Business Intelligence Evolves to Serve Users

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Business data and BI software are currently beginning a new phase of evolution. In this new phase, users of business data will be able to collaborate and connect with other colleagues and team members without multiple spreadsheets and laborious processes.

The BI user experiences of past decades are being re-thought and fast collaboration and crossover functionality are the way of the future.  Southard Jones, in the May 9th Venture Beat article Blurred lines: Reimagining the user experience for business intelligence, details how companies are developing new ways of delivering business data and what companies will be looking for in the future.

The article is of interest because it discusses that the business intelligence space needs to evolve to meet the needs of modern businesses.  Currently, there is little crossover functionality between products, and products are rigidly aligned to arbitrary user “roles” like information consumers vs. producers. But, people are not rigidly defined in their roles; they need to be able to answer questions quickly, using their business data. “Blurring” the line between consumers and producers of information is one example of how business intelligence products need to evolve, because blurring that line will make everyone more productive.

Crossover functionality is another topic this article broaches. To quote Jones, “Ensuring success with BI and analytics also means recognizing that different people prefer different tools.”  We whole heartedly agree! People in business should be able to access relevant, informative data quickly, and from whichever tool seems appropriate to them.

His article feels very validating because at least someone in the BI industry sees the status quo is no way to continue.  Jones also writes, “The modern business landscape demands a new approach to the user experience. […] And one that allows interoperability between different products. Our work styles have evolved. BI and analytics should do the same.”

One such software, developed by PARIS Technologies, is taking on this new, modern business crossover and collaboration and use of multiple products with their newest product Olation®. With this kind of technology, companies can eliminate inaccurate data and time-consuming processes that stem from data located in various applications, spreadsheets and databases.  With Olation, data is centralized in a non-proprietary database and access to that information is permitted simultaneously by multiple users in their different applications.  It’s is a game-changer, especially if you’ve been struggling with a typical or limited BI tool. With everyone in the business working from the same source data set, and Olation’s calculation engine doing the formula and calculation work, there is little manual spreadsheet work to be done. Which means analysts can actually answer questions quickly and spend time getting to the meat of data discovery.

Learn More About Olation

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The Need for Business Analytics, even Inside the Dean’s Office

You may not think that business analytics as a concept applies to academics, but access to meaningful and timely information is critical to the proper function of a dean’s office.  Anyone who has been a dean or worked in the dean’s office knows that.  And, like in any other business, certain kinds of data seem to percolate to the top of the needs list, but that data is all too frequently not easily accessible.

Take, for example, the need to project student enrollment for the ensuing year. As new students arrive on campus, there must be an adequate number of required courses as well as qualified faculty to teach those courses.  If enrollment is low because of a glitch or error in the Admissions Office, or there is an unexpected fluctuation in applications, the number of courses can be adversely impacted.

Similarly, enrollment projections are required several years forward, suggesting the need for a strong analytics tool, and one that allows for “what if” eventualities. The dean’s office needs to be able to monitor the number of applications, the number of offers tendered, the number of offers accepted, the number of paid acceptances, the cumulative amount of financial aid and the average aid per applicant.

These are just a few of the desired “data intelligence” items to have available at one’s fingertips; each one of these belongs to its own “dimension” for measuring performance. These enrollment statistics and other metrics drive the university, and the university president regularly seeks to be updated, just like any other CEO who needs “business analytics” to run a company.  Of course, a graph showing how the current numbers compare to past numbers is necessary.

The challenge is delivering up this intelligence, as by nature it is “multidimensional,” a word one encounters in typical definitions of OLAP technology.

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For example, one obvious dimension is “school” or “college,” since typically colleges are subdivided into various schools while universities are subdivided into colleges.  Thus, university X might have a College of Medicine, College of Business, and the like.  And so all the metrics above might be required by each school or college as well.

Other dimensions might concern staff [faculty] allocation to courses as well as course availability for student selection. Tracking the number of students progressing through the colleges from year to year, especially at the undergraduate level, is desirable so that sufficient resources can be properly allocated in a timely fashion.  When faculty are absent from the university for the purpose of a sabbatical (another dimension), their classes and student advisees must be accommodated either through existing faculty movement or the hiring of adjunct faculty.  If adjunct faculty are to be hired, the problem of recruiting an academically or professionally qualified individual can be a formidable challenge, not to mention the impact on a budget that might need to be crafted two or three years in advance.  This means that access to appropriate historical and current data must be available.

To consider another factor impacting faculty allocation: students, especially undergraduates, change majors at least once and it is not altogether unusual for a student to change majors several times.  As students move from one major to another, frequently within the same college, demand for certain courses might unexpectedly increase or drop.  Having as much advance data intelligence as possible for the potential impact on staff teaching needs in turn would lessen any adverse effect on financial budget plans.

