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The new Short Circuit Software version is now available. TORONTO, ON - ARCAD Inc. is helping create a safer working environment for repair service people and electrical maintenance workers who service electrical systems by providing on-line and PC based software for short circuit and arc flash hazard analysis. The arc flash software will help a business meet OSHA, NFPA 70D, CSA Z462 regulations and code requirements. SCA V1.0 (Short-Circuit-Analytic) software performs available fault currents calculations in three phase electric power systems. The program will take into consideration electrical parameters of the power supply as well as the power distribution system including cables, bus ducts, transformers, utility, motors, generators, etc. The software will automatically convert the entire system into a unique unit from which the short circuit current at each point is calculated. Because the process is simple and efficient, it will save a business money and time. Short Circuit Analytic Capabilities are as follows: Computes contributions from generators and motors Prints out multi-page single line diagrams Calculates available 3-phase short circuit currents within your power distribution system Saves calculation results and equipment data Compliments ARCAD software for arc flash hazard analysis and labeling Should you encounter any problem installing or running SCA V1.0, contact http://www.arcadvisor.com and they will assist you in identifying and resolving the problem.

Lean has been helping companies streamline their production, eliminate waste, and generally improve the way things are done for many years. Initially, the concepts behind lean were primarily used only in companies and facilities that were directly involved with physical product creation, such as manufacturing plants, factory floors and things of this nature. However, over time the lean methodologies have been adapted and implemented in almost every other type of business, ranging from health care to information technology, and many more. When done properly, lean can help improve virtually any work environment to help eliminate waste, improve communication, and to help ensure that the products or services being developed are indeed something customers will be interested in. For instance, when working in an information technology environment, it is important to be able to understand how lean strategies can be implemented, and why they are so important. The following are some of the most significant reasons why lean IT strategies should be taken seriously by any company that uses technology in their business (which is almost all of them!). Lean Promotes Ownership One of the things about lean strategies in an IT environment is that virtually every task completed is owned by an individual. Even if a person does not do all the work for a particular project, he or she will be directly responsible for overseeing it. This creates a sense of ownership, which can help in a variety of ways. It will give other teams a single point of contact for obtaining updates, providing feedback, or requesting changes. This will also allow the owner of a specific project to drive the progress directly, rather than having to rely on large committees or other types of groups to receive pertinent information. It is important to note that just because one person owns a process or project does not mean that he or she can simply dictate things to other groups. Instead, that person is there to

Are you AI-First? By editor Posted October 13, 2018 In Artificial Intelligence, Digital Strategy, Technology & Design 0 An AI-First company is an enterprise that has transformed to believe and understand the incredible and disruptive potential of Artificial Intelligence. Such an enterprise not only sees the value but can see the destructive impact of being left behind. An AI-First Company understands that it might not know all the answers but realizes that it needs to seek out a path forward with AI or risk being marginalized. Key Characteristics of an AI-First Company A-First companies might not be any different from their previous form but think and act differently. Here are some key characteristics of such companies. Approach to Problems and Planning An AI-First company evolves its approach to problems. AI-First companies realize that determining the existence of a problem and selecting the most consequential problems is a function of data and analytics. An AI-First company invests in building predictive mechanisms that can signal current or upcoming problems including the severity and priority of these problems. Building these predictive mechanisms becomes the first step in determining how and when to prepare for problems or upcoming issues. In addition, these companies leverage news and information that is generated inside and outside the enterprise as it is generated and ensure that their employees and customers have access to the insights embedded in the news and information. Approach to Products and Product Development An AI-First company understands how a prediction or classification could help them deliver a better solution to a problem faced by their customers and how their existing products can be adapted or new products created that change behavior based on the predictions and classifications. Enterprises that understand the power of AI ensure that data scientists come part of the core product ideation and development team with a heavy infl

A lot has been said about agility and the need for enterprises looking to innovate and disrupt to build agility. Agility, at the same time, also gets confused with the process of scrum. Small and large teams get enamored with the idea of scrum and mistake the process with the state of being agile. This is often more detrimental to the enterprise and can often create more process and not enough real agility. What is Agility Agility is the efficiency with which an enterprise executes and delivers on its objectives and goals. Agility is the ability to react to changes in goals, feedback from customers and shifts in strategy. Agility, from the outside, looks like a predictable stream of value delivered by the enterprise that matches and exceeds the needs of the customer. Organizational agility requires agility at multiple levels within the enterprise to drive the insights that can channel and align the efforts of the entire organization by leveraging data and information to make quick and informed decisions. Business Agility Business and customer-facing employees need to achieve "Business Agility". This is the ability of these employees to react to business critical in real time if needed and have access to the latest information at any decision point. Business Agility enables users to reduce the latency or lag between a need in the market or of the customers and when they are able to service the need. Decision Agility Analysts and data scientists creating the insights to drive decisions require "Decision Agility" i.e the ability to easily discover, leverage and use data for analytics and insights through any and multiple tools and channels. Analysts and data scientists need to produce insights that reduce the time and effort required to convert data into information and insights that are required to drive key decisions and actions. Development Agility Application developers and data engineers need the ability to easily generate, collect, access and deli

Digital Transformation is a huge topic now. Most software vendors have adapted their products to include the Digital Transformation message. Transforming into a digital company is no longer a choice and it is clear that the companies that transform faster can develop a competitive advantage that will serve them for years while the companies that do not will slowly fade into irrelevance. Digital Transformation is the change in an enterprise that makes it acquire and deploy the best in class technology assets and systematically removing analog or manual touch points, handoffs, processes and decision making. It is the ability of the enterprise to understand, assimilate and leverage the latest technology trends such as cloud, mobile, APIs, AI, Blockchain, ChatBots, Analytics, IoT etc.

