According to McKinsey surveys of global Supply Chain leaders (May 15-May 22, 2020, n=60), 85% struggled with insufficient digital technologies in the supply chain. One of the key digital technologies is business intelligence (BI) and analytics. According to Tableau, the projected return on investment of BI in a 3-year period is 127%. Clients and colleagues are seeing the importance of adopting BI and predictive analytics to proactively manage the company and make critical decisions. Are you on a roadmap to adopting BI?
A recent Google-commissioned study by IDG showed that the role of data analytics and intelligent solutions will be important to helping businesses separate from their competition. Insights from data will be crucial in carving out winners in the post pandemic era. BI was gaining in popularity prior to the pandemic, but it skyrocketed during COVID as companies realized they had to get insights to get ahead of the curve. For example, they needed to figure out the answers to questions such as how customers’ buying behaviors are changing and what types of new products and services will best serve their most profitable customers.
For example, a client had unprecedented demand coming down the pike and wanted to better forecast sales so that they could prepare for the surge. The issue is that they had multiple systems and data sources that didn’t connect to one another. Sales used one source, and Operations used a different source. Although their business is custom and engineered-to-order, we found predictable patterns in their historical sales, and we discovered that their quotes could be data mined to capture key information that would be instrumental in preparing their operations and extended supply chain.
However, to extract the information and connect the data to be able to gain insights to make directionally correct decisions, a significant deep dive into data was required. The client worked for months to delve into business processes to understand how to cleanse the data, connect the data, fill in data gaps and create a repeatable and sustainable process to manage the data. Of course, although centered on data; the key to success was working with the people to understand what was relevant and how to account for key conditions and build them into the data model. Instead of waiting for perfection, the client started to utilize the directionally correct information to order long lead-time materials, to plan capacity and to evaluate offloading opportunities to get a jump on critical decisions.
In this situation, the client started with a simple BI solution as time was of the essence. They created dashboards and visualizations to better align Sales with Operations and demand with supply as part of their Sales, Inventory and Operations Planning (SIOP) process. While building the data model, the client started to document the data maps and data integrity process disciplines required to ensure sustainability. This resulted in a BI roadmap to create a business analytics and intelligence platform to grow sales and scale the business successfully.
BI was a priority prior to the pandemic; in the post-pandemic, it is has transitioned from a priority to critical and essential to survival. According to 451 Research, the ability of business leaders to quickly use data from operational applications to make strategic decisions and deliver on strategic outcomes will rapidly be seen not just as a potential competitive differentiator, but also as a fundamental requirement and strategic imperative. Yet BI alone isn’t enough. According to Gartner, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI). Predictive analytics will become the norm. If you don’t yet have a roadmap, jump in the fast lane, and make sure you are in control of the car.
As originally published in Brushware Magazine on September-October 2021