No more ‘army of one’ with Big Data accountability revolution | #MITIQ

091013-A-7540H-016At this week’s MIT CDOIQ Symposium, held in Cambridge, Massachusetts, you wouldn’t have been faulted for recognizing that two industries that have embraced the Big Data revolution are healthcare and the financial sector. The benefits of employing analytics models to these fields are more and more apparent. You might be surprised, however, to learn of one particular public sector player that is seeking an operational advantage via Big Data: the Department of Defense.

Mort Anvari, Director of Programs and Strategy within the Deputy Assistant Secretary of the Army’s Cost and Economics division, has overseen the creation and implementation of directives aimed at the cost culture and cost management of the US Army.

“Private industry is easier because everyone is cost conscious,” Anvari explains. “In government, particularly during a war, that mission is driving everything. Most of our officers are only concerned with how much money they need and how they spend it.” Anvari admits that his task of directing commanders to accede to a cost culture mindset was a pretty big deal. “We had to look at it from the people’s perspective. That includes convincing leadership that attention to cost doesn’t create a bad image for the country.” The main argument centered on the perception that being cost conscious could appear to be putting our servicemembers unnecessarily into greater harm’s way.


Surviving the Culture Clash

Anvari claims an early success with the education of commanders and other officers that paying special attention to cost and soldier safety were not mutually exclusive. “You can be cost conscious. You can do more with your resources. You can be more efficient with it and still care about safety and care about the soldiers.”

With projects budgeted above $10 million, an automatic cost/benefit analysis is enacted. Anvari oversees more than 2,000 Army analysts who perform and validate each of these. Knowing the process, commanders will typically consider an additional course of action to what they submit for review. “Talking to commanders and leadership, we ask ‘What is your information need?’,” he stated. “Based on that, we develop a data need for that organization.”

Similar to challenges faced in the private sector, one of the issues overcome by the Army was convincing certain organizations that possessed data to share that property with other organizations. “Communicating the data need from organization A to organization B, telling organization B you need to provide this data that is not for you, it’s for someone else,” Anvari said, “that was a big culture shock.”

However, in explaining the funding structure for the military like an upside down tree, Anvari was able to bring an understanding that all funding came from the top and spread out to all of the “branches” within the Army. “We call it fund centers. They have all the money. The cost centers are the ones using this money. It could be them or it could be others. It’s truly like a neural network of information.”

Unlike private sector companies, the Army realized they had to streamline their budgeting and allocation process due to the fact they are subjected to strict oversight by the Congress. As all of the funding is taxpayer monies, citizens are also privy to the budgeting process through the use of Freedom of Information Act requests.

As noted above, the cost-benefit analysis process is automatic on projects in excess of $10 million. However, Anvari notes that projects under that threshold, undertaken by commanders of smaller outfits, are pretty well self-monitored because those commanders want to show that they are capable of critically applying the new cost culture analysis in the hopes they will be promoted to heading up larger projects in the future.

“Accountability is hard to swallow,” says Anvari, with regard to the early push back from Army leadership, “no matter how normalized the process is.” Anvari’s work is seeing results, however. “Cost management is on its feet and working,” he concluded.

(Originally published at

photo credit: The U.S. Army via photopin cc

Making Medical Data Better Data

large_2956265250In just over a week, the team here at SiliconANGLE will be setting off for Cambridge, Massachusetts for the 7th Annual MIT Chief Data Officer and Information Quality Symposium held on the MIT campus. The theme this year is ‘Big Data Demands Good Data’. In preparation for the event, we will be presenting a synopsis of some of the important topics scheduled to be covered in conjunction with other academic and real-world applications that apply.

One of the first sessions, to be presented by Dr. David Levine, Vice President of Informatics/Medical Director of Comparative Data and Informatics for United Healthcare, will address the need for improving risk models based on predictive analytics.  According to the abstract of Dr. Levine’s presentation, he will discuss how the advent of and improvements in data collection can be utilized to drive improved performance in health administration and patient care.

Writing recently for FierceHealthIT, Dan Bowman discussed how a recent survey of hospital CIOs found big data in the medical field was severely lacking in its efficacy. Bowman cites a healthsystemCIO.comsurvey in which 76 percent of respondents claimed their vendors were too often over-promising and under-delivering with their big data solutions.

In the same survey, it was found a full 52 percent of respondents admitting to not using their big data applications at anything approaching any level of sophistication. This figure is supported by the fact two-thirds of those who took the survey claimed their organization had neither the manpower nor the skill to take advantage of analytical tools at a high level. Each of these factor into one CIO stating the big data market, as it pertains to healthcare, isn’t likely to reach maturity for at least a few more years.

The challenge, it appears, is for the healthcare field to better understand the mountains of data they collect and learn how to better pore over it to help in establishing better predictive models for patient care and hospital administration. According to Chris Belmont, CIO at New Orleans’ Ochsner Health System, “We have the data points. We just have to do a better job of getting our hands around the data and understanding it better.”

What is the real-world benefit of achieving an optimal understanding and usage of data in the medical field though? Jeff Kelly of discussed the necessity of improving the collection and analysis of big data for those fields represented in the Industrial Internet in a posting entitled ‘The Industrial Internet and Big Data Analytics: Opportunities and Challenges’. Shockingly, he stated as much as 43 percent of an estimated $2.75 trillion in healthcare spending (for 2012 alone) was applied to unnecessary procedures and administrative waste. That abhorrent figure will be significantly reduced as the Industrial Internet is increasingly utilized by hospital CIOs to target administrative inefficiencies, eliminate waste and improve patient outcomes.

Dr. Levine’s presentation seems to aim at addressing the better utilization of data for improved patient outcomes. His work with United Healthcare, in tandem with their membership organizations, is striving to make predictive models more meaningful and actionable with the aim toward driving improved performance.

photo credit: Funky64 ( via photopin cc

(Originally published at