Author Archives: Reid Wegley

We’ve talked a lot about how big data is being used within industries such as banking and healthcare – but we’re equally fascinated to see how big data is collected and analyzed by other industries. Energy-related companies are creating and deploying big data based projects that are accomplishing everything from the creation of a more intuitive smart grid to helping homeowners be more energy efficient.

The energy sector’s data management issues are the same as those experienced by other industries. Utilities are looking for measurement and analytics systems that enable them to tap real-time information and to use it to take appropriate actions to avoid shortages. Here’s one example: 10 years ago, a real-time measurement system that could provide data from multiple points on the energy grid to avoid a blackout was a pipedream. That’s why, in 2003, the U.S. experienced a massive blackout affecting more than 50 million people in the Northeast and Midwest and even into Canada.

Fast forward to 2013. Today, we have phasor measurement units (PMUs) in place that measure electrical waves on a grid. PMUs are essential components of a smart grid monitoring system, and more than 150 are already installed and running. The first deployment was right in our area at the Bonneville Power Administration, which provides 35 percent of the power in the Pacific Northwest. It established a Wide Area Management System in 2000 to rapidly transfer and digest data collected from PMUs in real-time, enabling it to improve power flow over the grid and minimize power disruptions to consumers.

It’s easy to see how big data algorithms are helping utilities crunch the data from PMUs to learn from the smart grid; however, a massive amount of data is now becoming available to utility companies via homes with smart meters. In a survey conducted by Oracle:

• smart meters were delivering information on outages (78 percent), voltage usage (73 percent), tampering (63 percent) and diagnostics (56 percent).
• responding utility companies see a need to improve their ability to take this information and turn it into actionable intelligence; 64 percent of utilities said it was one of their top three priorities

On the downside, the survey also pinpointed that utilities are still struggling to deal with the mountain of information now at their fingertips; they only rate themselves as 6.7 on a scale of 10 in preparedness, and 50 percent say they have missed opportunities to deliver useful information to customers.

As progress is made in this area, generated data will play a crucial role in tightening smart grid operations. One day in the very near future, real-time data crunching will make the grid self-healing, needing far less hands-on maintenance, reducing disruptions due to weather and safeguarding resources for the future.

The Alacer Group is currently working on a project dealing with big data and energy systems. Watch for more information in the coming months.

by Ed Sarausad

On Saturday, Richard Paxton and I will be guest lecturers at the University of Washington – Bothell to talk about how process analytics can be better utilized in the healthcare setting, particularly when it comes to redesigning processes based on Lean principles.

We’ve talked and written on this topic in the past, most recently in Richard’s blog post. Hospitals and healthcare facilities typically have a lot of structured and unstructured data available that can be used to build a process flow model. The beauty of a model is that it allows operational changes to be tested, observed and fully optimized before they are actually instituted within the facility. This is an important benefit, since model testing minimizes the impact change has on patients and medical personnel.

We’ll be discussing this and other related tools, such as Value Stream Mapping IGrafx.

We’re also talking for the first time about a new project we’re initiating with UW School of Business grad students that involves using a mobile application to collect and validate data that impacts customer satisfaction within the healthcare setting.

The program is being held Saturday, October 12 at 10:00 a.m. at the North Creek Events Center, University of Washington – Bothell campus.

 Ed Sarausad

In today’s economic world, financial organizations are struggling to remain profitable when escalating costs are the norm.  Design for Six Sigma (DFSS) is one way to bridge the gap between profitability and cumbersome processes, often legacy ones, that no longer operate at peak efficiency.

Lean Six Sigma has been used within the financial community for more than a decade, particularly in the area of continuous process improvement.  It is still a popular and effective tool to improve financial services operational efficiency; however, many organizations are finding that identifying and reducing incremental defect variability does not fully maximize the full spectrum of improvement opportunities. To achieve a larger return on investment, many organizations are discovering how DFSS can help them re-examine, radically recreate and often build entirely new processes.

DFSS is a separate and emerging business process management methodology (process generation rather than process improvement) that helps organizations determine its customers’ needs and to use that information to create a solution.  These techniques include tools and processes to predict, model and simulate the product delivery system (the processes/tools, personnel and organization, training, facilities, and logistics to produce the product/service) as well as the analysis of the developing system life cycle itself.

Financial organizations rely on a complex network of interrelated processes and systems to deliver quality products and services for their customers.  New levels of performance and quality can be achieved using DFSS tools to take an end-to-end view and create a new design that crosses existing functional boundaries.

Case in point: we worked with a national bank with thousands of branches across the U.S. to solve its increasing Suspicious Activity Report (SAR) workload.  While SARs play a significant role in reducing the country’s vulnerability to terrorist threats by identifying potentially fraudulent activities, the process was causing an increased financial burden on the financial organization.  Specifically, the bank was experiencing an unanticipated related cost of $40 million in vendor and contracting expenses.

Alacer partnered with existing bank vendors to develop a multiphase approach that focused on expense controls, end-to-end process reviews and the identification of high variability areas.  Using DFSS principles, Alacer developed new processing and staffing models to address work backlog and to mitigate operational impact.  As a result, the bank realized $36 million in savings over three years, and $16 million in savings through vendor contract reductions.  The result outperformed regulatory expectations and was designated “Best in Class” by government agencies.

Going forward, DFSS principles can help future-proof banking systems.  While sales, fulfillment and service functions will remain the same, what will differentiate a financial institution will be the way it delivers the products and services customers want, in the way they want it and at a level of efficiency that makes sense for the business. When used in conventional and unconventional ways, DFSS can help organizations deliver this value to customers and, simultaneously, increase the bottom line.

For more information, check out our new white paper, “Design for Six Sigma Drives Increased Revenue for Financial Services Firms.”

 by Richard Paxton