4 Ways to Future-Proof Your Dashboards
by Dwight deVeraIn my last post, I ruminated on the problems that plague business intelligence dashboards. Traditional dashboards simply haven’t evolved as quickly as modern businesses, where decisions are made by many levels of management and need to be informed by various areas of the business – finance, marketing, sales, operations and more. If your dashboard is confined to your department’s metrics alone, it’s doing you a disservice. Dashboards of the future will require cross-functional views of KPIs to really be effective. And they’ll embed more self-service options than ever. The good news is that future-proofing your dashboards is possible. Here’s how:
1) Make your dashboards searchable.
Key performance indicators are essential for monitoring business performance. Last time, I talked about how “KPI overload” – common in so many businesses I’ve worked with – can cloud business insight. However in some cases, having hundreds of KPIs may actually be necessary for understanding and managing your performance. If you need KPIs from many parts of the business in order to make good decisions, it can become a complex task to find the information you need. So consider making your dashboards search-enabled so that users can easily find the metrics they’re looking for. Searching is how users find information; “Google” is a verb for a reason. So why should your BI system be any different?
2) Make your dashboards personalized.
Dashboards serve as a point of reference for business leaders, many times per day or at least a few times per week. Either way, your dashboard should be one of the things you look at the most in a given week (besides your husband, wife, or kids of course). From a personalization perspective, there’s something we can learn from a social medial platform like Pinterest…
A New Way of Thinking…Or Why Data Discovery Is Not the Only Path to BI Value Creation
by Roland Hoelscher
I am sitting on a train to Düsseldorf on my way back from Paris, where I presented an update of what we are doing at arcplan to a mixed audience of customers and prospects. Part of my presentation included the usual content of company and product development updates. The outlook included a preview of our next release, code named Xenon, in the context of what is happening in businesses these days. One of the key topics was the explosive appearance of mobile devices and the challenges this poses to organizations – different form factors and operating systems, security issues, and expectations from a user community that is educated by the private consumption of applications on these devices (bringing an expectation of usability to the business environment). Of course, I introduced our first-ever approach in the business intelligence world to solve the dilemma of catering to this ever-increasing diversity of different device types and form factors as DORA: Develop Once, Run Anywhere. This is accomplished by responsive design for business intelligence and analytics applications. The audience was clearly impressed as was our customer advisory board in a similar session last week.
However, this blog article is not about how to develop and deploy analytic content effectively in this new world; it’s about the business value BI solutions create.
This year we were positioned by Gartner in their annual Magic Quadrant for Business Intelligence Platforms. Although the Gartner analysts expressed strong appreciation for our capabilities (and commented accordingly in the strengths and cautions section of the report), we are positioned at the lower end of the niche vendor section. We were told this is partially due to self-service analytics and data discovery playing a strong role in this year’s Quadrant as this represents advanced BI. Really?
The Future of Dashboards – On-Demand Webinar
by Heather Smith
You’re invited to view arcplan’s latest webinar – 30 minutes that will change the way you think about dashboards.
The Future of Dashboards
Speaker: Dwight deVera, SVP of Professional Services at arcplan
There’s something wrong with dashboards – they’re stuck in the past. They’re designed for functional areas or departments, but as a modern decision-maker, you might need to view cross-functional KPIs from finance, sales, operations, marketing, and HR to make good decisions. So how do you reconcile the dashboards you have with the views you actually need to be effective?
In this webinar, we demonstrate:
- Why dashboards need to reflect the matrix-style way decision-makers are working today
- The “31 flavors problem” and how dashboard users can distinguish the signal from the noise when it comes to thousands of potential KPIs
- How our internet-fueled, “zero attention span” lives must influence dashboard design
- A simple way to make dashboards more effective by empowering users to develop their own “Pinterest-style” dashboards
It’s time to rethink what dashboards should be. Peek into the future with us in this webinar!
iWatch MyKPIs: Real-Time KPI Delivery to Your Watch?
by Roland Hoelscher
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?
Predictive Analytics: Examples, Advice and Shortcuts
by Dwight deVeraEveryone 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.
In Practice
Let’s take a look at finance institutions, which have predictive analytics down to a science….
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