Business Intelligence Blog from arcplan
15Apr/140

Analytics As A Catalyst For Positive Inflection

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Year after year the hype surrounding data analytics becomes louder. Thought leaders and research organizations have sung the praises of analytics as a means for generating much-needed insight into business operations, and companies that have embraced analytics have been able to translate insight to better operational productivity and faster, more accurate decision-making. In a competitive business environment where your competition is just as hungry as you are to reach and secure new customers and where business leaders need to make accurate, fact-based decisions about the company’s future, analytics can be the game-changer that makes the difference between success and failure. Here’s how:

The beauty of analytics is that it can serve as a guideline for transforming sub-par business performance to one that is efficient and profitable. Whereas reports provide a historical view of what transpired, analytic output is forward-looking, and plays an integral role in helping executives plan for the future.
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13Jul/120

3 Ways Self-Service BI Aids Decision-Making

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There’s a lot of talk about expanding the reach of business intelligence beyond the 15-25% of potential users currently using BI solutions. Certainly it’s one of our core missions at arcplan. With nearly everyone in an organization making decisions every day that affect the company, getting this remaining 75% of potential users to answer their business questions with data is imperative. The solution is self-service BI – tools that allow users to navigate and visualize data themselves to get the answers they need to make important business decisions on their timeline. In many ways, self-service BI is synonymous with user freedom since business users need not wait for the IT department to fulfill report requests, but instead are able to generate queries on their own and tailor reports according to their requirements.

We spent some time thinking about the ways self-service aids decision-making. Check out our list and let us know if you have more to add to it!

1) It gives users access to real-time information for faster decision-making.
Ad-hoc reporting, one of the tools under the self-service umbrella, allows users to create new connections between data not previously found in static reports and generate new insights on their own. According to Cindi Howson’s report, The Five Myths of Self-Service BI, executives and managers are a segment of users beyond power users and IT developers who derive value from ad-hoc reporting. If given the chance, a sales director for instance would use an easy ad-hoc solution like arcplan Spotlight to run a query of YTD product sales and compare performance across different regions, rather than wait a week or more for IT to deliver the same information to him. He could also save that query privately or publish it publicly, giving his entire team access to it for future reference. He could even select that report for automatic delivery via e-mail, where it will include the most updated data. The ability to access real-time data and create new reports on the fly means that business users get immediate answers to business questions and can make decisions based on current (versus outdated) information.

2) It addresses specific user needs for greater efficiency.
Self-service tools target the specific needs of users, allowing them to glean the most value out their BI and enabling more efficient decision-making…

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14May/121

Poor Data Quality – Part I: The Consequences

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Data Quality - Garbage in, Garbage out?We’ve been thinking a lot about the various ways organizations can improve their existing business intelligence applications. Many of arcplan’s customers have been with us 5-10 or more years and are continuously improving their BI along the way. Some of the initiatives we frequently hear about are related to data quality improvement, but this may be an anomaly. According to Ventana Research’s recent study, less than half of organizations surveyed have taken on some kind of information management initiative, like data quality or data integration improvements, in the last 2 years due to budget restrictions or lack of employees with the right skills.

I’d argue that data quality initiatives should be a “top 5″ priority for organizations in 2012. Why? Because of stories like this: A friend recently told me about a meeting at his company where the regional sales managers were giving their summaries of pipeline opportunities. During one of the updates, a director interjected that he didn’t see the favorable developments mentioned in Salesforce, their CRM system. Based on the information that was present in the system, the director figured that the quarter would be an average one. However, the updates from the sales manager would really swing the potential outcome of the quarter in a positive way. Now I bet that director had to make some decisions that were compromised by the (lack of) current information in the CRM system. He might have started strategizing about how to re-engage with the (assumed) stagnant prospects, started working with marketing on a nurturing campaign, asked the telesales team to reach out…any number of things could have happened based off of the faulty information available to him.

Unfortunately, many organizations have to contend with poor data quality which ultimately results in poor decision-making. After all, decisions are no better than the data on which they’re based. Reliable, relevant, and complete data (as opposed to the incomplete data set available to the director in my example above) supports organizational efficiency and is a cornerstone of sound decision-making. So what are some of the consequences of sub-par data quality?

1) Mistrust. Poor data quality often breeds mistrust among internal departments. I read a great example from 1998 (if you can believe it) that could have been written yesterday:

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7May/120

Enterprise Collaboration vs. Collaborative BI: What’s the Difference?

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In recent months we’ve explored Collaborative BI as a growing trend and how it’s gaining popularity as an extension of traditional business intelligence solutions. Despite all the hype around this topic, it can be confusing to determine what makes Collaborative BI unique. I’ve seen the terms “Collaborative BI” and “enterprise collaboration” used interchangeably a lot lately, and while both may fall under the categories “Collaborative Decision-Making” or “Knowledge Management,” there are distinctions between the two that are important to understand.

Enterprise Collaboration
Though enterprise collaboration and Collaborative BI share some of the same features – the ability for users to interact like they would on social media, for example, rating, tagging, and commenting on content – enterprise collaboration is less specific about the type of interaction employees have. These platforms, like SharePoint and Socialcast, enable users to chat with each other, post blogs and wikis, make announcements, view the activity streams of other users, collaborate on projects, take polls, and generally do all the things they’d do in a workplace – but online. They provide a secure place for business users to work together and eliminate some of the need for project-related e-mails, phone calls, meetings, and shared drives. This article on CMS Wire gives a great example of how enterprise collaboration can improve the work life of a manager and his project team. It’s all about workflow and process-driven decision-making (as opposed to data-driven decision-making, which Collaborative BI facilitates).

Here are two ways that enterprise collaboration may look at your company:

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11Apr/120

Collaborative BI: Today & Tomorrow

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Collaboration is becoming an increasingly important facet of our business interactions. For years, research groups like Gartner , Ventana Research and the Aberdeen Group have provided insight and predictions about this phenomenon, and today we’re seeing how collaboration within the business intelligence space has moved from knowledge sharing and self-service BI to a whole new level of innovative decision-making for the business team. So let’s take a look at some of the shifting points of view about Collaborative BI and where it’s headed in the future.

Web 2.0 technologies and the social media boom have had a tremendous impact on what business users expect out of their business applications, especially in the collaborative space. Collaborating does not simply mean exchanging emails, making calls or holding meetings to facilitate decision-making (though they are the most-used ways according to Wayne Eckerson’s Collaborative BI report). These days, Twitter, LinkedIn, Facebook and YouTube have taught us how to share, rate, like, comment on, and especially make use of user-generated, helpful information. In our work lives, business users have learned to embrace information from various data sources – both formal and informal – as well as perform ad-hoc analyses without help from IT and share this information with colleagues. Collaborative BI as it exists presently is about facilitating the innate desire of business users to collect and share the information necessary for their everyday decision-making, while at the same time preventing duplicate work and allowing colleagues to draw on each other’s strengths. Users have an expectation that social media concepts will be available to them in their business environment, and so many Collaborative BI systems, like our own arcplan Engage, incorporate rating, tagging, etc.

However, we’re seeing a shift in how analysts define Collaborative BI and they are now calling for an even higher level of engagement.

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