Xentity recognized on CIO Review list for Most Promising Government Technology Solution and Consulting Providers 2013

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Matt Tricomi

Xentity was recognized on CIO Review list for “20 Most Promising Government Technology Solution and Consulting Providers 2013” list. 

With the advent of internet technologies, there has been a change in the landscape of business processes related to the Federal Government system. But the change hasn’t been easy as it requires constant dedication to move the entire workforce from traditional systems, and getting them to seamlessly adapt to the modern systems. This transition also includes the role of technology consulting providers, whose sole responsibility is to provide a wide spectrum of services in order to help the federal agencies to cope with the changes, in the best possible manner.

As customers and business partners increasingly demand greater empowerment, it is imminent for government companies to seek for improved interactions and relationships in their entire business ecosystems, by enhancing software capabilities for collaboration, gaining deeper customer and market insight and improving process management.

In the last few months, we have looked at hundreds of solution providers and consulting companies, and shortlisted the ones that are at the forefront of tackling challenges related to government industry.

In our selection we looked at the vendor’s capability to fulfill the needs of government companies through the supply of a variety of services that support core business processes of all government verticals, including innovation areas related to advanced technologies and smart customer management. We also looked at the service providers’ capabilities related to the deployment of cloud, Big Data and analytics, mobility, and social media in the specific context of the government business.

We also evaluated the vendors support for government bridging the gap between IT and Operations Technology. We present to you, CIOReview’s 20 Most Promising Government Technology Solution and Consulting Providers 2013.

CIO Review Magazine Full Article on Xentity:

Xentity Corporation: Rapidly Designing The Needed Change In Cost-Cutting Times

By Benita M
Friday, December 6, 2013

 

Benita M

“We always try to believe that leaders want to execute positive change and can overcome the broken system. We are just that naïve,” says Matt Tricomi, Founder of Xentity Corporation in Golden, CO, named for “change your entity” which started on this premise just after 9/11 in 2001.“This desire started in 1999. I was lucky enough to be solution architect on the award winning re-architecture of united.com. It was a major revenue shift from paper to e-ticket, but the rollout included introducing kiosks to airports. Now that was both simple and impactful”. Xentity found their niche in providing these types of transformation in information lifecycle solutions. Xentity started slow, first, in providing embedded CIO and Chief Architect leadership for medium to large commercial organizations. 

Xentity progressed, in 2003, into supporting Federal Government and soon thereafter International to help IT move from the 40-year old cost center model to where the commercial world had successfully transitioned – to a service center. “Our first Federal engagement was serendipitous. Our staff was core support on the Department of the Interior (DOI) Enterprise Architecture team”, Matt recalls on how the program went from “worst to first” after over $65 million in cuts. “We wanted to help turn architecture on its head by focusing on business areas, mission, or segments at a time, rather than attack the entire enterprise from an IT first perspective.” The business transformation approach developed ultimately resulted in being adopted as the centerpiece or core to the OMB Federal Segment Architecture Methodology (FSAM) in 2008.

Xentity focuses on the rapid and strategic design, planning and transformation outreach portion of the technology investment in programs or CIO services. This upfront portion is generally 5 to 10 percent of overall IT spending. Xentity helps address the near-term cost-cutting need while introducing the right multi-year operating concepts and shifts which take advantage of disruptions like Geospatial, Cloud, Big Data, Data Supply Chain, Visualization, and Knowledge Transfer. Xentity helped data.gov overcome eighty percent in budget cut this way. “Healthcare.gov is an unfortunate classic example. If acquisition teams had access to experts to help register risks early on, the procurement could have increased the technically acceptable threshold for success.” 

One success story of Xentity is at United States Geological Survey (USGS). “After completing the DOI Geospatial Services Blueprint, one of several, the first program to be addressed was the largest: USGS National Mapping Program.” This very respected and proud 125-year old program had just been through major reductions in force, and was just trying to catch its breath. “The nation needs this program. The blueprint cited studies in which spending $1 on common “geo” data can spur $8 to $16 in economic development. Google Maps is one of thousands which use this data.” The challenge was to transition a paper map production program to be a data product and delivery services provider. “The effort affected program planning, data lifecycle, new delivery and service models, and road-mapping the technology and human resource plan. We did architecture, PMO, governance, planning, BPR, branding, etc.” Xentity, with its respected TV production capability, even supported high-gloss video production to deal with travel reduction and support communicating the program value and changes with partners and the new administration. This is definitely different than most technology firms. The National Map got back on the radar, increased usage significantly, and is expanding into more needed open data. 

