When trying to implement informed business solutions, what you see is all there is (WYSIATI), which can result in being “data-nearsighted.” For this reason, it is crucial to have a comprehensive data strategy in order to make better business decisions and implement efficient business solutions that use internal, external, real-time and historical data.
Companies collect, store and manage (or rather, mismanage) data to develop decision making information. They rely on that collected data to make informed decisions to enhance efficiency and increase revenue. However, simply collecting data is not enough. What story is the data is telling? What opportunity does it present?
Pulling data through the process of collection to consumption is a serious undertaking. Because data collection platforms are not inherently connected and do not share formats, it is time-consuming and expensive to collect information from siloed databases. Consequently, insights are not based on real-time data, so by the time you get your hands on a report, you're likely considering insights based on old data, generated days or even weeks ago. This effect is the groundhog or pigeon approach to business analytics.
Monolithic applications have caused businesses to pursue a groundhog or a pigeon approach to data collection and analytics. These monoliths are either large and cumbersome or discrete and unconnected.
In business analytics, a groundhog is often large and cumbersome -- so big and slow that insights are either too late or so large in scope that they are rendered unactionable.
In the early stages of business development, monolithic applications present a unified option for an application that is initially easy to implement and manage. Notably, most of today’s prominent and successful applications started with a monolithic architecture. Although there are certain circumstances in business development that are well-suited for a monolithic application, as a company grows, it is also likely to outgrow what the groundhog provides.
The pigeon approach to business analytics relies on isolated information and batch processing methods to produce near-sighted reports. It is discrete and unconnected -- myopic even.
This approach to business analytics is as outdated and inefficient as sending information via a messenger pigeon. At best, the pigeon analytic approach can be used to provide cursory recommendations and finite insights. If your business has the need to connect data and insights, then the pigeon approach is not for you.
Benefits And Drawbacks Of A Monolithic Architecture
Simplicity is the key feature of monoliths that offer easy deployment and a unified package-code base. It can be a simple and singular approach to developing a business analytics insight. The ease of access and uniformity can be especially appealing during the early stages of business development. However, these monoliths are often broken down and replaced with the style of a more polylithic solution known as microservice applications.
Foxes are clever, and those who use the fox approach have a savvy understanding of the "why" in business analytics. Foxes understand the use case and the opportunity that the data addresses, and they know how to synergize operational marketing and social data into something greater.
In contrast to the groundhog and pigeon approaches, the fox approach uses speedy microservice applications. The applications are based on an innovative polylithic solution and insight style that render a multitude of relevant and actionable insights.
A microservice application is a discrete purpose-built application that integrates a business' data-collection platforms and delivers analytics-ready data via a website or portal. A microapp takes this a step further by using machine learning to deliver data-driven insights to users to accelerate and enrich decision making with artificial intelligence, machine learning, analytics, automation and external data.
Microapps move and adapt independently to collect data, which is then prepared for consumption. My experience across multiple industries has been that data automation, machine learning and intelligent decision support has made the sizeable difference in realizing opportunities framed by business analytics, ranging from right-sizing inventories to maximize service and minimize inventory to improving payables processing to reducing duplicate payments.
Microapps provide point solutions rather than monolithic features, which are less efficient and accessible; they provision analytics at the point-of-need. A significant benefit of a microservice application is that it is inherently easy to scale.
Microservices are inherently complex applications. Many parts make for many opportunities for gears to grind -- or worse, not integrate at all. Implementing a microservice application requires attention to detail.
In a microapps hub, multiple analytic activities integrate seamlessly (wherein the gears are brought together in a “clockworks” solution) with timed and shared data, insights, scenarios and options. This is, in a sense, the data-savvy fox who generates predictable revenue, increases efficiency and strengthens security year after year. The fox knows the whole is greater than the sum of its parts. Each unique and genius microapp can be connected via a hub, producing novel solutions where the whole is always greater than the sum of its parts.
History teaches us that it is essential to know where you came from to know where you are going. In The Wealth of Nations, economist and philosopher Adam Smith conceptualized growth economics by emphasizing that growth is reliant on the increasing division of labor and specialization of the labor force. This concept of deconstructing jobs into multiple, smaller parts resonates in the microservice applications’ approach to business analytics.
The pigeon and the groundhog played important roles in the evolution of business analytics and continue to offer a simplistic approach. While these monolithic architectures are suitable for noncomplex applications, the microservices architecture of the fox approach is a good option for more complex applications that require scalability. A fox in today's business analytics world uses microapps and a microapps hub to render relevant, speedy and actionable insights in order to accelerate innovative and efficient business solutions.
This blog post was originally posted in June 2019 as an article at Forbes.com where the author, Aaron Burciaga, is a Forbes Technology Council Member. Aaron is presently the CTO at Anatlytics2Go, leading the company's development and global operations of analytics technologies and capabilities.