Systems Thinking and Data Science: a partnership or a competition? | 7wData

• Read original article here

Information is pretty thin stuff, unless mixed with experience. – Clarence Day (1874–1935), American essayist.

Why do organizations get stuck with their data? It is such a fundamental question. Often, this problem can be due to the Organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective.

systems thinking is an approach to problem-solving which invests in understanding the system within which a problem or challenge is situated rather than targeting a specific component of the problem. How can systems thinking and data science solve digital transformation problems?

Information can be hard to find. Understandably, organizations focus on the data and the technology since data retrieval is often viewed as a data problem. Data tends to run in silos throughout the Organization. The questions usually focus on who can access the data and who can make the decision. Organizations often consider the ‘right’ time to access the data. As an aside, businesses often talk about ‘real-time’ data but often mean up-to-date data, which could be weekly or even monthly data. There is usually a focus on the correct data, which may be a matter of ensuring which one of the many different data stores is selected that has the data as it may be duplicated across various sources and analytical systems. Actionable insight is a buzzword, but it is unclear what it means or how businesses can work to achieve the insight. Systems thinking helps organizations consider the proper context of the data. On its own, the data may be comprehensible by the person at the end of this extensive process.

Systems thinking helps to build consumable data products, and it helps to make the data meaningful and relevant. To be very customer-focused, the organization must continually reflect on their strengths and the customer they serve. For example, for some organizations, no-code is an excellent way to show success early in the journey towards solving digital transformation challenges. No-code and Automation solutions can help to accelerate the organization on its journey. There is a particular interest in the growth of Robotic Process Automation (RPA) which uses AI and metaphorical robots to deliver repetitive tasks and make digital transformation a reality. The RPA market may grow to $25 billion in 2025 according to Forrester, and it has the promise of supporting digital transformation through streamlining digital transformation ( Reference ).

For example, FPT Software , a global IT services and solutions provider, has a product in the automation and RPA space called akaBot , which has gained recognition on Gartner Peer Insights and other global review platforms. In the industry, there has been intensive growth in the need for low-code and no-code in terms of democratizing access within companies to go from simply using data towards a complete digital transformation strategy. Therefore, interacting with systems using minimal technical skills is very beneficial.

How is it possible to enable data-driven decisions in a systems thinking approach?

A crucial aspect of digital transformation is to enable data-driven decisions. The digital part of digital transformation is to arrange a digital foundation where the right person can access trustworthy, correct information at the right time in the proper context. The foundation should be well structured and have essential data quality measures, monitoring and good data engineering practices.

Systems thinking helps the organization frame the problems in a way that provides actionable insights by considering the overall design, not just the data on its own.