Presently, Xentity is a certified 8(a) small disadvantaged business with multiple GSA Schedules and GWACs (Government Wide Acquisition Contracts). Xentity invested heavily in Federal Business management. Part of providing innovative, pragmatic, and rapid architecture and embedding talent is being able to respond quickly with compliant business management vehicles. Xentity is constantly seeking out the passionate CIOs, Program Directors, Architects, and Managers looking at transformation in this cost-cutting environment. “Sequester, Fiscal Cliff, debt ceiling, continuing resolutions–it’s all tying the hands of the executives who can look at best six months out. They don’t have the time to both re-budget and rapidly design multi-year scenarios to out-year performance drivers and options let alone staff up to speed on the latest disruptions or right innovation. That is where we come in. We start small or as fast or slow as the executive wants or believes their organization can absorb and progress.” 

To do BigData, address Data Quality – People and Processes – Tech Access to information

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As a follow on to the “cliffhanger” on BigData is a big deal because it can help answer questions fast, there are three top limitations right now: Data Quality, People and Process, Tech Access to Information. 

Lets jump right in.

Number One and by far the biggest – Data Quality

Climate Change isn’t a myth, but it is the first science to ever be presented on a data premise. And in doing so, they prematurely presented models that didn’t take into account the driving variables. Their models have changed over and over again. Their resolution of source data has increased. Their simulations on top of simulations have proven countless theories of various models that can only be demonstrated simply by Hollywood blockblusters. Point being, we are dealing with inferior data for a world scale problem, and we jump into the political, emotional driven world with a data report? We will be the frog in slowly warming water, and we will hit that boiling point late. All because we started with a data justification approach using low quality data. Are they right the world is warming? Yes. Do they have enough data to proven the right mitigation, mediation, or policy adjustments? No, and not until either we increase the data quality or take a non-data tact.

People and processes is a generation away.

Our processes in IT have been driven by Defense and GSA business models from the fifties. Put anyone managing 0s and 1s technology in the back. They are nerds, look goofy, can’t talk, don’t understand what we actually do here and by the way, they smell funny. That has been the approach to IT since the 50s – nothing has changed with the exception that their are a few bakers dozen of the hoodie wearing, mountain dew drinking, late night owls who happen to be loaded now, and their is a pseudo culture of geek chic. We have not matured our people talent investment to balance maturity of service, data, governance, design, and product lifecycle to embrace that engine culture as core to the business. This means, more effective information sharing processes to get the right information to the right people. This also means, investing in the right skills – not just feeding doritos and free soda to hackers – to manage the information sharing and data lifecycle. I am not as worried about this one. As the baby boomer generation retires, it will leave a massive vacuum as Generation X is too small and we’ll have to groom Generation Y fast. That said, we will mess up a lot missing a lot of brain drain, but market will demand relevancy which will, albeit slowly, create this workforce model in 10-15 years.

Access to Environments 

If you asked this pre-hosting environments or pre-cloud, this would have been limited to massive corporations, defense, intel, and some of the academia co-investing with those groups. If you can manage the strain of shifting to a big data infrastructure, this barrier should be the least of your problems. If you can allow your staff to get the data they need at the speed they need so they can process in parallelization without long wait times, you are looking good. Get a credit card, or if Government, buy off a Cloud GWAC, and get your governance and policies moving, as they are likely behind and not ready. Likely they will prolong the silo’d information phenomenon. Focus on the I in IT, and let the CTO respond to the technology stack. 

Focus on data quality, have a workforce investment plan, and continue working your information access policies

The tipping point that move you into Big Data is where these combined require you to deal with the complicated enormity at speeds answering questions not just for MIS and reports, but to help answer questions. If you can focus on those things in that order (likely solving in reverse), you will be able to implement parallelization of data discovery.

This will shorten the distance from A to B and create new economies, new networks, and enable your customer or user base to do things they could not before. It is the train, plane, and automobile factor all over again.

And to throw the shameless plug in, this is what we do. This is Why we focus on spatial data science and Why is change so fundamental.

BigData is a big deal because it can help answer questions fast

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BigData is not just size and speed of complex data – it is moving us from information to knowledge

 

As our Why we focus on spatial data science article discusses, the progress of knowledge fields – history to math to engineering to science and to philosophy – or the individual pursuit of knowledge is based on moving from experiments to hypotheses to computation to now The Fourth Paradigm: Data-Intensive Scientific Discovery. This progression has happened over the course of human history and is now abstracting itself on the internet.

The early 90s web was about content, history, and experiments. The late 90s web was about transactions, security and eCommerce. The 2000s web was about engineering entities breaking silos – within companies, organizations, sectors, and communities. The 2010s web has been about increasing collaborating of communication, work production, and entering into knowledge collaboration. The internet progression is just emulating human history capability development.

When you are ready to move into BigData, it means you are wanting to Answer new questions.

That said, The BigData phenomenom is not about the input of all the raw data and explosion that the Internet of Things is being touted as. The resource sells, and the end product is the consumed byproduct. So lets focus on that by-product – its knowledge. Its not the speed of massive amounts of new complex and various quality data as our discussion on IBM’s 4 V’s focus on.

