Monday, January 30, 2012

Location Intelligence for Alternative Energy Smart Grids

Electrical utility corporations and location intelligence providers have long understood the usefulness of location intelligence to the generation, transmission and consumption of electrical power. The advent of alternative energy supplies and smart grids have made this connection even stronger.

A smart grid:
is a digitally enabled electrical grid that gathers, distributes, and acts on information about the behavior of all participants (suppliers and consumers) in order to improve the efficiency, importance, reliability, economics, and sustainability of electricity services (Wikipedia).
Although the term "smart grid" has been with us for a while, the reality has been slow to develop, largely because smart grid deployment is complex and capital-intensive. For example, one of the first deployments, the Telegestore project in Italy (completed in 2005) saves about 500 million Euros per year, but cost 2.1 billion Euros to deploy. As one of the first such deployments, they had to take responsibility for the design and manufacture of meters, the development of system software, and they had to act as their own system integrator (Wikipedia).

While the world lags in the development of smart grids, the growing popularity of, and need for, alternative energy sources adds a new wrinkle. It's one thing to manage the supply and demand of electrical power efficiently when you have complete control of the rate of generation, quite another when you're using wind and solar, and the wind doesn't blow and the sun doesn't shine.

Growing complexity calls for better ways to analyze data. Smart grids are all about location: where is the power generated? Where consumed? Consumption is obviously an important determinant of where energy should be generated, and alternative generation method, with their low environmental impact, are more amenable to demand-centered location. (NIMBY ‑ not-in-my-backyard ‑ syndrome is likely to be less pronounced then for, say, a nuclear power plant or a hydro-electric dam.)

A recent article in LBx Journal describes the collaboration between SolarReserve and NV Energy. Nevada (NV) Energy manages their smart grid using location intelligence, particularly for site selection, but also for "generating consistent reliable energy to the grid is a whole."

For upper management, location intelligence provides a means of visualizing all of the business intelligence that influences strategic decision making ‑ LI delivers a map of your customers and prospects, suppliers and competitors, assets and liabilities, challenges and opportunities, and your strengths and weaknesses.

For operations, it's all about knowing who is generating and consuming, where and when they are doing so, and how to make supply meet demand without waste.

For more information on location intelligence for utilities, view the recorded APOS webinar:
Location Intelligence: Energize Decision Making in Utilities

Thursday, January 26, 2012

Webinar: Well Managed BI with APOS COO Allan Pym

From time to time on this blog, I have offered definitions and illustrations for the concept of well managed BI (here and here and here and here and here). Today you can join APOS COO Allan Pym for a 45-minute webinar on that will answer the question: How . do you get from a curative (reactive) BI practice to a progressive (proactive) BI practice?

Allan will examine some of the BI platform management trends and issues facing organization today, and discusses strategies and best practices you can implement to establish a well managed SAP BusinessObjects deployment.

Register for the well managed BI webinar.


When Thursday, January 26, 2012, 2pm ET

Monday, January 23, 2012

Location Intelligence and the Kia Optima

Some time ago, we published a location intelligence white paper called "Whole Brain Analytics: The Science Behind Location Intelligence." In that white paper, I talked about the cognitive differences and complementarity between the right brain and the left brain, and noted that Mercedes-Benz had used this cognitive distinction in a highly original advertising campaign.

Now Kia has done something similar:


Similar, but the Mercedes-Benz effort was a print campaign, which allowed them to cater somewhat more to the left brain than a 30-second TV spot can:
Left brain: I am the left brain. I am a scientist. A mathematician. I love the familiar. I categorize. I am accurate. Linear. Analytical. Strategic. I am practical. Always in control. A master of words and language. Realistic. I calculate equations and play with numbers. I am order. I am logic. I know exactly who I am.
Right brain: I am the right brain. I am creativity. A free spirit. I am passion. Yearning. Sensuality. I am the sound of roaring laughter. I am taste. The feeling of sand beneath bare feet. I am movement. Vivid colors. I am the urge to paint on an empty canvas. I am boundless imagination. Art. Poetry. I sense. I feel. I am everything I wanted to be.



