Recent Blog Posts

Amplify Your Value: Reap the Rewards!

Amplify Your Value.jpgAmplify Your Value and you can Reap the Rewards…that’s kind of the theme of this entire series…how you can amplify the value of your IT department and how your company can reap the rewards. But this post is not a summary of our journey, it is about the next step on our journey. It is a post about an organization moving head first into the cloud, moving head first into buy versus build, and moving head first into changing its operating model, deciding to develop its own loyalty card program and execute one of the most impact “IT Projects” in the 85 year history of our company. But…let me start at the beginning.


It was mid 2010 and I had just joined Goodwill Industries of Central Indiana as CIO. That first week, one of the meetings I had, in fact the first meeting with a peer VP, was with our VP of Marketing. That meeting covered a lot of ground and various topics. One that stood out for me was when she mentioned Goodwill had been discussing gift cards and loyalty cards for about eight or ten years but it never seemed to move forward. She even pulled out a folder that had enough of a thud factor to make any contract attorney jealous. It contained page after page of meeting minutes, email correspondence, and requirements. I was floored…eight years? Of talking? What was the roadblock?


A few days later, I was meeting with the VP of Retail. Again, we talked about a lot of different topics. Sure enough, the conversation soon rolled around to gift cards and loyalty cards. We’ve talking about it for eight years…and we’ve made no progress…eight years? Of talking? What was the roadblock?


That afternoon, I met with a couple of folks from my new staff. “What’s up with this gift card and loyalty card thing?”, I asked. Eight years? Of talking? What was the roadblock?


So, since this is my blog, I get to use my “bully pulpit” to air some dirty laundry and perhaps, according to who you ask, some revisionist history. It seemed, the problem was Marketing blamed Retail’s inability to define requirements, Retail blamed IT for always saying “no we can’t do that”, and IT blamed Marketing for want to discuss ad nauseum, but never move forward. I vowed, this was going to change. So in the midst of our Strategic Planning process, I called a meeting to discuss: gift cards and loyalty cards. After all, it was very near to my sweet spot…early in my career I had spent 12 years in banking, specifically in credit cards. 


As the year progressed, we began to define requirements and search commercial offerings for gift and loyalty cards. Within a few short months, the team decided to separate the project into two phases. Phase one would be gift cards and phase two would be loyalty cards. With that decision, the project kicked into high gear. Given our Point of Sale system and our requirements, we very quickly identified a gift card software provider. Within a few short months, we launched our gift card program.


Several weeks later, we reconvened our team of Marketing, Retail and IT to start on loyalty cards. We further defined our requirements. We wanted a random reward system, not a points based system, we wanted flexibility in the rewards offered, and most importantly, we wanted to track and drive two different behaviors on the same car: shopping and donating. Throughout the winter, we evaluated many off the shelf solutions. However, it was becoming readily apparent that no off the shelf solution was going to meet our requirements. Sure, they all offered flexibility in the rewards, but they were all based on earning points and none of them could track two different behaviors on the same card. Even taking that into consideration, the team was narrowing the selection down to a handful of packages that met at least some of the requirements.


I knew we had to build it. We had to deviate from our cloud-first, buy strategy and build it ourselves. There was no other way. With that in mind, we developed a response to the RFP we had issued. It was basically a general design document of what could be built. We submitted our “RFP Response” to the team along with the two or three commercial packages that had been down-selected. As selection day quickly approached, I made it a point to discuss the proposal in detail with the VP of Retail and the VP of Marketing. I could tell they were skeptical that IT could pull it off. I assured them we could, and quite frankly, played the “new guy card” and asked for a chance.


Our proposal was selected, now it was time to put up or shut up. We engaged with a local firm (Arete Software) to build the initial database and prototype and then shifted to the internal team. As we worked feverishly on the code, the project team defined the goals and the targets for success. The launch date would be November 11, 2011 (11/11/11); we would achieve an 11% increase in retail sales, our average shopping cart would increase by $5, and we would have 100,000 cardholders at the end of the first year.


Over the course of the summer and the fall, the team worked faithfully to hit the target date. Finally…go live…the organization that was moving head first into the cloud, moving head first into buy versus build, moving head first into changing its operating model, launched its loyalty card program…Goodwill Rewards (™).


Yes, we hit our target dates; yes, we hit our budget; but, how did we do on our goals? Our increase in retail sales was 13%, beating our target by 2%; our average shopping cart did improve, but fell short of our goal (our lessons learned review identified some areas for improvement here); and, we blew past the 100,000 cardholder mark in under six months, in fact, at the end of year one we had over a quarter of a million cardholders, today we have over 550,000 (remarkable, considering our geographic territory is 29 counties in Central Indiana…yes, 550,000 cardholders in just 29 counties in Indiana).