Its about what we can do with the technology on the cheap that before required supercomputer clusters that only the big boys had. Now with cloud, internet, and enough standards, if we have good and improving data, we ALL now have the environment to be answering complicated questions while sifting through the noise. Its about the enablement of the initial phase of knowledge discovery that everyone is complaining about the “web” right now “too much information” or “drowning in data”.

The article on Throwing a Lifeline to Scientists Drowning in Data discusses how we need to be able to “sift through the noise” and make search faster. That is the roadblock, the tall pole in the tent, the showstopper.

Parallelizing the search is the killer app – this is the Big Deal, we should call it BigSearch

If you have to search billions of records and map them to another billion records, doing that in sequence is the problem. You need to shorten the time it takes to sift through the noise. That is why Google became an amazing success out of nowhere. They did and are currently doing it better than anyone else – sifting through the noise.

The United States amazing growth is because of two things – we have resources and we found out how to get to them faster. Each growth phase of the United states was based on that fact alone, and a bit of stopping the barbarians at the gates our ourselves from implosion. You could say civilization. Some softball examples out of hundreds

  • Expanding West dramatically exploded after trains, which allowed for regional foraging and mining
  • Manufacturing dramatically exploded production output, which allowed for city growth
  • Engines shortened time between towns and cities, which allowed for job explosion
  • Highway systems shortened time between large cities, which allowed for regional economies
  • Airplanes shorten time between the legacy railroad time zones, which allowed for national economies
  • Internet shortened access to national resources internationally, which allowed for international economies
  • Computing shortened processing time of information, which allows for micro-targetted economies worldwide

Each “age” resulted in shortening the distance from A to B.  But, Google is sifting through data. Scientists are trying to sift as well through defined data sensors, link them together and ask very targetted simulated or modeled questions. We need to address the barriers limiting entities success to do this. 

 

When you are ready to move into BigData, it means you are wanting to Answer new questions.

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The article on Throwing a Lifeline to Scientists Drowning in Data discusses how we need to be able to “sift through the noise” to be able this faster and faster deluge of sensors and feeds. Its not amount information management models of fast, large retail or defense data. It is about finding the signals you need to know to take advantage.

In controlled environments, like retail and business, this has been done for years on end to guide business analytics and targeted micro-actions. 

For instance, gambling industries have been doing this for 15 plus years taking in all the transnational data of each pull of a slot machine from all their machines from all their hotels linked with your loyalty card you entered and time of year and when you go, your profile, your trip patterns, then laws allowing, they adjust the looseness of the slots, the coupons provided, the trip rewards all to make sure they do what they are supposed to do in capitalism – be profitable. 

Even in uncontrolled environments such as intelligence, defense or internet search, the model is build analytics on analytics to improve the data quality and lifecycle so that the end analytics can improve. Its sound equalizers on top of the sound board.

Do go for the neat tech for your MIS. Go because your users are asking more of you in the data information knowledge chain. 

Continue on to read more on our follow-on article: BigData is a big deal because it can help answer questions fast

Some favorite TED talks

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Wiki Admin
– “Migrated to Confluence 5.3”

A business partner last night said “I don’t wake up and turn on my phone, or watch TV, or check email right away. I try to keep it simple… ” he said as several of us waxed rhapsodic of the pre-pocket tech and internet days and how teenagers patterns know no other world. But yet he continued, “OK, well that’s not true, I do get my morning dose of TED for inspiration”. 

Its just one more to add to the many morning intake mediums. People seeking personal philosophical guidance in the morning through religion, scripture, reading a story, meditation, prayer, mind-body engagement or quiet time. People seeking temporal context in morning news TV, newspaper, internet and feeds, websurfing (can I still use that term?), tablet time. People seeking social engagement with morning coffeee at the diner with the guys/gals, spouse or/and kid quality time, the facebook rise-and-shiner, or other social media digests. People seeking inspiration in either of the above

Personally, I have yet to ever find my morning ritual and I bounce in different mediums. Sometimes, its playing trains or toys or some activity with the family when we get a good rhythm going that morning, sometimes it is tablet browsing when feeling curious on various news or video feeds, sometimes it is mindless TV news digestion, and probably more rare than I should, sometimes it is outside quiet time in a run, bike, walk, or reading or whanot. Other times, the day gets going to fast, and there is no interstitial time, and an east coast call to this mountain time zone starts right up.

Though, I haven’t found my rhythm, but over the last partial decade here are a few of the greatest TED hits I’ve tweeted out as greatest hits and found inspirational :

Hans Rosling: Stats that reshape your world-view (Jun 2007)

Geoffrey West: The surprising math of cities and corporations (July 2011)

TEDxUofM – Jameson Toole – Big Data for Tomorrow (May 2011)

Eli Pariser: Beware online “filter bubbles” (Mar 2011)

Sugata Mitra: Build a School in the Cloud (Feb 2013)

Deb Roy: The birth of a word (Mar 2011)

-mt