provider to write change data directly into a mirrored database within Fabric. source

相：在「太空商業化」論壇，理大與創星匯（香港）簽署合作備忘錄，在理大大學顧問委員會成員兼創星匯－國際顧問委員會顧問梁甜昭教授（後左），及創星匯國際理事會召集人李嘉樂教授（後右）見證下，由理大副校長（研究及創新）趙汝恒教授（前左）及創星匯總裁吳自榮先生（前右）代表簽署。  香港理工大學（理大）昨日於校園舉行「航天航空科技創新高峰會」，匯聚航天航空技術和創新領域的政商領袖、研究人員和業界人士，在各個專題分組論壇上分別聚焦深空探測、火箭和衛星技術、新太空經濟、低空經濟、初創機遇等重要議題，共同分享最新的科研成果和技術突破，探討創新航天方案，匯聚近千名全球學者和業界人士參與，超過50位講者分享他們對航天航空科技的真知灼見與研究成果。 昨舉行「航天航空科技創新高峰會」 開幕典禮上，由中央人民政府駐香港特別行政區聯絡辦公室教育科技部副部長吳程，香港特別行政區政府創新科技及工業局副局長張曼莉，理大校長滕錦光，國際宇航聯盟執行總監Christian FEICHTINGER，中國國家航天局衛星數據與應用國際合作中心綜合管理部部長李婷婷，立法會議員李浩然、邱達根、洪雯、尚海龍、黃錦輝，港區全國人大代表楊德斌，以及理大副校長（研究及創新）趙汝恒為活動揭開序幕；中國工程院院士、中國探月工程總設計師吳偉仁，以及聯合國外層空間事務廳總監Aarti HOLLA-MAINI亦通過視頻致辭祝賀峰會順利舉行。 滕錦光致歡迎辭時表示，理大致力於促進航天領域的國際交流與合作，在去年，理大成為香港首個加入國際宇航聯盟的高等教育機構，該聯盟擁有來自全球77個國家、超過500家領先企業會員；在上月，理大科研團隊也在意大利米蘭舉辦的國際宇航大會展示了7項前沿研究項目；而理大在QS世界大學排名中位列第57位，並以創新型世界一流大學為定位，「我們將繼續運用理大在科學、工程和研究方面的實力，為航天領域的發展作出更多貢獻。」 高峰會下午的5個專題分組論壇，分別以「探索企業家如何利用科研成果把握太空經濟機遇」、「香港低空經濟發展」、「工程—低軌道衛星和火箭」、「太空探索：科技與科學」及「太空商業化」為主題，促進與會者就技術創新及發展、行業趨勢及應用等範疇交流意見。 專題分組論壇上，理大與兩個業界夥伴簽署合作備忘錄：在「太空商業化」論壇，理大與創星匯（香港）簽署合作備忘錄（MOU），旨在推動太空科技的發展，並將合作創立一個「航天產業發展加速器」，為新太空經濟及相關產業培育未來人才；在「香港低空經濟發展」論壇，理大與大灣區低空經濟聯盟簽署合作備忘錄，就促進低空經濟領域的創新與實踐、推動相關學術研究和技術轉移開展合作。 LinkedIn Email Facebook Twitter WhatsApp The post 理大與創星匯(OASA)簽MOU合作推動太空科技發展 appeared first on VeriMedia. source

In our real-world case study, we needed a system that would create test data. This data would be utilized for different types of application testing. The requirements for the system stated that we need to create a test data set that introduces different types of analytic and numerical errors. Twelve different scenarios need to be tested against, and the data files need to contain or be able to contain data that will exercise those 12 tests. In addition, the system needs to create different files that mimic the data sets or files customers submit. There can be up to eight different data sets or files. Each record in each file needs to have a correlation ID or primary/foreign key value to match and link across records in the files. These correlation IDs can be kept in a text file that the system will read and assign along with the created output.   Then, the system needs to be able to create different amounts of records per file to mimic the number of transactions in the source system. The output of the system should be able to stress the end user application by producing different-sized test files. The requirement for the output is to be able to create files of 1000, 10,000, 100,000 and 1,000,000,000 records.   Lastly, the system needs to keep track of the number of records in each file, the time it takes to create the output, the time it takes to process, the number of errors created per output test file by the 12 different test types, the number of errors correctly captured by the automated tests and other business-specific metrics. Some of these data points will come from the agentic AI system and some will be generated from the automation testing system.   source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Leading figures in AI, including Anthropic’s Dario Amodei and OpenAI’s Sam Altman, suggest that “powerful AI” or even superintelligence could appear within the next two to 10 years, potentially reshaping our world. In his recent essay Machines of Loving Grace, Amodei provides a thoughtful exploration of AI’s potential, suggesting that powerful AI — what others have termed artificial general intelligence (AGI) — could be achieved as early as 2026. Meanwhile, in The Intelligence Age, Altman writes that “it is possible that we will have superintelligence in a few thousand days,” (or by 2034). If they are correct, sometime in the next two to 10 years, the world will dramatically change. As leaders in AI research and development, Amodei and Altman are at the forefront of pushing boundaries for what is possible, making their insights particularly influential as we look to the future. Amodei defines powerful AI as “smarter than a Nobel Prize winner across most relevant fields — biology, programming, math, engineering, writing…” Altman does not explicitly define superintelligence in his essay, although it is understood to be AI systems that surpass human intellectual capabilities across all domains.  Not everyone shares this optimistic timeline, although these less sanguine viewpoints have not dampened enthusiasm among tech leaders. For example, OpenAI co-founder Ilya Sutskever is now a co-founder of Safe Superintelligence (SSI), a startup dedicated to advancing AI with a safety-first approach. When announcing SSI last June, Sutskever said: “We will pursue safe superintelligence in a straight shot, with one focus, one goal and one product.” Speaking about AI advances a year ago when still at OpenAI, he noted: “It’s going to be monumental, earth-shattering. There will be a before and an after.” In his new capacity at SSI, Sutskever has already raised a billion dollars to fund company efforts. These forecasts align with Elon Musk’s estimate that AI will outperform all of humanity by 2029. Musk recently said that AI would be able to do anything any human can do within the next year or two. He added that AI would be able to do what all humans combined can do in a further three years, in 2028 or 2029. These predictions are also consistent with the long-standing view from futurist Ray Kurzweil that AGI would be achieved by 2029. Kurzweil made this prediction as far back as 1995 and wrote about this in this best-selling 2005 book, “The Singularity Is Near.”  