To further validate our success, we were awarded the Society of Information Management of Indiana’s Innovation of the Year award in 2012. Additionally, we licensed the software to a couple other Goodwill organizations in the US, turning us into, if not a profit generator, at least a revenue generator for the company.


How were we able to achieve this? First, it truly was a team effort. In fact, I believe one of the most important outcomes of this project was for Marketing, Retail and IT to work together, as a team, to achieve a common goal. Second, our path to amplify our value by leveraging cloud technologies and avoiding C-F Projects (see That Project is a Real Cluster!) enabled us to spend our energy on this A-C project. Third, the environment and culture enabled us to take a risk, to step into the unknown, to ask for and receive the support to move forward.


Next month, we will eliminate even more C-F Projects by looking at disaster recovery in: Amplify Your Value: A Tale of Two Recoveries.


The series, “Amplify Your Value” explores our five year plan to move from an ad hoc reactionary IT department to a Value-add revenue generating partner. #AmplifyYourValue


We could not have made this journey without the support of several partners, including, but not limited to: Bluelock, Level 3 (TWTelecom), Lifeline Data Centers, Netfor, and CDW. (mentions of partner companies should be considered my personal endorsement based on our experience and on our projects and should NOT be considered an endorsement by my company or its affiliates).


Jeffrey Ton is the SVP and Chief Information Officer for Goodwill Industries of Central Indiana, providing vision and leadership in the continued development and implementation of the enterprise-wide information technology and marketing portfolios, including applications, information & data management, infrastructure, security and telecommunications.


Find him on LinkedIn.

Follow him on Twitter (@jtongici)

Add him to your circles on Google+

Check out more of his posts on Intel’s IT Peer Network

Read more from Jeff on Rivers of Thought

Read more >

Improving User Experience through Big Data

Fig1.png

Enterprise IT users switch between a multitude of programs and devices on a daily basis. Inconsistencies between user interfaces can slow enterprise users’ productivity, as those users may enter the same information repeatedly or need to figure out what format to enter data (e.g. specifying an employee might be done with an employee number, a name, or an e-mail address).   On the application development side, code for user interfaces may be written over and over again.  One approach to solving these problems is to create a common User Experience (UX) framework that would facilitate discussion and the production of shareable interface templates and code.    Intel IT took the challenge to do just that, with the goals of increasing employee productivity by at least 25% and achieving 100% adoption.  To create that unified enterprise UX frame work, Big Data approaches were critical, as described in this white paper from IT@Intel.

 

To understand the requirements for the enterprise UX, two sources of data are available, but both have unique problems.  Traditional UX research methods like surveys, narratives, or observations, typically are unstructured and often do not have statistical significance. Usage data from logs have large volumes, and user privacy is at risk.  Unstructured data, varied data, and voluminous data are a perfect fit for Big Data techniques.   We used de-identification (aka anonymization) to hide the personal information of users.  De-identification techniques were combined with Big Data to create a Cloudera Hadoop based analysis platform shown to the right.  Fig2.png

 

Using that analysis platform, Intel IT’s UX team created a single framework standard for all enterprise solutions.  60% of Intel IT’s staff can take advantage of it.   Data from this platform was also used to select and implement a new internal social platform.  The analysis platform has also been used to analyze other aspects of user behavior, which we are planning to write about in a future IT@Intel white paper.

 

In addition to the white paper, more detail on the development of the UX framework can be found in the following papers:

 

Regarding our use of de-identification/anonymization, we talked about our early explorations in this white paper, and a more detailed analysis of the challenges of using de-identification in an enterprise setting our detailed in this conference paper:

Read more >

Malware Trend Continues its Relentless Climb

Malware development continues to remain healthy.  The Intel Security Group’s August 2015 McAfee Labs Threat Report shows malware quarterly growth at 12% for the second quarter of 2015.  In totality, the overall count of known unique malware samples has reached a mesmerizing 433 million. 

2015 Q3 Total Malware.jpg

Oddly, this has become a very stable trend.   For many years malware detection rates have remained relatively consistent at about ~50% increase annually. 

 

Which makes absolutely no sense! 

 

Cybersecurity is an industry of radical changes, volatile events, and chaotic metrics.  The growth of users, devices, data, new technologies, adaptive security controls, and dissimilar types of attacks differ each year.  Yet the numbers of malware being developed plods on with a consistent and predictable gain. 

 

What is going on?

 

Well colleagues, I believe we are witnessing a macro trend which incorporates the natural equilibrium occurring between symbiotic adversaries. 

 

Let me jump off topic for a moment.  Yes, cyber attackers and defenders have a symbiotic relationship.  There, I said it.  Without attacks, security would have no justification for existence.  Nobody would invest and most, if not all, security we have today would not exist.  Conversely, attackers do need security to keep their potential victims healthy, online, and valuable as targets.  Just as lions need a healthy herd to hunt, to avoid extinction, attackers need defenders to insure computing continues to grow and be more relevant.  If security was not present to hold everything together, attackers would decimate systems and in short order nobody would use them.  The herd would disappear.  So yes, a healthy electronic ecosystem has either a proper balance of both predator and prey, or a complete omission of both.

