Posts

Building a global cloud with lessons learned from WeWork

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We couldn't build a global cloud that would go bankrupt without massive infusions of cash. We had to apply lean and agile methodologies to our global data center build-out. At InCountry, we face the herculean task of building a global data storage and processing cloud with points-of-presence (PoP) in every country in the world.  To make it even more challenging, we need two redundant facilities in each country and to be compliant with each country’s specific regulations. Our customers would then be able to store and process data in any country with our multi-tenant offering or use dedicated hosts with our single-tenant offering. Building fixed infrastructure across all of these countries would quickly add up. There are 193 countries in the United Nations. With two redundant facilities in each country, that’s 386 facilities. With an average annual hosting and bandwidth contract of $100,000 per facility and an average set up cost of $50,000 per facility and, we were looking at almost...

Why doesn't Facebook simply filter out politics?

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This post was also published in VentureBeat. As the adage goes, don’t discuss politics or religion at the dinner table. Facebook’s genesis was for friends and family to share what was going on in their lives. Yet over the past couple of years, many Facebook newsfeeds have turned into “Trumpbook,” with a stream of outrage-focused political posts fueling Facebook interactions, especially during election cycles. Facebook first claimed that its fake news issue was “crazy” , then repeatedly stated that their algorithm could discern fake news , and has since changed its tune — it has a war room where armies of contractors analyze ads and posts for validity. But with recent advancements in machine learning, it is now possible to algorithmically filter out political news and advertisements using off-the-shelf machine learning algorithms. Topic categorization algorithms have been successfully identifying content for years and have become increasingly sophisticated and turnkey. The...

Payments will be Facebook's regulatory waterloo

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This post was also published in Entrepreneur.   Facebook has had quite a run operating in the completely unregulated, wild world of social media, finally ending with a mea culpa that it needs government regulation in order to manage the massive social and democratic disorder it has created. With its new Libra cryptocurrency, Facebook wants to disrupt the most highly regulated industry on the planet: the payments and transborder payments markets. In recent years, startups have made a habit of taking on regulators in order to grow, with Uber and Lyft as the posterchildren. Playing cat and mouse with much-hated, local regulators like the Taxi and Limousine Commissions of various cities and countries proved easy fodder in many jurisdictions and Uber and Lyft are now multibillion dollar public companies.  However, once startups aggressively step into highly regulated industries like insurance or healthcare, regulators come down on them hard. The once high-flying Zenefits was knee...

Why IT leaders need to meet the needs of the hourly worker

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This post was also published in CIO.com. Hourly employees are frequently overlooked in IT strategy — but often present the highest case for return on investment. In IT decision making, the core stakeholder of a business system is typically the business function. The finance department selects the finance system, the human resources department selects the HR system, and so on. Downstream from these decisions, regular employees are then frequently confronted with Byzantine systems. This issue is particularly pronounced for hourly workers, who are rarely considered when building and investing in work systems. At many large and midsize companies, hourly workers use a variety of non-intuitive legacy systems to perform functions like submitting timesheets, scheduling shifts, and looking up inventory. The business challenge of integrating hourly workers Hourly employees are usually the most underfunded in terms of IT spend, but often present the highest case for IT return on i...

Seven tech trends that will destroy globalization

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This post was also published in CNBC. Over the past few decades, globalization has bound countries together into a global supply chain encompassing finished products, parts, agricultural products, food products and energy. But a commingling of seven well-known tech trends will soon make it inconceivable to manufacture a product in China , ship it 7,000 miles to Long Beach, and then truck it 700 miles to Salt Lake City to be placed onto a Walmart shelf. With projected continual improvement in each of these seven tech trends, a large majority of global trade could cease very shortly. 1. Automated manufacturing A fundamental basis of outsourcing manufacturing is that decreased labor costs outweigh the shipping cost. But thanks to more automated assembly lines, we are very close to the tipping point in employee productivity where the shipping cost will outweigh the labor savings of offshore manufacturing. It's not a coincidence that multinational companies are suddenl...

