Business Intelligence Blog from arcplan
17May/120

Responsive Design + Metro Design in Business Intelligence Applications

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Recently we have seen a dramatic change when it comes to deciding which screen size to design a new report or dashboard for. It’s always been a struggle for BI app designers to optimize applications to fit to the different sizes of desktop PCs and laptops, but adding mobile devices like smartphones and tablet PCs to the mix makes it even more complex.

The most natural solution of the past was to design two different views – one for the desktop and one for mobile deployment. But we no longer recommend this approach as the lines between different device categories are blurring.

Netbooks are encroaching on notebook and iPad territory, coming closer to their display capabilities. iPad has initiated a storm of new devices from other vendors with similar screen size. Even worse (from an app design point of view), Internet giant Amazon.com launched its Kindle Fire, whose screen size sits between traditional smartphones and tablet PCs. And now new devices like the Galaxy Note and the Galaxy III by Samsung, whose screen sizes are between the iPhone and the Kindle Fire, have found their own fans.

Although size does matter, screen size is not the sole point to consider when designing BI apps. There’s orientation to consider – which devices are optimized for portrait or landscape orientation – and on top of this, different vendors also offer a wide variety of pixel density – defined by pixels per Inch (PPI). For example, the new iPhone 4S with its Retina Display is able to display more pixels on its 3.5″ display than a decent netbook.

For app designers, it is impossible to create separate reports for every device, especially at organizations where BYOD (bring your own device) is the standard. This would end up being a total nightmare from a maintenance point of view. So what can we do? It’s time for a new and intelligent approach that will allow us to use one app and one report or dashboard layout for all devices.

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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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16Apr/120

Top 5 Collaborative BI Solution Criteria

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Collaborative BI enables employees at every level to make meaningful decisions for their areas of responsibility, backed by easily-accessible information and analyses. With 15% of BI deployments containing collaborative elements by 2013 according to Gartner, it’s time to start evaluating the kind of Collaborative BI solution that will work for your enterprise. To help, we’ve defined the top 5 criteria you should consider:

1. Integration of disparate systems
Integration of varying systems is a challenge for most businesses, but one that can be overcome with the right Collaborative BI solution. Enterprises often have several different stand-alone solutions for BI in place as well as other decision-relevant – often unstructured – content that is disconnected from BI systems. Your Collaborative BI solution should act as a bridge between these disparate systems, connecting them with a simple search function that delivers results from multiple BI vendors, third-party systems like SharePoint or e-mail, documents, articles, and user-contributed content. It should also allow users to open and use any report, analysis, or document within the Collaborative BI interface so that switching between tools is unnecessary.

2. Flexibility & personalization
Collaborative BI systems must allow users to perform a variety of actions, from contributing content to bookmarking to knowledge sharing. The ability for users to submit content to enrich the Collaborative BI system is paramount for system affinity and adoption. Who better to contribute content than users themselves – those who are making everyday business decisions with their available data? Users must be able to upload relevant information and reports from external sources (Salesforce.com for example) as well as bookmark items as favorites. In our own Collaborative BI solution, arcplan Engage, users have BI Walls where they can pin frequently-viewed reports or snippets of dashboards. In this way, each user can configure their own personal Collaborative BI environment.

3. Availability on any device

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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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2Feb/120

Collaboration – the Future of Decision Making?

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Perhaps every generation says this at least once, but I believe we’re in the midst of a very interesting time. The world is getting more social everyday with Facebook, Twitter, and LinkedIn, where we can find old friends, colleagues and even relatives online with a single click. We may even find new people to follow through social media tools’ recommendations and can form relationships online and offline with them. Hundreds of millions of users are making decisions online all the time – who to follow, what content seems interesting, what topics to promote.

Our social media feeds make it obvious who to engage with about a particular topic – a friend may post frequently about sports and you can go to him with thoughts or questions – but that type of insight is not widely available at the place where we spent most of our time: work. We lack intelligence when it comes to the enterprise decision making process. It follows that we should apply the same principles of social media in our corporate environments to identify which colleague can help us make decisions. Applying social media functions that allow users to rate, tag, and comment about corporate content is the answer. Enterprises gain insight into the most used reports and dashboards at the company, report authors get instant feedback and enhancement requests from users, and users gain from the existing expertise of colleagues.

This idea has led to a new category of business intelligence software that Gartner describes as Collaborative Decision Making (CDM) and Collaborative BI. Gartner considers such platforms an emerging trend to fill the gap in decision support for tactical and strategic decisions most often made by knowledge workers.

“By 2013, 15% of BI and analytic applications will combine BI, collaboration and social software in decision-making environments.” – Gartner Group

BI vendors are following this path, creating matching solutions that serve as an interface to your wealth of corporate data. Is the market ready to deploy these solutions?

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