Optimize: Enable Higher Efficiency of Your Product, Processes, and Systems

Optimization can be applied to infrastructure, products, internal systems, and processes. The main task and goal are to improve efficiency and productivity.

Delivery optimization allows you to improve the performance of the product (application or platform), reduce the time to market. Optimizing processes and systems increases employee productivity and motivation. This can be achieved by applying innovative strategies and technologies.

Computools’s engineers are able to audit your systems and products to identify bottlenecks and develop a step-by-step guide to overcome them.

Here’s a Quick Rundown of How It Works

Starting from the first stages of the project, each team member works on the product’s improvement. Ideas are filtered and processed based on business analysis and technical management, after that they are offered to the client.

Continuous improvement of processes on the project helps to increase development speed, improve quality, and minimize costs. The Business Analyst’s team researches new trends and technical solutions in the domain for suggestions on improvements to the product in accordance with the market changes.

Product components are also improved by technical experts. Optimizing also involves continuous monitoring of the system’s state. It helps prevent crises and collect data for analysis.

Data collection for analytics consists of the receiving of bug reports from real users; the usage of vendors’ analytical systems, like google analytics; the usage of internal Computools’s solutions for data collection in the industry; the receiving of logs; the receiving of dynamic data from databases; the receiving of users’ feedback, application of domain-specific methods.

Primary processing and data visualization include the development of tools for data analysis within the admin panel; logs analysis; users’ feedback analysis; usage of domain-specific methods.

Then the team proceeds to the creation of hypotheses based on Big Data: a building of classical mathematical models; the building of heuristic models; analysis of data using AI; reviews analysis; making hypotheses; development of requirements for the hypothesis’s implementation; prototypes development; usage of domain-specific methods.

The next step is hypothesis testing. Engineers organize, conduct, and study the results of A/B testing, conduct beta testing, and work with user’s feedback following the three-stage plan: analysis, verification, implementation. The cycle ends with the full implementation of successful hypotheses.

Computools’s solutions will help your company’s processes and organizational network to become more efficient, functional, and responsive.

Feel like your products, processes or systems require optimization? Contact a company’s expert by emailing at info@computools.com or through the form below to find out what optimization strategy will be the most beneficial for your business.