 

Back to this mind boggling trend.  I believe the steady growth of malware samples is a manifestation, at a high level, of the innumerable combined maneuvering of micro strategies and counter tactics.  As one group moves for an advantage, the other counters to ensure they are not defeated.  This continues on many fronts all the time.  No clear winner, but no complete loser either.  The players don’t consciously think this way, instead it is simply the nature of the symbiotic adversarial relationship.    

I have a Malware Theory and only time will tell if this turns into a law or dust.  My theory “malware rates will continue to steadily increase by 50% annually, regardless of the security or threat maneuvering” reflects the adversarial equilibrium which exists between attackers and defenders.  Only something staggering, which would profoundly upset the balance will change that rate.  If my theory is correct, we should break the half-billion mark in Q4 2015.

 

So I believe this trend is likely here to stay.  It also provides important insights to our crazy industry and why we are at this balance point.

 

Even in the face of new security technologies, innovative controls, and improved configurations, malware writers continue to invest in this method because it remains successful.  Malware continues to be the preferred method to control and manipulate systems, and access information.  It just works.  Attackers, if nothing else, are practical.  Why strive to develop elaborate methods when malware gets the job done?  (See my rants on path of least resistance for more on understanding the threats.) 

 

Defensive strategies are not slowing down malware growth.  This does not mean defensive tools and practices are worthless.  I suspect the innovation in security is keeping it in check somewhat, but not slowing it down enough to reduce the overall growth rates.  In fact, without continued investment we would likely be overrun.  We must remain vigilant in malware defense.

 

The rate increase is a reflection on the overall efficacy of security.  Malware must be generated at a rate of 150% per year, in order compensate for security intervention and achieve the desired success.  Flooding defenders is only one strategy as attackers are also demanding higher quality, feature rich, smarter, and more timely weapons.

 

Malware must land somewhere in order to operate and do its dirty deeds.  PC’s, tablets, phones, servers, cloud and VM hosting systems, and soon to be joined more prominently by droves of IoT devices, are all potential hosts.  Therefore, endpoints will continue to be heavily targeted and defense will continue to be hotly contested on this crucial battleground.  Ignore anyone who claims host based defenses are going away.  Just the opposite my friends.

 

At a rate of over three-hundred thousand new unique samples created per day, I speculate much of the malware is being generated automatically.  It is interesting on the defensive side, anti-malware companies are beginning to apply machine-learning, community reporting, and peer-validation to identify malicious code.  It is showing promise.  But just wait.  The malware writers can use the same type of machine-learning and community reporting to dynamically write code which either subverts detection or takes advantage of time delays in verification.  Malware code can quickly reinvent itself before it is verified and prosecuted.  This should be an interesting arms race.  Can the malware theory sustain?  Strangely, I suspect this battle, although potentially significant, may be exactly what the malware model anticipates.  The malware metronome ticks on.

 

 

Connect with me:

Twitter: @Matt_Rosenquist

Intel IT Peer Network: My Previous Posts

LinkedIn: http://linkedin.com/in/matthewrosenquist

Read more >

SmartGrid Security: Q&A with Bob Radvanosky, Co-Founder, Infracritical

Bob Radvanosky is one of the world’s leading cyber security experts, with more than two decades of experience designing IT security solutions for the utility, homeland security, healthcare, transportation, and nuclear power industries. The author of nine books on cyber … Read more >

The post SmartGrid Security: Q&A with Bob Radvanosky, Co-Founder, Infracritical appeared first on Grid Insights by Intel.

Read more >

How Wearables are Impacting Healthcare

Read Part I of this blog series on wearables in healthcare


As I mentioned in the first part of this blog series, wearables have become more than a passing trend and are truly changing the way people and organizations think about managing health. I hear from many companies and customers who want to understand how the wearables market is impacting patient care as well as some of the changes taking place with providers, insurers, and employers. In the next several blogs, I’ll share some of their questions and my responses. Today’s question is:

 

What are some of the ways that wearables are impacting providers, payers, and employers as well as patients?

 

For providers, one example is a pilot that the Mayo Clinic did with Fitbit to track patients recovering from cardiac surgery. They were able to predict which of those patients would be discharged sooner than others based on their activity in the hospital. You can easily see how this use case could be extended outside of the hospital, where you might be able to use wearables to more accurately predict which patients are at the highest risk for hospital readmission. This of course is a key quality metric that hospitals are incentivized to reduce.

