Business Intelligence Blog from arcplan
14Feb/121

Business Intelligence at Hospitals: Real-World Examples of Hospital Efficiency & Quality Metrics

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As both the battalion chief of my local ambulance and rescue squad and a business intelligence consultant, you can imagine that healthcare analytics are near and dear to me. Plus, living in the Philadelphia region, it’s impossible to escape the news of numerous hospital closures every year. So at arcplan, I love working with hospitals and healthcare organizations to build reports and dashboards that track the metrics critical to their survival. All the way back in 2001, Paul Mango and Louis Shapiro of McKinsey & Company argued that hospitals are essentially a commodity business and therefore need to compete on the basis of operational efficiency. This sentiment rings true more than 10 years later, with skyrocketing medical costs, declining insurance reimbursements, and increased utilization by an aging population. Giving hospital executives (and physicians!) access to real-time data has never been more critical to hospital operations.

Hospital executives often report on financial, operational and clinical system metrics which are crucial to ongoing operations and management. The hospitals we’ve worked with often have an overarching goal to provide efficient, quality care to patients, and they need access to their existing data to make sure they are achieving that goal. Important metrics that roll up to the goal of “efficiency” include the average wait time for a hospital bed, physician productivity, nurse turnover rates and the cost per discharge. Metrics that roll up to a “quality” goal include average length of stay, re-admission rates and patient satisfaction. The only way to improve the quality and efficiency of care is to analyze current performance and identify areas for improvement.

One of arcplan’s customers, the largest private operator of healthcare facilities in the world, came to us when they were focusing on efficiency. For more than 5 years, they have used an arcplan-powered business intelligence system (with data from Oracle Essbase and Teradata) to track key metrics and make decisions that improve efficiency of care – specifically in emergency rooms. All of their ERs needed to reduce wait times, shorten lengths of stay, and avoid people leaving the ER without care and treatment. The goal became to have every ER patient seen by a doctor within 45 minutes of arrival.

So what metrics do they track to achieve this goal? Here are a few examples:

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17Jan/123

The Big Data Trend Explained: Big Data vs. Large Data

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Acquiring thorough insight into your data and tapping into the needs and buying patterns of customers are growing needs for businesses striving to increase operational efficiency and gain competitive advantage. Throughout 2011, I noticed a heightened interest in ‘big data’ and ‘big data analytics’ and the implications they have for businesses. In August, Gartner placed big data and extreme information processing on the initial rising slope of their Hype Cycle for Emerging Technologies, so we’re just at the beginning of the big data trend. A recent TDWI survey reports that 34% of organizations are tapping into large data sets using advanced analytics tools with the goal of providing better business insight. The promise of big data analytics is that harnessing the wealth (and volume) of information within your business can significantly boost efficiency and increase your bottom line.

The term ‘big data’ is an all-inclusive term used to describe vast amounts of information. In contrast to traditional data which is typically stored in a relational database, big data varies in terms of volume, frequency, variety and value. Big data is characteristically generated in large volumes – on the order of terabytes or exabytes of data (one exabyte starts with 1 and has 18 zeros after it) per individual data set. Big data is also generated in high frequency, meaning that information is collected at frequent intervals. Additionally, big data is usually not nicely packaged in a spreadsheet or even a multidimensional database and often takes unstructured, qualitative information into account as well.

So where does all this data come from?

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16Nov/111

Uncovering 21st Century Consumer Behavior with Business Intelligence

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This post on BI for retailers is co-authored along with Raj Kutty, CEO of iVEDiX.

Retailers are frequently challenged with a new definition of multi-channel marketing. The marketing landscape includes more than the traditional components of print advertising, direct mail, and Customer Relationship Management (CRM). It also rolls email, social media, mobile and web (e-commerce) into the marketing mix. Customers engage with brands and make purchasing decisions on a new array of platforms, which has increased the amount of consumer behavior data available for retailers to manage. This subsequently makes the marketing campaign management process much more complex—from budgeting and planning to predicting consumer behavior to providing superior customer service.

With the rapid advent of new, innovative technologies, Business Intelligence (BI) has seen a great deal of change over the past few years. BI has reached a state of sophistication where it is being adopted as a key strategic initiative by retailers. BI solutions aggregate information and provide retailers fast and easy access to data for business reporting, analysis, planning and decision support. By transforming data into actionable information, BI helps retailers make better fact-based decisions at every level of an organization.

