Business Intelligence Blog from arcplan

5 BI Worst Practices to Avoid


bi-worst-practicesBusiness intelligence is the key to unlocking insights from data and empowering company leaders to make impactful decisions, act swiftly even in volatile market conditions, and plan strategically for the success of the organization. arcplan is celebrating its 20th anniversary this year, and BI has been around at least as long as we have. Over the last 2 decades, we’ve seen companies make similar mistakes – mistakes that undermine the success of their BI initiatives. Those new to BI should learn from their predecessors. Here are 5 common BI worst practices and how to avoid them:

1) Blindly buying technology without considering your analytical requirements
BI projects do sometimes fail; it’s not something anyone likes to talk about, but most of the time these failures can be blamed on a lack of requirements gathering. Vendors like us have to ensure that we understand our customers’ requirements inside and out in order to deliver a solution that will be successful and demonstrate concrete ROI. But the truth is, some companies don’t have a thorough understanding of their users’ needs before they start evaluating solutions. Too many organizations start “feature wars” with vendors and end up buying the solution with the most perceived bells and whistles – features they barely understand and will never have a use for.

This is a much of a problem for customers as it is for vendors; it’s our job to ensure that what we’re selling you will have value to your organization, and a lot of that comes down to understanding your users’ needs. But if you don’t understand your users’ needs, how can we?

The first thing you must understand before you try to purchase a BI solution is the analytical problems your company is trying to solve. Don’t get side-tracked by fancy bells and whistles that will not solve your business problems. Avoid the feature wars and make your shortlisted BI vendors prove that their solution is a match with a custom demo or proof-of-concept application.

2) Using BI as a gateway to Excel

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Better Planning Through Business Analytics


In past articles I’ve written here on arcplan’s BI Blog, I explored the role of spreadsheets in the planning, budgeting, and forecasting process and the importance of agility and accuracy. Today I would like to talk about the benefits of business analytics in the planning process when it comes to providing agility and accuracy.

When forecasts are consistently accurate, business leaders can have more confidence when making decisions and investments to guide the organization, as they have a good idea of how the organization will perform in the coming months. Agility is essential because volatile markets make it difficult for forecasts to reflect current business conditions. Therefore, Best-in-Class organizations are more likely than All Others to implement technology to enable both data access and the ability to utilize data to make predictive decisions (Figure 1). Fifty percent (50%) of Best-in-Class organizations have implemented an enterprise-level BI solution in comparison to 28% of All Others. These tools provide data in an easily consumable format so employees can find and utilize the data they need to make decisions. The Best-in-Class are also over twice as likely as All Others to have implemented predictive analytics. This technology helps to convert BI data into forward-looking forecasts.

Figure 1: Best-in-Class Technology Adoption


Source: Aberdeen Group, January 2013

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Build vs. Buy: Business Intelligence for Big Data Analytics


build-business-intelligence-arcplanWhy 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.

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Customer Analytics: See the Truth with Data Visualization – Part II


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 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:


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On-Demand Webinar: Business Intelligence as the Gateway to Big Data


View-WebinarCheck out this on-demand webinar from arcplan – a 40-minute primer on using big data and BI together for enterprise impact.

Business Intelligence as the Gateway to Big Data
Recorded Date: August 28, 2013
Speakers: Dwight deVera, arcplan Senior VP; Tom Veith, Senior Solutions Manager

About this webinar:

You’ve heard the hype around big data, and maybe you’ve put some thought into how it could impact your business. After all, the promise of big data is accessing hidden insights, discovering new approaches, and making better decisions. But how do you begin developing a technology approach that’s practical and doesn’t require a massive investment of money, time and resources?

big-data-biThe answer is to leverage business intelligence platforms that can handle huge data volumes, provide real-time access and enable data exploration. This webinar serves as a primer on how to practically use big data and BI together. Investments in big data usually allow a group of data scientists to deliver their results to a small community of business end users. To get beyond small communities and have an enterprise impact, you’ll need business intelligence – the mechanism to scale your big data initiative across the enterprise.

In this webinar, we:

  • Lay out the big data approaches you can take based on your available resources and infrastructure, and the benefits and challenges of each approach
  • Explain the benefits of utilizing existing BI platforms for big data analysis and visualization
  • Demonstrate big data and BI in action on Teradata and Google BigQuery

This isn’t a webinar for IT professionals only. We break the concepts down in a way that makes sense for everyone.

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