Futurist Ray Kurzweil stands by his prediction of AGI by 2029. The imminent transformation As we are on the brink of these potential breakthroughs, we need to assess whether we are truly ready for this transformation. Ready or not, if these predictions are right, a fundamentally new world will soon arrive.  A child born today could enter kindergarten in a world transformed by AGI. Will AI caregivers be far behind? Suddenly, the futuristic vision from Kazuo Ishiguro in “Klara and the Sun” of an android artificial friend for those children when they reach their teenage years does not seem so farfetched. The prospect of AI companions and caregivers suggests a world with profound ethical and societal shifts, one that might challenge our existing frameworks. Beyond companions and caregivers, the implications of these technologies are unprecedented in human history, offering both revolutionary promise and existential risk. The potential upsides that could come from powerful AI are profound. Beyond robotic advances this could include developing cures for cancer and depression to finally achieving fusion energy. Some see this coming epoch as an era of abundance with people having new opportunities for creativity and connection. However, the plausible downsides are equally momentous, from vast unemployment and income inequality to runaway autonomous weapons.  In the near term, MIT Sloan principal research scientist Andrew McAfee sees AI as enhancing rather than replacing human jobs. On a recent Pivot podcast, he argued that AI provides “an army of clerks, colleagues and coaches” available on demand, even as it sometimes takes on “big chunks” of jobs.  But this measured view of AI’s impact may have an end date. Elon Musk said that in the longer term, “probably none of us will have a job.” This stark contrast highlights a crucial point: Whatever seems true about AI’s capabilities and impacts in 2024 may be radically different in the AGI world that could be just several years away. Tempering expectations: Balancing optimism with reality Despite these ambitious forecasts, not everyone agrees that powerful AI is on the near horizon or that its effects will be so straightforward. Deep learning skeptic Gary Marcus has been warning for some time that the current AI technologies are not capable of AGI, arguing that the technology lacks the needed deep reasoning skills. He famously took aim at Musk’s recent prediction of AI soon being smarter than any human and offered $1 million to prove him wrong. Linus Torvalds, creator and lead developer of the Linux operating system, said recently that he thought AI would change the world but currently is “90% marketing and 10% reality.” He suggested that for now, AI may be more hype than substance. Perhaps lending credence to Torvald’s assertion is a new paper from OpenAI that shows their leading frontier large language models (LLM) including GPT-4o and o1 struggling to answer simple questions for which there are factual answers. The paper describes a new “SimpleQA” benchmark “to measure the factuality of language models.” The best performer is o1-preview, but it produced incorrect answers to half of the questions.  Performance of frontier LLMs on new SimpleQA benchmark from OpenAI. Source: Introducing SimpleQA. Looking ahead: Readiness for the AI era Optimistic predictions about the potential of AI contrast with the technology’s present state as shown in benchmarks like SimpleQA. These limitations suggest that while the field is progressing quickly, some significant breakthroughs are needed to achieve true AGI.  Nevertheless, those closest to the developing AI technology foresee rapid advancement. On a

Data Determines Adaptive Manufacturing Destiny Last week’s announcement by automotive parts supplier Schaeffler of plans to cut 4,700 European manufacturing jobs was just the latest in a string of similar news pointing to a growing crisis within the European manufacturing sector. Rising costs, falling sales, and increasing global competition mean that Europe’s manufacturers must adapt to technology budgets that are, in real terms, hardly growing. My colleagues Bernhard Schaffrik, Paul Miller, and I have been wondering: Where are the opportunities to put limited funds to best use? Forrester’s automation predictions for 2025 discuss how citizen developers capitalizing on domain expertise will deliver 30% of generative AI-infused automation apps and a major pivot to governance of data and AI together. Forrester readers are curious about the implications for their traditional enterprise applications like CRM (customer relationship management), ERP (enterprise resource planning), or PLM (product lifecycle management). To be sure, enterprise software vendors now recognize the immense value of their data assets, but manufacturers are anxious that a volatile outlook threatens their ambitions to reclaim data value using the right mix of enterprise proprietary and pooled partnership language models. But they can still boost their adaptive posture even with limited budgets if they wrap their applications in an “adaptivity” layer and if they pursue new routes to innovation. Cocoon your applications in a data “adaptivity” framework. Now is not the time to rip out core enterprise systems that are still (mostly) fit for purpose. But focused investment around the periphery will deliver disproportionate adaptive benefit. You cannot make your ERP or PLM systems more adaptive while they run in production. But you can become more adaptive if you: Encapsulate your legacy apps. In earlier research, we described how technology architecture and delivery leaders can leverage enterprise application governance to improve their agility. But you can also make application sources, sinks, and surroundings more adaptive — for example, by adopting open API architectures and by preparing your autonomous enterprise roadmap. Wrap legacy in automation fabric. You can start by working out how to provide to developers, process admins, and managers access to the full process orchestration lifecycle to use, monitor, and improve it. Accommodate real-time operational process insights. The beauty of real-time process intelligence is that it enables root-cause detection and “decisioning” while processes run so you can act much more quickly than with classic process intelligence. Pursue new routes to innovation by leveraging partners. Tech organizations can become more adaptive by selecting a suitable pace for technology renovation and by focusing on new skills and data management. But you can’t do this alone. You will need a co-innovation partner. Start by complementing familiar cost-cutting exercises with a program of rapid collaborative co-innovation with your own suppliers. A co-innovation partner brings assets, alliances, and solutions and can help you transform by orchestrating the value of your internal and external ecosystems. We will work on these topics further but would also love to hear your thoughts on how best to invest limited funds to adapt to new challenges. If you are a Forrester client, feel free to schedule a guidance session through [email protected]. source

Redtail CRM fast facts Starting price: $39 per user per month Key features: Workflow management Reporting and analytics Calendar syncing and integrations Seminar and call campaigns Mobile app Redtail CRM is a cloud-based customer relationship management tool from Redtail Technology. Redtail CRM supports two-way sync for contacts and activities between Redtail and Microsoft Office 365 (web-based), hosted Microsoft Exchange Online, and Google. With features tailored for financial services, Redtail CRM can help automate workflows and processes, store data and client information, and track opportunities in real time. While Redtail CRM does have core CRM functionalities, its pricing structure is costly compared to other, more popular, solutions and doesn’t offer additional niche industry specializations. Below I cover standout features offered by Redtail CRM plus real user feedback and alternatives to help guide you in choosing a CRM. 1 Zoho CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 2 Pipedrive CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 3 HubSpot CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Small (50-249 Employees) Micro, Medium, Large, Small Redtail CRM pricing Launch: $39 per user, per month when billed annually or $45 per user when billed monthly. Supports up to five users. Growth: $59 per user, per month when billed annually or $65 per user when billed monthly. Supports unlimited users. Enterprise: Contact for a quote. A minimum license commitment is required. Redtail CRM key features Automated workflows The best CRM software solutions offer automations that can streamline processes with trigger-based actions. With Redtail CRM you can create custom automated workflows to track task ownership. These workflows track repetitive tasks and can minimize mistakes by standardizing processes so that no client-related actions fall through the cracks. This type of streamlined process is helpful for client onboarding, lead nurturing, and so much more. Redtail CRM workflow setup and edit page. Image: Redtail CRM Calendar Redtail CRM’s native calendar tool is a hub for individual users that can be customized in many different ways, including color coding, notifications, reminders, and activities. This is particularly useful for businesses where internal schedule visibility is important. Reps, managers, and admins can all view public calendars and monitor tasks through them. Redtail CRM also integrates and syncs calendar items with Office 365 and Google Calendar through the Retriever Cloud tool. Sample