Last month, I asked if traditional outsourcing had lost it strategic relevance. The question was based on the business world’s current irrational exuberance over digital transformation and the shifting focus of CIOs in today’s digital economy. Many readers agreed with me, but I was reminded recently that sourcing is far from dead. According to the latest state-of-the-industry report from ISG, the market generates more than $100 billion of total contract value a year.
IDG Contributor Network: Harvard students partner with U.S. government to address digital skills gaps
Recently, I interviewed Neel Mehta, a senior computer science major at Harvard University with a 4.0 GPA. He has interned at Khan Academy, Microsoft, and the U.S. Census Bureau. In addition, he was a technology fellow with Partners in Health. Neel is passionate about civic tech, and there were no good civic tech internship programs around for undergraduates to engage with government, so he started his own Civic Digital Fellowship, a fully funded data science and technology internship program in federal agencies. Here’s our interview:
Separation of concerns has been an important phenomenon in all modern organizations. The result is that monolithic stacks are being broken into multiple services for more granular control. Some of these services can then be outsourced to other providers as well, who often have expertise in handling that particular service. This is not confined to the development teams in the organization either. Each team has different a set of requirements and use different tools and services to do their job.
With this explosion in the number of services each team uses, access management becomes a menace for the sysadmin. The sysadmin is required to ensure that each employee only has access to the services they are authorized to use. They also need to take care of credentials management to make sure that the employees are accessing the infrastructure securely. This is fairly easy to do in small organizations, but once the organization starts to grow, handling these tasks manually becomes very difficult to scale. This is where Single sign-on (SSO) comes into play.
As IT organizations become more strategic, so too do their partnerships with IT outsourcing providers. Digital transformation, automation, and the data revolution are not just shaking up how IT operates, they are greatly impacting the kind — and quality — of services under contract with IT outsourcing firms.
Here is a look at the technologies, strategies and shifting customer demands shaking up IT outsourcing right now and the once-hot developments that are beginning to cool. If you’re looking to leverage an IT outsourcing partnership, or want to make good on the market for IT outsourcing as a provider yourself, the following heat index of IT outsourcing trends should be your guide.
Confused by the jumble of acronyms surrounding mobile device management? This video simply defines three key concepts: Mobile application management (MAM), enterprise mobility management (EMM) and unified endpoint management (UEM).
Sara Spivey, Chief Marketing Officer of Bazaarvoice, discusses how Bazaarvoice uses segmentation to reach the right audience, the importance of data in delivering personalized customer experiences and why face-to-face events are still valuable for building relationships with prospects and clients.
Lauren Flaherty, EVP and CMO of CA Technologies, discusses the changing role of the CMO, the importance of mapping the buyer journey, launching CA's Modern Software Factory and reaching the right tech buyers and decision-makers.
Tim Minahan, Chief Marketing Officer and SVP of Citrix, discusses how Citrix uses data to predict customer needs and engagement readiness, Citrix’s content marketing approach and the importance of industry events in building credibility and long-term relationships with new audiences.
Companies are refreshing enterprise software platforms for the cloud era and stitching together new systems to support digital business projects, triggering an uptick in IT spending worldwide.
Gartner is forecasting a 2.4 percent increase in global IT spending this year, amounting to $3.5 trillion, up from an anemic 0.3 percent growth last year. The big driver of growth is enterprise software spending, expected to jump 7.6 percent this year, hitting $351 billion, according to the market research and consulting company.
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AI. Cognitive. RPA. Autonomics. Machine learning. Deep learning.
All these terms fly around in IT organizations today as CIOs, battling marketplace uncertainties and cost pressures, look for ways to enhance enterprise performance. As with most technology trends, the hype tends to overhang reality by a significant margin in the early stages of adoption, much in line with Gartner’s hype cycle theory.
Early this year, I wrote a piece that discussed how emerging technologies such as artificial intelligence (AI) and blockchain will drive precision medicine this year. Halfway into the year, the signs are that the use of AI technologies has definitely picked up momentum.
If you follow my blogs, you won’t be surprised that I’m passionate about helping organizations drive to success in business transformation and achieve breakthrough performance. As the demand for digital transformation accelerates, I find companies setting out on the required multiyear journey without understanding what lies ahead – and then failing. I’ve blogged about several pitfalls such as the need to determine and develop support up front for the strategic intent, issues around budgeting and funding the initiative, how to de-risk the transformation journey, and much more. In this blog post, I want to alert you about the risk of “organizational fatigue.”
Uber has been in a leadership crisis for the last several years. In recent months, Uber has gone through a series of highly public missteps. Some highlights include:
While the intense scrutiny began in February when Susan Fowler published a blistering condemnation of the abusive culture, the problems Uber faces today have been snowballing well before she came forward. We typically think of problems in the workplace – sexual harassment, embezzlement, a discriminatory hiring practice – as one-off instances of someone making a mistake. In reality, these issues are a culmination of a progression of looking the other way, lack of accountability, and mismanagement of culture. Growing and expanding a team is exciting – it means a company has identified its product-market fit and is gaining traction. As technology leaders quickly scale business operations and product development, the team and culture must scale with it. Making culture a priority from the start, rather than fixing it when it’s broken (see: Uber) is critical for long-term success of the company.