Of course, the need for financial information is forever present in higher education as it is in business.  The usual data such as major budget categories and current progress should be easily available along with a comparison with past budgets.  Of equal importance is the projection to end-of-year.  At a different level the projected liability of the university to support the scholarships granted is something the financial vice president would want to know.  And it is not uncommon for faculty to approach their dean with requests for additional travel funds so they can take advantage of some unforeseen opportunity. As in the business world, in the face of unavailable or incomplete data, the answer is typically in the negative!

The list of information needs continues with the number and kind of publication each faculty member writes, the total yield for each faculty member over the number of years necessary to meet accreditation requirements, the percentage of publications in high quality journals, and perhaps some ranking of faculty by academic production.

I have indicated these information needs not only to suggest that in the academic environment they can be vast and various, but also to suggest that it behooves us to look beyond products with limited single information source availability. A really productive solution would also provide modeling with 1) robust “dimensionality”, 2) “what if” capabilities, and 3) the ability to compare Current v. Historical v. various Planned scenarios. These are hallmarks of products featuring OLAP technology, which, though more widely adopted in the business community, are clearly well-suited and necessary to provide an application-oriented academic “business analytics” program as well.

(Professor Bill Tastle is a regular contributor to OLAP.com. At Ithaca College he teaches a course in Business Analytics, and uses PowerOLAP from PARIS Technologies for in-class exercises.)

Infographic: Why BI is Key for Competitive Advantage

A great infograhic from the Master of Science in Computer Information Systems program at Boston University.  The BU researchers focused on: growth of business intelligence, management of data, decision-making and budgeting.  Enjoy!

 

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{Originally posted here}

Excel-Friendly BI Helps Teach Business Analytics at the University

By Bill Tastle, our newest OLAP.com contributor

As a Professor at an AACSB accredited business school, I am responsible for preparing  business students who are eager to enter the marketplace upon graduation. Naturally,  I spend a lot of time researching about what skills will best serve them. This can be more of a challenge than one might think because today’s skills may not be in demand tomorrow but one thing appears to be quite apparent; the need for graduates trained in the methods of business analytics will be in demand for at least the next decade.  Thus, my business school faculty members and I have been discussing how best to incorporate Business Intelligence (BI) skills into our existing program.

This is a bit exasperating if one’s business school/college is AACSB accredited, because the required set of courses that comprise the curricula have very little room for extras.  BI, I must argue, is not an “extra” but rather, a critical component to a student’s undergraduate business education.

So, I carefully examined the landscape for suitable software tools to bring into my undergraduate classroom environment. I spent considerable time reading everything I could find from many, many companies and multinational corporations hawking tools for BI. Eventually, I happened upon a company featuring a strong “Excel user-friendly” product.

There seemed to be a natural logic to doing BI in Excel, given the pervasive use of spreadsheets in the business community, but what I had discovered is that many software vendors try to address the Excel “problem” by doing away with Excel altogether.

This company had a different approach, which is to embrace what Excel has to offer as a familiar front end. I sent off an email asking for information and virtually immediately was in contact with someone at the company and quickly received their literature. I read it!  Carefully!  The more I read, the more excited I became.

It is pretty obvious that all business schools teach Microsoft Excel, some at a trivial level, which is little more than a superficial introduction, and others are more advanced levels.  Perhaps I am a statistical outlier, but at my school, sophomores must become Microsoft Expert certified to pass their required business technology course.

So, the ability to bring a BI tool directly into Excel in the form of a simple add-in has made all the difference in the world.  Students receive an introduction to the world of BI and quickly discover what is meant by “multi-dimensionality,” an important concept when business performance models (“cubes” in BI terminology) are being constructed.

I could not do as good of a job teaching Business Analytics if I had to teach an enterprise database program first, just to get to their dashboard graphs.  Furthermore, being able to attach the BI software program to other sources of data made it all the more fascinating to students who are amazed to discover they can access data not only from other worksheets, but also from database tables.  This is also a fantastic achievement, getting data from multiple sources with different data structures.

I am about as pleased as can be. In fact, I am offering an additional course in BI and I have other courses undergoing development.  The pedagogy involved in the skills of Business Intelligence is being written in this decade, and the benefit of using an “Excel-friendly” tool in the classroom brings daylight to the mysterious area of “intelligence gathering” and how it is used in decision-making solutions.  For me, it is particularly exciting because it is the beginning of a thrilling direction in business education.

Next time:  Analytics in the Business Dean’s Office