Redtail CRM calendar. Image: Redtail CRM Reporting dashboards Redtail CRM generates standard reports that you can access for relevant day-to-day operational data. Examples of the filtered reports Redtail CRM can produce are accounts, activity, contacts, documents, emails, fiduciary, notes, permissions, opportunities, or transactions. All client data is recorded in a secure place that is easy for users to track and filter to see precisely the information they need. Sample activities by contact Redtail CRM report. Image: Redtail CRM Mobile app Redtail CRM’s free mobile app allows users to access critical client data from anywhere. This helps financial professionals, agents, sales reps, and administrators reference client profiles for contact information, daily tasks, and calendar schedules. The mobile app is available for both Android and iOS phones. However, I do want to note that not all desktop functionality is available through the mobile app. Example Redtail CRM mobile app interface. Image: Redtail CRM Redtail CRM pros 30-day free trial. Extensive note taking and record keeping features. Users praise Redtail CRM’s support teams and response time. Redtail CRM cons Limited integrations compared to other popular CRM solutions. Real users call out outdated UI. Users report occasional bugs. Alternatives to Redtail CRM Redtail CRM HubSpot Pipedrive monday CRM Starting paid plan $39 per user, per month $15 per user, per month $14 per user, per month $12 per user, per month Forever free plan No Yes No Limited Reporting and analytics Medium Advanced Advanced Advanced Mobile app Yes Yes Yes Yes AI-powered tools No Advanced Medium Medium HubSpot HubSpot is a popular CRM solution that also offers marketing, customer service, and operations products. HubSpot’s free CRM is popular since it provides basic core functionality as well as some advanced CRM features. Unlike Redtail CRM, HubSpot also offers AI-powered features that are designed for improved productivity. Some standout AI features include the AI email writer, web builder assistant, AI chatbots, and even reporting assistants. Check out our HubSpot review to learn more. Pipedrive Pipedrive is an operational CRM that organizations can use to build out their entire business workflow to track clients and deals. Pipedrive doesn’t offer a free-for-life plan of its software, but its paid tiers are affordable for businesses of any size. Like Redtail CRM, Pipedrive can be adapted to serve financial services, banking, and accounting businesses, along with a multitude of other industries. Want to know more about Pipedrive? Head over to our Pipedrive review. monday CRM monday CRM is a highly customizable sales CRM platform. While monday CRM’s forever free plan is only available to approved student or nonprofit users, its paid tiers are still affordable and great for small businesses. Compared to Redtail CRM, monday CRM has more customization options when it comes to automations and collaboration between users. These custom formulas and automations in monday CRM can assign leads to reps, set reminders, and move deal statuses along. Read our review of monday CRM for more information. Methodology I used an in-house TechRepublic rubric to score and review Redtail CRM. Our rubric consists of outlined criteria around the most important factors when evaluating generalized CRM solutions. I referenced Redtail CRM’s own online resources in addition to real user feedback, scores, and reviews. Redtail CRM was reviewed based on the following criteria: Cost: Weighted 25% of the total score. Core features: Weighted 25% of the total score. Customizations: Weighted 15% of

By Andrew Karpan ( November 19, 2024, 10:29 PM EST) — HP has agreed to join a patent pool for coding technology developed by companies like Dolby Laboratories, Mitsubishi and Philips, months after alleging that the group was engaging in “a money grab” to coerce it to accept “unfair and discriminatory licensing terms.”… Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

The Dynamic Host Configuration Protocol (DHCP) automatically assigns unique IP addresses to your devices, along with other necessary details like subnet masks and default gateway information. This process allows devices to communicate within the network and access the internet. Automating this process, rather than manually configuring each device, saves a lot of time and reduces errors. DHCP is a free and reliable way to configure devices on IP networks, but it isn’t without its drawbacks and security vulnerabilities. I’ll walk you through the advantages of it along with the tradeoffs, to help you understand when it’s apt to use. 1 RingCentral Office Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Enterprise (5,000+ Employees), Large (1,000-4,999 Employees) Medium, Enterprise, Large Features Hosted PBX, Managed PBX, Remote User Ability, and more Essential DHCP terms To understand DHCP, there are a few other terms and technologies you will need to know: IP address: An IP address is a unique identifier for each device on a network. DHCP can