Posted by Tom Woodhead at 4:00 p.m.

Wednesday, January 18, 2012

Well Managed BI Whitepaper

Our newest whitepaper, "Well Managed BI: Managing Your BI Platform for ROI," is now available for download as a PDF on the APOS website.

The whitepaper presents a detailed look at the APOS Well Managed BI Capability Maturity Model (CMM). Learn how you can become a progressive BI practitioner.


Friday, January 6, 2012

SAP BI 4.0 - One of Top BI Stories of 2011

SearchBusinessAnalytics:
One of the biggest business intelligence (BI) software developments of 2011 was the debut of SAP BusinessObjects 4.0, the first major update to SAP AG’s flagship BI and analytics platform in more than three years. The new version is fully integrated with SAP’s enterprise information management products and offers an improved user interface, better mobility, social networking tools and the ability to analyze unstructured data, according to SAP.
BI 4.0 marks the first major update to BusinessObjects since its acquisition by SAP, and answers concerns about SAP's roadmap for business intelligence. The new release promises better integration and user experience, especially for enterprises running SAP solutions. It paves the way for enterprises to realize huge benefits with in-memory computing (HANA), as well as mobile and collaborative (StreamWork) BI.

Here's a summary of what's new in BI 4.0 (SP2), from SAP's documentation:
  • Extends the information infrastructure provided by earlier releases and integrates seamlessly with the existing product line.
  • Supports all deployment models and lets you fine tune administration and configuration of the entire system.
  • Brings together features from across the SAP BusinessObjects Business Intelligence Suite to meet your evolving reporting needs, from providing web access to Web Intelligence, to improving SAP Crystal Reports interactivity and personalization.
  • Facilitates migration from SAP BusinessObjects Enterprise 5.x and 6.x to SAP BusinessObjects Business Intelligence platform 4.0, however you need to migrate to Release XI 2.0 first.
  • Delivers new tools to drive user productivity and self-service reporting.
  • Delivers more reporting capability with fewer reports.
  • Includes a variety of major enhancements spread across our data access methods, administration capabilities, and report design options.

    Simplifies business monitoring with dashboard functionality and improved user experience.
  • Delivers the strongest self-service query and analysis solution for SAP customers.

Wednesday, January 4, 2012

Big Data Analytics Skills Shortage

A recent article at SearchBusinessAnalytics cited "raw and user-unfriendly technology" and lack of "skilled experts" in these technologies as the biggest challenges for large enterprises seeking the considerable benefits of big data analytics. As enterprises become more information driven, and business intelligence and analytics become critical to competitive advantage both strategically and operationally, there just aren't enough skilled personnel to handle the development of the needed predictive modeling and predictive analytics applications.

The greatest need is for more data scientists -- people who have post-graduate educations in statistical analysis. As demand grows, and supply remains relatively constant, individuals with these skills will command larger and larger portions of corporate business analytics budgets.

While this "crisis" seems worrisome, it is a problem that the average business intelligence platform manager would love to have. They would all like to be pushing the data analytics envelope to provide proactive and progressive solutions that meet or exceed their enterprises' information needs. Instead, these managers are dealing with smaller curative or preventive issues that won't go away, and which occupy altogether too much of their budget, and their resources' time.

The oldest (okay, maybe second oldest) service-type business proposition in the world goes something like this: If I can make (or save) you $50, will you pay me $5? In IT, such a proposition speaks to both return on investment (ROI) and total cost of ownership (TCO): you make back the money you invest in the service, and you save on the cost of operating the system.

That's the promise of APOS well managed BI solutions. You conserve the time of your resources, and you can move away from fixing and preventing problems, and toward providing progressive business intelligence solutions for your information consumers.