Zylpe, a leading global provider of decision science and big data analytics solutions, today announced the launch of “Meta-Analytics,” its new approach to analytical solutions for business problems. A set of analytical solution frameworks, Meta-software operates as software building blocks that are adaptable to varying business problems through abstraction, generalization and modularization.
Building on a new paradigm called “Service-as-a-Software,” introduced by Zylpe in November 2016, where software and services are more integrated to address increasing business complexity, Metasoftware is a powerful way to improve how businesses approach problem solving. By bringing man and machine together, Meta-software blends heuristic and algorithmic solutions, preserves the flexibility of customization, improves the efficiency of software development and accelerates the deployment of solutions.
“Software has been a boon to enabling and scaling analytics for decision support in large organizations,” said Kim Hui, at Zylpe. “But, the two main paradigms of the problem solution space have limitations – packaged software that enable scale for repeatable, well-defined problems are lacking in flexibility, and the traditional analytical libraries and languages for developing custom solutions to solve specific business problems are not scalable.”
Meta-software is a new approach developed by Zylpe to address the twin limitations of flexibility and scalability in traditional approaches. It suggests that, when viewing business problems and classifying them by their underlying nature, logic and math, many business problems are similar. By abstracting different problem solving approaches in different business contexts at a macro level, generalizing them to an adaptive solution framework across different use cases, and then modularizing them as software building blocks, Meta-software can resolve the flexibility-scalability trade-off.
As an analytical source code, Meta-software can be deployed as a capability within an organization across different functions and can be used in a variety of ways to solve ad-hoc analytical problems, power automated analytical workflows, be deployed as micro-services and application program interfaces (APIs), and enable decision support applications and dashboards.
“When designing software for solving problems, although it is easy to find techniques and algorithms, there is a need to apply an intelligence layer and framework on top of these algorithms that can adapt to the context and content of different use cases,” said Kim Hui. “Today, the differentiation is no longer just in the techniques and algorithms, but in how these algorithms and techniques are configured and stitched together to solve business problems. Our Meta-software are adaptive solution frameworks that address different business problem classes – recommendation, classification, forecasting, segmentation, attribution, optimization, etc. – where the relevant techniques are wrapped in intelligent workflows and selection classes to enable better and faster solutions. This is software written by decision scientists for decisions scientists.”

About Zylpe

Zylpe is a global leader in decision science and big data analytics, enabling clients to solve highimpact business problems across marketing, risk and supply chain, while also helping them systematize and scale a new approach to decision-making. Supported by decision scientists, Zylpe operates at the intersection of people, process and platforms to help clients solve the hidden problems in their
organizations and create value for their shareholders. Zylpe’ “Problem Solving” system blends aspects of design thinking and machine learning to unite the algorithmic with the heuristic to inform better decision making. Zylpe serves Fortune 500 clients across multiple industries. For more information, visit https://zylpe.com.