Companies are facing a digital imperative to revamp business operations to better serve customers. To accommodate these shifts, CIOs are making sweeping organizational changes, adding new key roles, setting up innovation labs and tapping modern technologies to meet strategic mandates issued by their CEOs and boards.
Social, mobile, analytics and cloud (SMAC) forms the primary digital fuel for most IT organizations. But CIOs who are eager to stay atop trends are also testing artificial intelligence, machine learning, internet of things and blockchain. Collectively, such technologies have the potential to help companies transform their business processes.
Much has been written in this publication about the EU’s General Data Protection Regulation (GDPR). According to PWC, CIOs are allocating millions of dollars from their budgets to GDPR. Yet Gartner’s Bart Willemsen says, “97% of companies did not have a definitive strategy as of late last year,” and “23% of companies actually expect to be sanctioned or to take remedial action.” I was not surprised by Bart’s numbers because in a recent conversation with the Executive Director of the Privacy and Big Data Institute, Dr. Ann Cavoukian, she said that “although most organizations expect a grace period after the regulation becomes effective, regulators believe enough time has been made available to comply and enforcement will commence on May 2018”. One CIO that I know said recently, “It is unfortunate that many are not studying up on GDPR because the impact of not doing so is so material to their businesses.”
It’s hard to turn on the television or read another article about corporate data breaches. With that kind of coverage, one would think that most Americans are taking their own personal cybersecurity very seriously. Not so.
According to a recent survey from AlertSec, only 45% of Americans know they have anti-virus protection on their laptops.
But despite all the information that is stored on your laptop. Most Americans only really care about whether their phone is encrypted. “While most people work on laptops or desktops for their job. They likely think they’re employer is making sure it is secure. To them, mobile devices are more personal and they are more of an extension of the user,” Says AlertSec CEO Ebba Blitz.
Over the past two months, we’ve clearly seen how cyber attacks inflict immense harm on companies and governments. The WannaCry ransomware attack crippled healthcare institutions across Great Britain and affected hospitals in the U.S. The Petya attack shut down critical infrastructure in Ukraine; left global shipping giant Maersk reeling; halted operations at a Cadbury chocolate plant in Australia; and struck the property arm of French bank BNP Paribas.
That’s quite a wide swath.
Cyber attacks will continue to become more complex, frequent and destructive. Yet, when discussing cybersecurity, we consistently avoid focusing on the elephant in the room. We do not have enough cybersecurity professionals to help keep us safe in the first place, and more swiftly mitigate the aftermath of these attacks. Our country’s national security is at risk.
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It’s funny the ways pop culture conditions our sense of how humans and machine intelligence (MI) might interact.
Take Star Wars. When Threepio warns Han Solo that it's almost impossible to successfully navigate an asteroid field, how does Solo respond? By barreling the Millennium Falcon into an asteroid field, of course. Artificial intelligence abounds in that galaxy far, far away—but not with much obvious effect on human decision-making.
Iron Man offers a different take on MI. Tony Stark builds intelligence into almost every aspect of his life—managing smart devices in his home, helping him engineer new inventions, even offering real-time analysis to help him counter opponents in combat. Whereas to Han Solo, MI is generally a sidekick, to Stark, it’s often a way to amplify his own intelligence and accomplish things he couldn’t accomplish himself.
Big ideas are great. The technology world long ago accepted the idea of high risk/high reward moon shots. It is very easy to get swept up into how a technology can revolutionize the world. Blockchain has the potential for big things, from combating voter fraud to recreating the world's financial systems. The future is seemingly very bright for blockchain, . But what I don't hear people talking about are the more practical IT usages of blockchain. How can blockchain make IT departments more efficient and more secure?
The first step in talking about practical uses of blockchain is to first understand what exactly makes blockchain so revolutionary. The idea of distributed data is not new; we've had technologies like BitTorrent for years. Blockchain extends the idea of distributed data to include digital transactions and ledgers.
Artificial intelligence is gaining traction in enterprises, with many large organizations exploring algorithms to automate business processes or building bots to field customer inquiries. But while some CIOs see self-learning software as a boon for achieving greater efficiencies, others are leery about entrusting too much of their operations to AI because it remains difficult to ascertain how the algorithms arrive at their conclusions.
CIOs in regulated industries in particular, such as financial services and any sector exploring autonomous vehicles, are grappling with this so-called "black box problem." If a self-driving rig suddenly swerves off of the road during testing, the engineers had darn well better figure out how and why. Similarly, Finservs looking to use it to vet clients for credit risks need to proceed with caution to avoid introducing biases into their qualification scoring. Because of these and similar issues around risk, companies are increasingly seeking ways to vet, or even explain, predictions rendered by their AI tools.