In honor of arcplan 8‘s official release today, let’s talk about Responsive Design and its importance for business intelligence and planning applications. The latest version of arcplan’s platform is focused on mobile BI with a new HTML client that supports Responsive Design, which enables arcplan applications to automatically adapt their layouts to appear optimized on the end user’s device.
Responsive Design is something you’ve probably heard about when it comes to websites, but it’s just as important to application design – especially as organizations are challenged to support multiple devices and provide the best user experience possible on each of them. Responsive applications, like BI dashboards, rearrange their layouts and navigation to fit properly on smartphones, tablets, laptops and desktops. It’s not automatic; there’s no algorithm in the background figuring out the best layout. That is done by the application designer ahead of time. With arcplan, we have implemented “Views,” which define the breakpoints for each type of device. The designer then rearranges the application elements (charts, tables, filters, etc.) for each View. It’s quick, simple, and even better, all of the layouts are contained within one application. Changes made to an object are filtered down to each View/layout. There are no separate applications to maintain for each device. Just one total, no matter how many Views are defined.
So now that I’ve established how cool Responsive Design for BI is, let’s get into why it’s essential now.
An In-Depth Look at arcplan 8: Focus on Mobile BI
Recorded Date: October 3, 2013
Duration: 60 min.
Speakers: Dwight deVera, arcplan Senior VP; Wayne Chambliss, Senior Pre-Sales Engineer
The next release of arcplan’s business intelligence platform officially launched on September 26th. It focuses on efficient mobile BI, making it easier than ever for users and developers to mobile-enable their BI and planning apps for any device.
Watch this webinar on-demand to see:
- A primer on Responsive Design, a concept built into arcplan 8 that enables apps to dynamically adjust their layout to the end user’s screen size, resolution and orientation
- An exploration of arcplan 8’s new features, as well as a few updates from past releases that you may not be aware of (advanced analytics, commentary, etc.)
- A look at “Views,” a new concept in the arcplan Application Designer that enables developers to build responsive applications and print layouts with very little effort
- An in-depth demo of arcplan 8: responsive dashboards, self-service reporting (ad-hoc using Teradata as a data source) and more
This is a must-see not only for our customers and partners, but also for anyone interested in Responsive Design and how it applies to business intelligence.
Why It’s a Bad Idea to Build a Business Intelligence Platform From Scratch
A friend of mine is a Python developer for a billion-dollar corporation. His team is building a custom call center reporting app that connects to the company’s cloud data storage via APIs. I’ve seen some of the application and while it’s impressive for a custom system, it’s mostly tables of numbers with the occasional pie chart. This is after 8 months of work, and the only people accessing the system are a select few big data scientists.
Believe it or not, a number of companies are doing this kind of in-house development of analytical platforms. All the hype surrounding big data has them convinced that they’re missing out on the action. Consequently, companies large and small are devoting huge amounts of time, money and human resources to developing custom business intelligence systems for big data (Google BigQuery, Hadoop, etc.) reporting rather than simply choosing a platform that already exists and is proven to work in a similar environment.
At the heart of this trend is a desire for big data to have a greater impact in the organization. Since it’s usually small teams of data scientists who are dealing with big data, their impact and effectiveness is equivalent to a small drop in a much larger body of water – their ripple effect throughout the organization is often minimal and short-lived. To extend the reach of big data in the company and get important insights out to a greater number of decision makers, a BI platform is a necessary next step – one that leverages big data insights in easily-digestible executive reports and dashboards.
Some companies are going down the road of custom BI platform development, but their efforts are no match for solutions like arcplan that are already available. Below is a list of what you’d need to do to build a BI platform from scratch. You’ll quickly see why the effort and expense aren’t worthwhile.
I’m wrapping up my series on customer analytics and their associated visualizations with a discussion of 3 more metrics you should track on your customer dashboards – customer lifetime value, accounts receivable, and bookings & backlog – and why these simple visualizations are effective because they extend the reach of data to more people in the organization.
Track Customer Lifetime Value with a Stacked Bar Chart
One of the most underutilized metrics is customer lifetime value (CLTV), which sits at the intersection of sales, marketing and finance. CLTV calculates the historic value of a customer over time and helps establish how much customer relationships are worth – and therefore how much money can be spent to acquire them.
It’s conventional wisdom that it costs more to acquire new customers than it does to maintain existing business. For many companies, customers become more profitable over time. It costs less to pick up the phone and sell additional licenses to an existing software customer than it does to fly a sales person to meet with a prospect for the first time. It costs less to run loyalty programs to keep customers happy than it does to sponsor a trade show to meet new prospects. But the costs of these programs, all of which are necessary for running a business, have to be taken into account when using the CLTV metric. Customer lifetime value shouldn’t be something that only finance teams look at. Sales and marketing professionals must use it to ensure that their acquisition program costs are in line with CLTV.
There are many ways to calculate customer lifetime value, but the simplest is…
In Part I of this series, I covered some of the key metrics and visualizations that contribute to a 360 degree view of your customers. Today let’s explore two more metrics that reveal insights about your customers’ relationship with your company, and the graphs that best explain the data.
Track Net Promoter Score with a Gauge or Bar Chart
At B2B companies especially, you’ll often need to call upon your customers to serve as references in order to close new business. Some CRM systems like Salesforce.com enable you to add checkboxes to indicate whether a particular customer will serve as a reference or not. It’s simple to run a report on that information, summarizing the number of checkboxes over the total number of customers, but visualizing a more robust metric on a dashboard keeps customer relationships top-of-mind with your marketing, sales, and customer support teams.
Many arcplan customers are going back to an old standby metric, the Net Promoter Score (NPS), which segments the percentage of customers who would recommend your products and services (“Promoters”), versus those who are satisfied but unenthusiastic (“Passives”) and those who aren’t happy and might go out of their way to voice negative opinions (“Detractors”). On a scale of 1-10 for the question “How likely would you be to recommend <<company>> to a colleague?”, Detractors are the people who choose 1-6, Passives choose 7-8, and Promoters choose 9 or 10: