“An algorithm is like a recipe.” – Muhammad Waseem
Mathematics, and its myriad forms and applications, finds an expanding footprint in the modern world. Algorithms, essentially complex expressions of mathematical formulae, have begun to dominate a wide range of processes in domains as varied as electronic commerce, software engineering, climate modeling, the pharmaceutical industry, stock trading, marketing and manufacturing, hydrocarbon exploration, scientific research, and others. The typical algorithm finds explanation as “a well-defined procedure that allows a computer to solve a problem. A particular problem can find resolution through more than one algorithm. Optimization is the process of finding the most efficient algorithm for a given task.” In light of such assertions, various initiatives of mapping computer algorithms have come to the fore, often driven by factors that include entrepreneurship, market forces, the profit motive, commercial competition, the imperatives of modern data science, the drive to attain billion dollar valuations, and more. In such scenarios, analytical frameworks such as flowcharts can ably assist efforts designed for mapping computer algorithms in a variety of contemporary contexts.
Operators of e-commerce services can develop techniques of mapping computer algorithms through flowchart diagrams. The objectives of such initiatives could include the quest to raise understanding of behaviors emanating from target customers, analyzing user behavior on shopping apps and websites, harvesting meaning from data generated by e-commerce apps and websites, expanding the idea of customer segmentation in digital commerce, refining the ability to predict customer choices and preferences, and predicting (in real time) the intent of different types of digital visitors and customers. A variety of algorithms and their operating segments, when positioned inside an appropriate flowchart, allow analysts and e-commerce operators to extract meaning that can populate the various contexts outlined above. Therefore, flowcharts act as a bridge between abstract mathematical formulae and commercial intelligence that spurs the strategies, actions, and tactics endorsed by modern e-commerce operators.
Digital recommendation engines (and their operating mechanics) can find granular expression when software architects set about mapping computer algorithms inside flowcharts. Such an illustration includes stages that depict the sampling of sets of typical user profiles, apply sophisticated filters, analyze the requirements of an extended user profile, suggest certain predictions in terms of user assumptions, survey the top items of merchandise preferred by users, find and impose content-based filters, and generate a set of personal recommendations suitable for each user profile. The mechanics of such engines, when reviewed and refined inside multiple flowcharts, spotlight the value of data and actual findings harvested by e-commerce operators. Industry comment indicates the economic value generated by sophisticated recommendation engines could exceed 1 billion US$ for top e-commerce operators. The flowchart plays a central role in the construction and operation of such digital engines, thereby validating the use of such illustrations in modern commerce.
Technology-driven algorithms can help business operators to manage product inventory efficiently. Such an assertion gains relevance when we consider opinion that states algorithms represent “one of the most important tools to manage scale of operations, speed of execution, and complexity of human nature.” Therefore, in this context any effort at mapping computer algorithms inside flowcharts must survey quantities of product inside an inventory, unit prices of product, the total dollar value of the inventory, numbers of product supplied to customers each day, schedules for replenishing units of product, incoming demand for particular lines of product, the delivery schedules operating in various warehouses, and others.. The resulting flowchart-based illustration can assist business operators and inventory analysts to adjust and control inventory operations, while effecting efficient connections in supply chain operations.
Interesting outcomes emerge when designers fashion flowcharts inside the traditional image of a geometric square. Such an initiative can help the mission of mapping computer algorithms by positing multiple math values inside smaller squares designed into the primary shape. Such a stance enables designers to simplify logical operations and reduce complexities in the design of electronic circuits, for instance. However, the illustration continues to be animated by traditional symbols of flowcharts, such as arrows, stages, and sub-stages. Designers pursuing the objective of visual clarity may elect to fashion layers of information inside multiple illustrations and subsequently assemble the final illustration. This technique of mapping computer algorithms empowers designers to build high levels of complexity inside diagrams, review and revise individual sections of diagrams, and embark on voyages of incremental design complexity.
Commercial airline operators, keen to enhance profitability could practice dynamic pricing of passenger tickets and services by mapping computer algorithms inside flowcharts. Industry observers note, “Dynamic pricing is a strategy for offering personalized fares to individual consumers based on their flight history and other factors.” Algorithms that power key aspects of such strategy must include time-based pricing models, best practices for peak pricing of airfares, segmented pricing for less frequented passenger routes, a consideration of customer profiles, real time examinations of prices offered by competing services, and others. These factors can help designers embrace and implement the key logic of such pricing mechanisms, and develop competent strategies that boost income levels for participating airline operators. In addition, the act of mapping computer algorithms must include algorithmic components that constantly sample operational data generated by airline operations. This allows pricing strategy to stay current and relevant to the stated objective of boosting profitability.
New technologies such as machine learning offer “the ability to accurately perform new, unseen tasks, build on known properties learned from training or historic data, and based on prediction.” In line with this, software architects could devise intelligent techniques for mapping computer algorithms using inter-linked illustrations such as flowcharts. Such initiatives, when fully developed, could assist medical professionals to assess a patient’s risk for various health conditions based on numerous “blood pressure readings, laboratory test results, race, gender, family health history, socio-economic status, and clinical trial data.” These elements, when positioned inside flowcharts, allow designers to utilize various machine-learning systems to serve humankind and ensure greater accuracy in standard healthcare practices. In addition, the algorithm can assist healthcare providers to offer patients sophisticated services that trigger better outcomes, reduce the costs of healthcare, and result in higher levels of satisfaction among patients and their families.
These lines of analysis and examination help readers to appreciate the use of flowchart diagrams in acts of mapping computer algorithms. Each algorithm, when individually compiled inside a flowchart, must remain subject to tests for metrics such as operational efficiency. This stance allows designers to create validated development projects that make the optimal use of resources. However, analysts and designers must work to examine and expand the relevant use cases, and connect these to applications in the real world, prior to authoring an algorithm. In addition, the process of creation must negotiate various acts of visual exploration wherein, designers work to ideate the flow of actions that must be driven by the completed algorithm. A variety of external factors must feature inside flowcharts, because these can enrich the construction process of algorithms. Subsequently, designers may elect to verify each algorithm in light of accepted best practices, remove any bugs from the creation, and test extensively in real world conditions. The outcomes could encourage architects and designers to develop new editions of algorithms, ones that prove superbly efficient at delivering the proverbial goods to clients and customers.