Social media, an influencer of consumer behavior
Most retailers are aware of who their customers are. They are equipped with the technology to reasonably ascertain demographics, buying patterns and influencing behaviors. However, the proliferation of numerous social media channels in the consumer market—like Facebook, Twitter and Foursquare—has exponentially amplified the challenge of identifying and understanding target markets. Next generation Web 2.0 communication has altered the frequency and intimacy with which retailers interact with their customers.

Retailers, more often than not, have data on their customers’ online and in-person shopping habits stored in separate repositories—a CRM system and an ecommerce database. For a complete analysis, this information can be combined with social media data—customers who “like” a particular store or product or who tweet about a specific brand or product—as well as fundamental demographic information such as income level, gender and age. These layers of information can be superimposed on a geographical map to create very powerful campaign segmentation visuals. Going even further, tying in customers’ actual receipts can give the retailer an incredible perspective on the customers’ buying behavior and thought process leading up to their purchasing decision.

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13Oct/110

Mobile BI’s Hype vs. True Adoption Rates

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Is mobile BI more than just hype? We think so.There’s no denying the hype around mobile BI. But how much of this talk is actually put into action? According to The BI Survey 10, the world’s largest independent survey of BI users published this week by the Business Application Research Center (BARC), only 8% of companies using BI software access reports on mobile devices! That’s a surprisingly low number considering how much BI vendors (including arcplan) have been promoting it as the next big thing, how many analyst reports and surveys have been devoted to it, and, of course, how many companies seem to be clamoring for it. Let’s consider the factors that contribute to this low adoption rate and evaluate whether there’s any redemption for mobile BI adoption in the future.

It should come as no surprise that the heaviest consumers of BI are the folks behind the desk. In a recent post on mobile BI, we called out these users specifically to include account managers, research analysts and finance managers – the “first to arrive and last to leave” crowd. Because their work is best accomplished behind a desk, there’s less likelihood that they’ll need to rely on a smartphone or tablet PC for reporting or analysis. So this huge subset of BI users can’t be relied upon to be the first adopters.

Who else isn’t adopting mobile BI right now? Apparently the executive set. A major reason for low adoption rates, according to BARC, is that the prime candidates for mobile BI usage – namely executives and high-level managers – are too busy to even run reports and would actually prefer to be fed information by someone else. In other words, they’d rather trust someone else to quickly tell them what they need to know.

Even with these two major factors, 8% still seems like quite a low adoption rate, so what else could be going on here?

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10Oct/110

Teradata PARTNERS User Group Conference 2011 Recap

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If you follow arcplan news, you’ve probably heard about our new partnership with Teradata. We just got back from exhibiting at the Teradata PARTNERS User Group Conference (TDPUG) in San Diego late last week and we’re blown away by how well we were received at the show.

Overall, the show was positive and encouraging, with Teradata’s customers really looking to partners for ways to extend the reach of their existing infrastructure and drive utilization and data storage within Teradata.

We met with so many data architects, DBAs, BI managers, and analysts who were excited over arcplan’s status as the only partner to support Teradata’s new OLAP connector without the need for a semantic layer. We talked to many Teradata customers who have already installed (or are in the final stages of installing) the OLAP connector in order to directly integrate a BI solution into their Teradata Warehouse. That’s what arcplan does, and it saves developers time – time to value, time to build reports, dashboards, and other analytic applications…and it also saves money since it requires less resources and less infrastructure.

We demo’d arcplan’s support for the Teradata OLAP connector and heard a lot of interest in the fact that arcplan takes the power of Excel (the only other way to access the OLAP interface directly) and broadens it to the casual business user of BI – those who need intuitive access to their reports and dashboards either on their desktop browser or on any mobile device. In fact, I spent most of the show walking around with my iPad out, showing arcplan + Teradata everywhere I went (as you can see in the picture).

We also spoke with attendees in the finance function, or IT managers responsible for budgeting and planning support, whose interest was piqued by our integrated platform, which combines reporting with budgeting and planning capabilities (allowing Teradata customers to leverage their existing infrastructure and expertise to address this additional organizational need!).

We’ll definitely be back next year. In the meantime, if you have questions about how arcplan works with Teradata, or if you’re a Teradata customer who is exploring the OLAP connector, email us or leave us a comment!