 

On the payer side, organizations are using wearable devices to influence the behavior of their members, encourage a healthier lifestyle, and delay the onset of conditions like obesity and diabetes. Cigna has a program for their own employees where they identify individuals who may be at risk for diabetes. They created a wearables program that encouraged increased activity in those individuals’ daily lives, and it’s making a difference.

 

Gartner finds that over 2,000 corporate wellness programs have integrated wearables to track employees’ physical activity and incentivize them, sometimes financially, to have a healthier lifestyle. BP rolled out a program with 14,000 employees. Those who were able to achieve 1 million steps (equivalent to roughly 500 miles for an average-size person) over the course of a one year period received a health plan premium reduction the following year.

 

Now, has anybody been able to aggregate enough wearable data for some serious predictive analytics, or is that down the road? I think that’s down the road; certainly before it becomes mainstream. This will entail significant data integration and big data analytics. We’re looking to pull in multi-structured data from multiple distributed entities and repositories – data from electronic health records, health insurance claims, in some cases socioeconomic data, and all the new sensor data from wearables. If we can pull the continuous stream of patient-generated data into a repository, and overlay more traditional payer and provider data, I suspect the accuracy of predictive models will be significantly improved. We’ll be much better able to identify high-risk patients that will benefit most from additional outreach by a provider organization.

 

What questions do you have?

 

In my next blog, I’ll look at the primary challenges companies are facing in collecting, analyzing, and sharing data generated by wearables.

Read more >

Intel Donates HPC Infrastructure to Pan-Cancer Analysis of Whole Genomes Project

We’re experiencing ever-increasing volumes of data within health and life sciences. If we were to sequence just once the ~14M new cancer patients (T/N) worldwide[1], it would require more than 5.6 Exabytes (and the reality is we need to be able to sequence them multiple times during the course of treatment using a variety of omics and analytics approaches). The technical challenges of big data are many, from how do we manage and store such large volumes of data to being able to analyse hugely complex datasets. However, we must meet these challenges head-on as the rewards are very real.

 

I’m pleased to tell you about a significant project that Intel is supporting to help overcome these types of challenges which will assist in the drive to comprehensively analyse cancer genomes. Our HPC solutions are already facilitating organisations around the world to deliver better healthcare and individuals to overcome diseases such as cancer. And our relationship with the Pan-Cancer Analysis of Whole Genomes (PCAWG) project is helping scientists to access and share analysis of more than 2,600 whole human genomes (5200 matched Tumor/Normal pairs).

 

Scientific discovery can no longer operate in isolation – there is an imperative to collaborate internationally working across petabytes of data and statistically significant patient cohorts. The PCAWG project is turning to the cloud to enhance access for all which will bring significant advances in healthcare through collaborative research.

 

By working directly with industry experts to accelerate cancer research and treatment, Intel is at the forefront of the emerging field of precision medicine. Advanced biomarkers, predictive analytics and patient stratification, therapeutic treatments tailored to an individual’s molecular profile, these hallmarks of precision medicine are undergoing rapid translation from research into clinical practice. Intel HPC Big Data/Analytics technologies support high-throughput genomics research while delivering low-latency clinical results. Clinicians together with patients formulate individualized treatment plans, informed with the latest scientific understanding.

 

For example, Intel HPC technology will accelerate the work of bioinformaticists and biologists at the German Cancer Research Centre (DKFZ) and the European Molecular Biology Laboratory (EMBL), allowing these organisations to share complex datasets more efficiently. Intel, Fujitsu, and SAP are helping to build the infrastructure and provide expertise to turn this complex challenge into reality.

 

The PCAWG project is in its second phase which began with the uploading of genomic data to seven academic computer centres, creating what is in essence a super-cloud of genomic information. Currently, this ‘academic community cloud’ is analysing data to identify genetic variants, including cancer-specific mutations. And I’m really excited to see where the next phase takes us as our technology will help over 700 ICGC scientists worldwide to remotely access this huge dataset, performing secondary analysis to gain insight into their own specific cancer research projects.

 

This is truly ground-breaking work made possible by a combination of great scientists utilising the latest high-performance big data technologies to deliver life-changing work. At Intel it gives us great satisfaction to know that we are playing a part in furthering knowledge in both the wider genomics field, but also specifically in better understanding cancer which will lead to more effective treatments for everyone.

 

 


[1] http://www.cancerresearchuk.org/cancer-info/cancerstats/world/incidence/

Read more >

In Their Own Words: Intel Intern Juan Lopez Marcano Shares His Story

Juan Lopez Marcano was an Intel Scholar with the Platform Engineering group during the summer of 2015. He is currently earning a Master’s Degree in Electrical and Electronics Engineering at Virginia Polytechnic Institute and State University. If I could describe … Read more >

The post In Their Own Words: Intel Intern Juan Lopez Marcano Shares His Story appeared first on Jobs@Intel Blog.

Read more >