Enterprises have to constantly decide, at every step in their digital journey, should they build or buy. This question often is posed as a critical, do or die decision and the answer varies on a case by case basis. Building can be expensive, take longer but offers future proofing and more dependability whereas buying offers a faster time to market, less risk and accountability forced through contractual terms. However, a key point often overlooked is the cost of integration. Integration can be required at multiple levels. Vendor Applications Vendor applications typically require a two-way connection between the enterprise systems and the vendor application. The application requires incoming data and information from somewhere in the enterprise technology stack and an output stream of information back into the enterprise at one or more points in the stack or workflow. Vendor Platforms Vendor provided platforms typically have similar integration requirements as Vendor applications requiring an incoming data & information connection and an outgoing information connection into the enterprise process, workflow, platform or product. Application-To-Application Application to Application integrations where an application needs to be connected to another application to either provide data or signals to enable the downstream application to create value can be seemingly deceptive. Application-To-Application integration costs can grow at O(n^2) as potentially, worst case, each application could be connected with every other application. Enterprise Stack Fragmentation The problem of integration is exacerbated by the fragmentation of the enterprise at the organization level. This problem is also known as "Shadow IT" is driven by superficially differing needs of multiple lines of businesses in an enterprise. Shadow IT typically leads to multiple instances of similar technology stacks that cause data, compute and information to be silo'd. Stack fragmentation and its

One of the biggest hurdles to Digital Transformation and Digital Innovation is the organization's inertia and tendency to optimize for self-preservation. Self-preservation can exist in the enterprise at the individual, team, divisional or the organizational level and can have a devastating impact on the organization's ability to innovate and grow. Self-preservation is not a new phenomenon however, it is more deadly for an enterprise now than ever. This is because the speed of technology change has increased geometrically. In the past, self-preservation would automatically get corrected as the technology was generally learned and adopted slowly with enough time for the enterprise to become aware of the change and implement it. However, the rate of technology change has magnified tremendously and the enterprises no longer have the luxury to take their time with the change. Inaction risks getting left behind and other competitors who leverage and change faster stand to capture the largest market shares and customer mind share. Self preservation is the tendency of the enterprise to ignore, undermine or postpone the adoption and integration of new technology in the enterprise to avoid a change in the status quo across technology, products, services and most importantly, day to day operations and organizational structure. Self-preservation can lead to what is termed as "politics" in an org, it can stifle innovation and innovative individuals & teams and it can favor business driver stagnation over risk taking. 5 Signs of Self-Preservation The following are signs of self-preservation Highlighting the Journey of Innovation as Failure Adversarial teams and individuals within an enterprise who are interested in self-preservation often go out of their way to highlight the tough, risky journey of true innovation as a failure citing the cost and the time being taken to address the real problems in a truly innovative manner. While the individuals and teams trying to

Modern, RESTful APIs are not considered standard, table stakes and expected out of any new project, effort, application, system, service or product. It has become so normal to talk about developer interfaces, developer adoption, application development and innovation in the same breath as APIs that a distinct effort to build APIs for a new product or service seems out of place and abnormal. APIs are the defacto standard of app development. So where do we go from here? We believe that APIs are about to enter the second growth spurt. APIs will evolve from not just interfaces and integration enablers into the rockets that propel enterprises towards innovation and market dominance. Here are three key trajectories that will lead the next API evolution and revolution. Innovation - Starts, and Ends with APIs All modern technologies such as Artificial Intelligence, Machine Learning, ChatBots, Analytics, BlockChain etc. begin and end their stories with APIs. APIs are what enables the communication between front-end user interfaces and the backend technology services. All new machine learning capabilities offered out of the big four tech companies have seen the light of day through APIs. Intent & Sentiment extraction, Topics, Categories, Summarization, Image Recognition, Entity Extraction etc. are all capabilities powered by Machine Learning, Natural Language Processing that is ultimately being delivered as APIs to application developers. Similarly, ChatBots are typically designed to get the user entered text, use an intent API to determine intent and then use a service API to respond to the user conversationally or with a service. Clouds - Multi-Cloud, Hybrid Cloud As the big three cloud providers grow their market share and attempt to attract attention, increasingly, enterprises need to think about how they minimize their risk by building in the flexibility to switch their cloud provider if and when they need. In addition, hybrid architectures or a cloud migration

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