How BI facilitates a decision-making process that saves millions
At the core of every business decision is the desire to drive value for the company – whether that’s increased sales, higher margins, elevated profits, or return on investment. Decision makers should use all the resources at their disposal to drive this value, including their business intelligence software, which may include guided analytics (i.e. dashboards), ad-hoc analysis and collaboration capabilities that contribute to informed decision-making. Today I’ll explore how BI software facilitates decisions in a retail scenario. But this article isn’t just for retailers – anyone can extrapolate this information to their business to see how BI can provide concrete ROI.
arcplan serves a number of customers in the retail industry, including two of the largest grocery chains in the United States. Retailers are well-known for the small net revenue margins – on average, 3% across the globe for all types of retailers – which pose significant challenges on process controls and efficiency in supply chain decisions. One of the key areas of interest for all retailers, especially grocery chains, is the reduction of shrink – the loss of inventory due to product spoilage, waste, theft and other causes. It’s estimated to account for 2-3% of overall sales. Perishable shrink even goes up to 5% within a typical grocery chain. So for one of our customers, whose revenue reached $6.25 billion in 2012, a reduction in shrink of just 0.1% means $6.2 million to their bottom line.
So a simple question that would catalyze a decision-making process at this grocery chain might be: How can BI help reduce my shrink by 0.1% while balancing availability of goods and customer satisfaction? They would want to meet high customer expectations without over-ordering, which leads to shrink through spoilage.
Mobile-First BI Enabled by Responsive Design
Recorded Date: August 13, 2013
Speakers: Dwight deVera, arcplan Senior VP; Takashi Binns, Solutions Manager
About this webinar:
Conditions are finally right for mobile business intelligence to take off: affordable, high-performance devices are in the hands of nearly 50% of the population, BYOD policies are spreading like wildfire, and users are clamoring for performance information anywhere and everywhere they are. Mobile BI is no longer just a possibility but an inevitability.
A mobile-first design philosophy is necessary in 2013 and beyond to future-proof your BI apps. But with so many different devices available to users, how do you create usable yet easy to maintain business intelligence, analysis, and planning applications that work on every one? The answer is Responsive Design.
This 30-minute webinar is a primer on Responsive Design, a concept that enables apps to dynamically adjust their layout to the end user’s screen size, resolution and orientation. We review:
- Why Responsive Design is the best way to develop BI apps going forward
- How you can achieve a 60-80% reduction in mobile BI development and maintenance costs
- Examples of responsively designed dashboards
As mobile devices become the primary way of accessing BI, now is a good time to revise your strategy to “mobile-first.” Watch this webinar to learn more.
Last week I had the pleasure of attending Collaborate 13, the Technology & Applications Forum for the Oracle Community, for the first time. Over 5,000 Oracle experts, users, and partners assembled in Denver, Colorado for a week of education and networking.
I was there as arcplan’s Director of North American Alliances to build and expand our partner community. As the most widely-used third-party BI frontend to Oracle Essbase, I was looking to meet with Essbase experts as well as Hyperion and OBIEE consulting and systems integration firms. Collaborate was an excellent way to get in front of these companies, who can benefit by adding arcplan to their solutions portfolio. I found a great deal of interest and acceptance of our positioning: arcplan as a lower cost, less complex, and quicker-to-implement solution than OBIEE; our extensive connectivity within and outside of Oracle databases; and our ease of use for developers and end users.
My colleagues mentioned that last year at our booth, the common theme of conversations was the challenges IOUG and OAUG members were experiencing around budgeting and planning. This year, however, the conversations tended toward challenges around reporting and dashboards – the importance of connecting all their data sources and making meaningful use out of the data they already have without having to build additional repositories or metadata layers. arcplan is a lightweight, flexible alternative to the Oracle and SAP BI tools many companies have in place that aren’t meeting their needs.
While I met with partners and our team manned the booth, our CEO Roland Hölscher attended Collaborate’s educational sessions…
As speculation about Apple’s iWatch grows – will it be a snap bracelet? will it replace the iPhone? – it got me thinking about a watch (of all things) supporting the vision of real-time analytics. What sounds stupid at first (the notion of an old-fashioned personal device, around for 5 centuries with little to no innovation over such a long period, inspiring a 21st century topic such as real-time analytics) has some merits if you think about it twice.
First off, wearable computing devices are real business. According to tech analyst Juniper Research, the next-gen wearable devices market, including smart glasses, will be worth more than $1.5 billion by 2014, up from just $800 million this year.
While the majority of those devices are sold in the context of fitness and healthcare scenarios, there is applicability in modern enterprises. In fact any business process that can benefit from real-time analytics can leverage computing devices that are “at hand” and travel with us easily.
So what business processes can benefit from real-time analytics?
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
Predictive 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.
Let’s take a look at finance institutions, which have predictive analytics down to a science….