Analytics Operating Eco (OE) System
What is the Eco System?
As per the National Geographic Society, an ecosystem represents a geographical region wherein plants, animals, and other organisms, alongside weather and landscapes, collaborate harmoniously to create a vibrant hub of life [1]. Ecosystems are ubiquitous in our environment, manifesting in diverse domains such as business operations, IT operations, analytics, and beyond. In these ecosystems, all the elements collaborate synergistically to create bubbles aligned with their respective objectives.
Operating ecosystems are crucial for modern businesses. Operating ecosystems provide a framework that enables businesses to effectively integrate and coordinate various components, processes, and stakeholders within their operational environment. These ecosystems facilitate seamless collaboration, efficient resource allocation, and streamlined workflows, ultimately enhancing the overall productivity and competitiveness of modern businesses. Operating ecosystems also enable businesses to adapt to evolving technologies, market dynamics, and customer needs, allowing them to stay agile and responsive in a rapidly changing business landscape.
CEOs are being challenged to transform their organizations to adapt to a much changed — and continually changing — business context. In response, a growing number of CEOs are embracing ecosystem business models — and with good reason. A study of more than 800 business leaders leveraging at least one ecosystem business model has revealed that ecosystems make up on average 13.7% of their total annual revenues, drive 12.9% in cost reduction and generate 13.3% in incremental earnings. — Greg Sarafin, EY Global Alliance and Ecosystem Leader
Some view the rise of ecosystems as an opportunity for creating powerful new competitive advantages. — Deloitte
In a business ecosystem, companies co-evolve capabilities around a new innovation: They work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the next round of innovations. — James Moore, Harvard Business Review (1993) [2]
For this discussion, our focus will be on the analytics operating ecosystem.
What are an Analytics Operating Eco (OE) System?
An analytics ecosystem comprising a symbiosis of data, applications, platforms, talent, partnerships, and third-party service providers lets organizations be more agile and adapt to changing demands rather than feel locked into legacy investments, talent pools, and processes. — Deloitte in Wall Street Journal
In simple terms, an Analytics ecosystem can be defined as a comprehensive system that encompasses the entire analytical process, including front-end and back-end components. These components comprise dashboards, analytics tools, and data processing and storing units such as data pipelines, data warehouses, data lakes, and databases, designed to handle various types of structured and unstructured data from diverse data sources. The ecosystem operates in a cohesive manner by combining automated and manual processing methods to effectively fulfill predetermined objectives. Furthermore, it exhibits both robustness and flexibility, enabling it to adapt to evolving requirements, technologies, and user dynamics.
As analytics becomes a C-suite imperative, many CIOs are exploring ways to establish or tap into ecosystems to extract and exploit insights from growing volumes of data. — Deloitte
According to a survey of 450 executives conducted by Deloitte Analytics, companies that are significantly more likely to invest in building in-house analytics capabilities include those where data science is a priority. Figure 1 and figure 2 shows schematic data analytics ecosystem.
As illustrated in Figure 3, the accompanying diagram showcases an analytical ecosystem where loosely coupled data undergo processing and pre-processing stages. Within this system, the data dynamically moves and communicates with each other. Leveraging this ecosystem, analysts can employ machine learning algorithms to process diverse types of data from the core, enabling them to discover new meanings or patterns that build upon existing ones.
References:
1. https://education.nationalgeographic.org/resource/ecosystem/
2. James F. Moore, “Predators and prey: A new ecology of competition,” Harvard Business Review, May 1993, https://hbr.org/1993/05/predators-and-prey-a-new-ecology-of-competition/ar/1, accessed March 17, 2015. View in article
3. https://aite-novarica.com/report/current-state-assessment-global-analytics-ecosystem
4. https://www.teradata.com/Blogs/Governing-Data-Across-the-Analytical-Ecosystem
About the Author:
Dr. Ray Islam (Mohammad R Islam) is a Data Scientist (AI and ML) and Advisory Specialist Leader at Deloitte, USA. He holds a PhD in Engineering from the University of Maryland, College Park, MD, USA and has worked with major companies like Lockheed Martin and Raytheon, serving clients such as NASA and the US Airforce. Ray also has a MASc in Engineering from Canada, a MSc in International Marketing, and an MBA from, UK. He is also the Editor-in-Chief of the upcoming peer-reviewed International Research Journal of Ethics for AI (INTJEAI), and his research interests include generative AI, augmented reality, XAI, and ethics in AI.
