Business Intelligence Blog from arcplan
14Feb/140

5 Ways to Improve Business Intelligence Value

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valueHas your business intelligence software under-delivered on value? I don’t only mean the ROI of your BI – I also mean simply how valuable BI is to your organization. Is its use engrained in your company culture? If it’s not, you’re in the majority. By some estimates, 80% of corporate data isn’t accessed by BI users. How important to your culture can BI be if it’s only touching 20% of your data? But this isn’t an article about big data or social data – this is an article about changes you can make this year to improve how valuable BI is to your company, to increase the number of users who rely on it, and to make it essential to your everyday operations. You’ve likely paid between $100,000 and $1,000,000 for your BI system – why not squeeze every last drop of value out of it?

1) Pump customer data into your analysis
Is there a company in the world who can say “We have access to all the data we need about our customers”? A 360 degree view of customers is something every company seems to be chasing. Though it might seem like an elusive goal, you can take the first steps by integrating data from your CRM, accounting and customer support systems into your BI dashboards and reports to enable analysis of customer growth, profitability, and lifetime value. Understanding these KPIs can help you spot trends, identify opportunities to cross-sell, up-sell or simply target them more effectively. Your BI platform likely connects data from multiple sources, so why not take advantage of this inherent value by getting your platform to assemble the necessary data for you so you don’t waste time manually integrating data from all these different systems. It might not be quick to incorporate customer analytics into your BI initiative, but more companies are finding it essential to the continued value of their business intelligence and the success of their company.

Learn more about customer analytics in our blog series, which starts here.

2) Set up alerts and delivery

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26Nov/130

3 Ways Analytics Help Retailers See Black Friday More Than Once a Year

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retailers-black-friday-arcplanPeople 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…

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28Feb/130

Dashboard Lessons from “Are You Smarter Than a 5th Grader?”

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5thgraderAdvice for using business intelligence to keep winning

I like to channel surf, and one day I got sucked into the game show “Are You Smarter Than a 5th Grader?” I never watched it when it originally aired, but now I’m addicted! The show is set up like a school quiz, with contestants earning money when they answer questions correctly. The kicker is that the questions are based on things we learn in elementary school…things that are quickly forgotten since they’re not tested in everyday life. Once I really got into the show, I realized there are business intelligence lessons to be learned from it.

On stage with the contestant are a few 5th grade students who can help if the person chooses to “cheat” as they pursue the $1,000,000 prize. Let’s examine how each of the available cheats tells us something about BI dashboards.

Peeking is encouraged. If a contestant is unable to answer a question on their own, a “peek” allows them to glance at a 5th grader’s answer and decide whether or not they would like to use it. How does that relate to BI you wonder? Think about the predictive nature of BI – it allows you to peek into what may happen in the future so you can take corrective action today. Especially valuable for businesses whose markets are volatile and sales growth may change from one quarter to the next, or for businesses whose production costs fluctuate depending on circumstances – predictive analytics, what-if scenarios, and break-even analysis eliminate some of the randomness from your decision-making. Luckily with solutions like arcplan, it’s easy to add predictive elements like regression analysis and Monte Carlo simulation to your dashboards. So really, peeking on “5th Grader” isn’t that different from modern BI.

Copying is expected.

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14Feb/130

Predictive Analytics: Examples, Advice and Shortcuts

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Everyone is throwing around the term “analytics” – about as much as they’re throwing around the term “big data.” While I might put big data on my list of the Most Overused Phrases, analytics gets a pass. As companies realize the amount of insight and value they can glean from their ever growing volumes of data, there has been a surge in analytics initiatives. The goal of these projects is to use data to analyze trends, the effects of decisions, and the impact of scenarios to make improvements that will positively impact the company’s bottom line, improve processes, and help the business plan for the future.

In order for analytics to remain relevant and always provide value, organizations must continually up their game. One way to do this is with predictive analytics, which is becoming more mainstream every day. If you stick around to the end of the article, I’ll tell you a simple way to bypass its complexity and still get the predictions you need.

Gettin’ Predictive With It
Ventana-predictivePredictive analytics involves making predictions about the future or setting potential courses of action by analyzing past data. A 2012 benchmark study by Ventana Research revealed that predictive analytics is currently used to address a variety of business needs, including forecasting, marketing, customer service, product offers and even fraud detection. While predictive analytics used to be in play in only a small number of companies, two-thirds of companies participating in Ventana’s survey are using it, and among those, two-thirds are satisfied or very satisfied. These results indicate the maturity that predictive analytics has undergone over the last few years, as technology has advanced to make it less expensive and more approachable, and therefore easier for more areas of the business to make use of. At this point, it’s safe to say that most Fortune 500 companies are churning out predictive insights on a regular basis, but that doesn’t mean smaller companies without “big data” can’t do the same thing. They can supplement their internal data with external data from social media, government agencies, and other sources of public data to get the insights they need.

In Practice
Let’s take a look at finance institutions, which have predictive analytics down to a science….

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