While it might seem like every company on earth is using business intelligence tools to glean insight from their corporate data, surveys say that nearly 10% of companies do not yet have BI in place. Even though 91% of companies may have it deployed somewhere in their organization, anecdotally BI vendors like to trot out the statistic that only 20% of potential users have access to business intelligence. The more companies we talk to, the more this seems true.
If you run a company or a department that doesn’t have access to BI tools, you might wonder how you can use them. Boris Evelson from Forrester Research compiled a list of analysis types that may apply to your situation:
- Historical (what happened)
- Operational (what is happening now)
- Analytical (why did it happen)
- Predictive (what might happen)
- Prescriptive (what should I do about it)
- Exploratory (what’s out there that I don’t know about)
When you’re first starting out with BI, you’ll likely be most interested in historical and operational analytics, though we often work with finance teams who want to dive right into predictive analytics. Let’s look at a few practical BI use cases in various departments of an organization.
Finance Department: Historical, Operational, Analytical, and Predictive Analysis
People do crazy things, especially during the holiday season. On Black Friday – and even on Thanksgiving evening – customers will wait in line for hours to grab the best deals and knock items off their wish list. Retailers offer ridiculous discounts on high-priced items and keep doors open 3 days straight to cater to buyers around the clock, then web retailers kick in their own Cyber Monday promotions. Black Friday has remained the number one shopping day for the past decade, accounting for most of the sales that businesses reign in during the holiday season. But smart retailers don’t have to wait until Black Friday to ramp up their bottom line. Your analytical or business intelligence platform can keep a pulse on operations year round and help increase sales before the 11th hour. Here’s how:
1) Use analytics for in-store promotions
Analytics can help guide store layouts by tracking which products perform best on an aisle shelf vs. an endcap in various cities, and what products should go on sale in a given month and region based on sales history and inventory levels. Using business intelligence, you can run scenarios based on historical data and make predictions about programs designed to drive in-store business. For example, if you increase the circulation of your direct-mail flyer, how much additional business can you expect it to drive? Similarly, if you offer in-store coupons for a certain timeframe, what kind of sales uptick can you expect? Essentially, you can analyze past customer purchasing behavior to determine how to best influence future purchasing behavior.
arcplan’s retail customers use our platform to track KPIs and run what-if scenarios to ensure that products are priced appropriately. For retailers, one important KPI is the cost of goods sold (COGS) – the price paid for the product, plus shipping, handling and other expenses to get it ready for sale. By keeping track of COGS…