Business Intelligence (BI) is not a new term; indeed, it can be found in writings that are over 150 years old. There are numerous definitions for Business Intelligence, but for our purposes, let’s go with this:
Business Intelligence is the product of analyzing and distilling business-relevant data into actionable information that will inform better decision-making related to the management of assorted processes, functions and actions on the part of the enterprise.
The history of warfare provides numerous analogous examples of how intelligence is critical to decision-making. Some of the most disastrous battles in history were fought and lost because the generals who were involved made decisions based on bad intelligence or the absence of intelligence. Equally, some of the most brilliant victories were attributable to the quality and currency of information known about the enemy.
Decision-making in the world of business is no different, and results can be equally dramatic. In the past, the challenge for business managers was the lack of data available to facilitate effective Business Intelligence activities. Decision-making was frequently driven by past action, gut instinct and even wishful thinking.
Business Intelligence is the product of analyzing and distilling business-relevant data into actionable information that will inform better decision-making related to the management of assorted processes, functions and actions on the part of the enterprise.
Today, things have changed. Data, the grist of the Business Intelligence and analytical mill, is so plentiful that its very ubiquity can be problematic. Matching your data source to the process being managed is critical. What are the relevant metrics? Where does the supporting data come from?
Business Intelligence in the Information Age
Digitalization of processes, business records and transactional records has given us the ability to collect and store vast amounts of data. The deployment of sensors within complex machines such as automobiles, aircraft engines, airframes, locomotives, marine engines and other complex machines has provided vast numbers of new data sources that create prodigious amounts of data.
By example, a single jet engine can produce and download a full terabyte of data per hour of operation. An automobile will generate as much as 25 GBs of data per hour. This data is downloaded to manufacturers, sales teams, support services and maintenance teams for analysis and potentially for further action.
The rate of growth in data is nothing short of astounding. InsideBIGDATA estimates that the total quantity of data in our world will double every two years. Further, they show a 50-fold increase in data between the years 2010 and 2020.
Business Intelligence and Data Analytics
By itself, this mountain of data is about as useful as a mountain of dirt. The key to Business Intelligence is found in mining that mountain with the correct tools and parameters to extract and format data into useful information. That is where the key difference between intelligence and analytics is located.
Business Intelligence is all about the what, when, who and how-many questions. Analytics goes beyond this into answering the questions that are more relevant to your business. Why did something happen? Will it repeat? What effect will specific actions have on the outcome?
Even in specific vertical functions like sales management or performance management, making good decisions to support your planning and evaluation processes is critical. It depends upon distilling actionable information from the available data.
Business Intelligence Alchemy
This conversion process—turning the “lead” of data into the “gold” of information—is what successful Business Intelligence seeks to accomplish. The focus of this process can be aimed quite tightly at specific areas of the enterprise.
Here are some examples:
- Customer Behavior – Drives understanding of the lifecycle of your relationship with your customer. How they use your product and how they see you from a value perspective.
- Preventive Maintenance – Knowing when your customer’s product is about to fail is the best sales lead you can get.
- Market Trends – Understanding the dynamics of your market. Design your strategy for addressing that market.
- Financial Performance Factors – Credit worthiness, actuarial data and demographic preferences are all impacted by the availability of financial performance.
- Supply Chain Management – What are the risks to your supply chain that might be associated with weather, climate change, political instability and other variables.
- Cross-Selling and Upselling – Knowing your customer more completely and thoroughly will open avenues to expanded usage for your products within that customer’s business.
In future weeks, we will explore how to put Business Intelligence to work in your organization. We will explore how Sales and Sales management can employ and exploit existing or easily obtainable technologies within your organization to help reduce that data mountain into a Business Intelligence goldmine.