From federated identity to consolidated identity: a look at the past, present and future

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This post was also published in CIO.com. It’s time for a better way to maintain identity in the enterprise. Let’s explore a new identity model, Consolidated Identity, that will simplify how employees authenticate into systems, access data and complete workflows. Today, it is common to use your Google, LinkedIn, or Facebook identity to log into a website. However, in the first generation of the commercial Internet, this was not the standard experience. Virtually every internet service required users to create an account with a username and password. For services that were only used occasionally, having to create this account and remember all the associated passwords often created friction for new users. The invention of federated identity for the consumer Internet I worked for Sun Microsystems in the early 2000s and was fortunate enough to be the technical lead for a new concept called federated identity, which presented a way for separate online entities to share identity...

Why disrupting government pot policy is so much harder than the taxi commission

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This post was also published in VentureBeat. The recent legalization of recreational marijuana in California and other states now totals to 45 states that have legalized some form of marijuana . However, the federal government has never endorsed even medical marijuana. The Obama administration created rules known as the Cole memo where they decided not to enforce federal marijuana laws if states legalized it. Recently, Attorney General Jeff Sessions reversed this course and stated that marijuana laws would be enforced. A raft of startups are operating in this tenuous legal gray area, including Eaze, Baker, and Pax Labs. Much like Uber and Lyft flouted taxi commission regulations, these startups are betting that public sentiment and user traction will overcome the existing legal and regulatory environment. Indeed, all of the state legalization efforts were passed by millennial-driven voter ballot initiatives in both red and blue states rather than by entrenched legislators. The ci...

Don’t ignore active data, the trees in the big data forest

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This post was also published on Enterprise CIO. Big data has been in vogue for years, but many businesses are having a lot of difficulty harnessing value and gaining insights from the voluminous amounts of data they collect. However, there is an often-ignored set of data in the enterprise that is truly actionable, data that I call “active” data. Active data is “in-flight data” that represents things that are changing or need some sort of action taken to move forward. Active data includes data like open purchase orders, new PTO or family leave requests, sales opportunities that are changing in scope, orders that are shipped late and so on. Surprisingly, there's a relatively small amount of active data, even in companies with tens or even hundreds of thousands of employees. Yes, there is a lot of data floating around the enterprise, but there are only so many open Purchase Order requests and or Key Performance Indicators—data that emp...

Microsoft’s slow creep back into mobile

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This post was also published on TechCrunch. Despite an early lead with Windows Mobile and Windows CE — and spending billions on Nokia’s mobile business — Microsoft has been on its heels in the mobile device market since the one-two punch of iPhone and Android launching in 2007. Over the past five years, Microsoft has staked out a strong position in the pro tablet segment with its Surface Pro. Microsoft is aggressively expanding its Surface line into the notebook and desktop segments. The upcoming introduction of x86-compatible ARM chips and the rise of progressive web apps could drive a return to the mobile market for Microsoft. Microsoft’s foothold in the pro tablet market Back in 2012, Microsoft entered the tablet market in full force. While the ARM-based Surface RT failed spectacularly in the tablet market due to lack of apps, Microsoft invented a new category of pro tablets that were as powerful as laptops. Microsoft has had a very straightforward play with its pro ta...

Software is due for a bundling event

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This post was also published on TechCrunch. We are approaching a new phase of enterprise software, where every niche of Software-as-a-Service has been filled and cloud companies are being consolidated into larger companies. Markets have a tendency to cycle from bundling to unbundling, and software is due for a bundling event. The cloud, open APIs, next-generation messengers and machine learning are combining to turn the end-user interface to enterprise software into a unified experience. There have been attempts to do this, ranging from portal servers like Portal Software, to “Enterprise 2.0” collaboration software like Jive Software, to communications platforms like Yammer. However, none of these have stuck pervasively because they only solved one slice of the problem, various backends were difficult to integrate, it was hard to work with people outside of the enterprise and there was no machine learning to sift through all the data on users’ behalf. In just the past couple of...