Posts

Noetix and Qlik: Oracle EBS Reporting for QlikView Users

QlikView customers that wish to leverage the power of business discovery and natural analytics on data from Oracle E-Business Suite would need to write complex QlikView Load Script that is beyond the capability of many end-users, creating a technical resource bottleneck. Read more

Noetix Customer Tempel Wins Manufacturing Leadership Award

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Noetix customer Tempel has been awarded the prestigious Manufacturing Leadership Award in the project category of Enterprise Technology Leadership. Read more

Will Companies Ever Have the Ability to Measure BI Performance?

In January, we posted a quick poll question: “How much has your BI deployment contributed to your company’s success?”  Most companies embark upon a business intelligence initiative in order to improve the quality of business decisions, resulting in a positive impact on costs and revenue.  However, measuring that correlation is often difficult, if not impossible.  As part of the poll question, we offered answers that spoke to hunches: “Not at all”; “Slightly”; “Somewhat” or “Significantly”.  The top answer to that poll question was: Slightly. Read more

Executive Q & A with Thomas Casselberry, Sr. Director, Product Development

As the senior director for product development at Noetix, where do you see opportunities for innovation within BI products?

The biggest areas in which I see opportunities for innovation are: Broader and better support for heterogeneous data sources, embracing the mobile user base regardless of on-premise or cloud-based deployment, more predictive analytics that are geared toward real-time decision making, addressing the ever growing need to include social media, and even making devices we use and rely on today smarter through the use of BI. Imagine appliances that are semi-self aware and can inform you of pending maintenance and provide information about how they’re used, cars that can let you know of upcoming traffic, adverse road conditions, impending storms, etc. And even toys that will interact with and help educate our children in real-time. The primary point is that we’re headed for another information explosion where even the everyday users of systems will be provided with, and the beneficiaries of, analytics done across vast pockets of information. The innovations surrounding the use of what’s called ‘Big Data’ today are small and will pale in comparison to the many innovations in the areas that I’ve listed. Rest assured that every innovation we see between now and then will itself lead to even more opportunities. It’s an exciting time to be in the BI space. Read more

Developing a BI Strategy: Define Your BI Goals and Metrics

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

Business Intelligence remains high on the corporate IT agenda despite the current economic environment. In spite of the complexity of measuring the size of the BI market, analysts agree that it has been growing at a rate of at least 10 percent or more for the past three years. Read more

Determining Scope is a Top Challenge in Bringing BI Applications into Production – Research Study of 250 IT Professionals

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

Business intelligence infrastructures are dynamic. As companies generate new information, they need to apply that information productively to business processes. Sometimes that requires devising new kinds of analyses. Sometimes it means pushing information to new communities of users. Read more

Developing Analytic Applications is a Collaborative Process – Research Study of 250 IT Professionals

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

In many organizations, the IT department has the responsibility and the expertise to explore, develop, and install most major applications, as well as identify technology that can support an organization’s mission. While senior management must sign off on any significant new project, the IT group takes on the burden of such initiatives.

However, the process of identifying, developing, and implementing analytic applications is a much more collaborative process according to a research study conducted by the Lattanze Center, a nationally recognized center of excellence on issues related to business excellence and IT at Loyola University Maryland. To an overwhelming degree, IT professionals and end users work together to select and develop analytic applications.

In a survey of more than 250 IT professionals who indicated that analytic applications were used in their organizations:

  • 71% reported that selecting analytic applications was a joint decision made by IT and end users
  • 10% said that IT alone chose analytic applications
  • 5% indicated that end users alone selected analytic applications

The same pattern of collaboration held true for developing analytic applications. Among the respondents to the survey:

  • 56% said that IT professionals and end users work together to develop analytic applications
  • 24% reported that IT professionals alone created analytic applications
  • 9% indicated that consultants were responsible for developing analytic applications
  • 4% said that end users were entirely responsible for developing analytic applications

This data suggests that in many organizations end users do not have sufficient technical skill to build applications without assistance, nor are they empowered to select analytic applications entirely on their own.

On the other hand, end users do routinely collaborate on both the selection and development of analytic applications. The reason is not hard to determine. Analysis is a quintessential “ground up” activity. End users know what data they need and how they want to analyze it, while IT can identify and suggest new tools that could be potentially useful.

To a degree, the level of cooperation between end users and IT during the development process declines. While end users simply may not have the technical skills needed to assist in development, a high degree of interaction is needed to ensure the analytic tools selected, developed, and implemented can generate data and lead to the answers the end users want.

Stay tuned for part three of this series in the July/August 2011 issue of the Noetix Newsletter! We will take a look at the amount of time it takes for an organization to go from the decision to create a new analytic application, to having the application operational, including the biggest challenges found along the way.

Customization Plays Key Role in Analytic Application Development – Research Study of 250 IT Professionals

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

The production and retention of data within organizations has grown on an exponential curve for at least the past decade. All that data jamming up companies’ storage infrastructures can be virtually useless if people can’t extract actionable information from it. The amount of data a company collects is not nearly as important as what it does with that data. Read more

Establishing the Business Need for New Analytical Applications

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

Building a culture of analysis is an ongoing process for most organizations. As companies generate more data, the need to access and analyze data to measure and monitor performance and identify trends is no longer the sole domain of business analysts and senior executives. Line managers and customer-facing personnel can also take advantage of better data access and an opportunity to understand that data more fully.

However, developing and deploying analytic applications can be time-consuming and expensive. Custom-built analytic applications often take months to build, demanding a significant investment of money and resources. In many cases, companies don’t build these applications from scratch but customize packaged applications to a greater or lesser degree. (See post, Customization Plays Key Role in Analytic Application Development).

How should a company determine where to put resources to expand the number of analytical tools available to their employees? The wrong way to go about that decision is to try to oil the squeaky wheel. In every organization, there are business groups that voice their needs with more urgency than others. Responding to them is easy but not always the right choice.

The right approach is to establish the business need and business case for the proposed application, which requires answering four questions:

  • What is the current pain point? In other words, what is the business group not able to do that better access to data and analysis would allow it to do? Can the HR department produce accurate employee counts on a regular basis?
  • What business goal would be achieved by implementing the new application? Can the business benefit of having an accurate head count be quantified in some way?
  • Can you access the data you need to make the analysis in a cost-effective way?
  • How long would it take to create and deploy the application needed?

As requests for new kinds of data percolate up (and down), it is important to formulate a methodology to prioritize those requests. By asking the right questions and collecting the right information, the right answers will become clear.