dynamically assign addresses from a pool of available numbers, letting devices communicate within the network and on the internet. Subnet mask: This is a number that defines a range of IP addresses available within a network. It helps you divide networks into subnetworks for more efficient management and security. DHCP server: This is a network server that assigns IP addresses, default gateways, and other network parameters to client devices. It relies on the DHCP to respond to broadcast queries by clients. DHCP client: This is any device that requests and obtains an IP address and other parameters automatically from a DHCP server. Clients can include computers, smartphones, and other network-enabled devices. Lease duration: Lease duration is the length of time an IP address is assigned to a device. After the lease expires, the device must request a new IP address or renew the existing one. DNS server: A DNS server translates domain names into IP addresses so that network requests can be routed to the correct servers. Default gateway: The default gateway is a device that serves as an access point or IP router to pass traffic from a local network to other networks or the internet. How DHCP works Let’s walk through the process step by step, breaking it down into five discrete stages that ensure seamless IP address allocation and network connectivity. Knowing the fundamentals of computer networking will be really helpful for understanding this process. DHCP discover The DHCP process begins when a client device connects to the network and needs to obtain network configuration parameters. It broadcasts a “DHCP discover” message to the network. This message is a request for configuration information. Since the client device doesn’t yet have an IP address, this broadcast is sent to a special address that all DHCP servers listen to. DHCP offer After receiving the discovery message, a server on the network responds to the client, or device, with a “DHCP offer” message. This message contains critical configuration data, like an available IP address from the server’s pool, subnet mask, and lease duration. If there are multiple DHCP servers on the network, the client may receive several offers, each with different configuration options. DHCP request The client will evaluate all the offers it receives, then select one and respond to the network with a “DHCP request” message. This message indicates the client’s acceptance of one of the offers and informs all DHCP servers on the network of the decision. At this point, other servers that made offers will retract them and reserve those IP addresses for other devices. DHCP acknowledgement The server that made the selected offer responds to the client with a “DHCP acknowledgement” packet. This finalizes the lease of the IP address to the client and may include additional configuration information, such as the DNS server address and default gateway. The client configures its network interface with this information, establishing a connection to the network. Lease duration and renewal The process is essentially complete at this point, but the IP address lease is only valid for a specific duration, known as the lease time. This means that before the lease expires, the client must either renew its existing lease or request a new one. If the client shuts down or leaves the network before the lease expires, it sends a “DHCP Release” message, relinquishing its IP address and making it available for other devices. When it makes sense to use DHCP Since DHCP can automate an otherwise tiresome manual process, we generally recommend it for most business and network environments. Here’s the main reasons why I’ve found DHCP a good choice. Dynamic network environments In settings where devices frequently join and leave the network, such as businesses with multiple users or public Wi-Fi networks, DHCP is ideal. It dynamically allocates IP addresses, making it easier to manage a changing roster of devices. Doing this process manually would be much less efficient. If you want to support a Bring Your Own Device network, for example, I’d say DHCP is a must — though you will have to stay on top of BYOD security. Reduced administrative workload Since DHCP automates the process of assigning IP addresses, it frees up administrators to spend time on other things. This significantly reduces the workload for your network administrators and minimizes the chance of errors that can occur with manual IP assignments. Scalability and flexibility DHCP is highly scalable, so whether your network is small or expanding rapidly, it can adapt. It’ll continue to manage IP addresses efficiently as the number of connected devices on your network grows or shrinks. When to avoid using DHCP There are scenarios where assigning a static IP address makes sense. For example, servers, network printers, and other devices that need to maintain a consistent network address for easy accessibility are better suited to static IP addresses. DHCP can also present security risks or become a single point of failure in a network if