tech360 & BetterHiring.com Blog

tech360 post on http://betterhiring.com/your-boss-opinion-matters-more-than-you-think/

Your Boss' Opinion Matters More Than You Think

We’re all familiar with the phrase “seeing is believing.” Witnessing an unusual or unexpected event increases your ability to regard it as valid. But is the opposite also true? Do we tend to see what we believe? Daniel Kahneman, author of Thinking Fast and Slow, has noted that his overwhelming conclusion about people’s decision-making challenges is that they tend to seek only for information that confirms what they originally believed.

Over the last several months my colleague Jack Zenger and I have been working with a multinational company to assess and coach their top three levels of management. As we completed individual coaching sessions it was apparent that some managers had a positive bias and others had a negative bias in their ratings of employees.

To understand this better we looked at a larger dataset of 360 data. In a recent Harvard Business review article we shared a study where we identified 50 positive and 31 negative rating managers. These managers rated their direct reports significantly more or less positively than the rest of their colleagues. The graph below shows the 5-point rating scale for this 360 degree feedback instrument and the percentage of time each group of managers used each point on the scale.

These ratings represent the following scores:

Needs significant improvement—Poor performance

Needs some improvement—Inconsistent performance

Competent—Good performance

Strength—Top quartile

Outstanding strength—Top 10%

Note that only 18.4% of the positive managers’ ratings were “Competent” compared to 51.4% for the negative managers.

The Impact of a Positive or Negative Rating Manager

What is the impact when managers inherently rate more positively or negatively? Is the rating an objective and accurate analysis of a subordinate’s performance, or does the rating itself influence the subordinate’s performance?

Anyone who would have joined me in the discussions with the subordinates of the “high” and “low” rating managers would have instantly seen the impact. Those people who had higher, more positive ratings felt lifted up and supported. The vote of confidence from their managers gave them optimism about additional improvement.

But the subordinates who had a negative-rating manager were confused or discouraged, and often both. They felt it was impossible to succeed. They often heard the message as “you are not valued or trusted.” What effect did that have?

We measured employee engagement data for the direct reports of positive and negative rating managers. Direct reports who worked for negative rating managers had engagement scores at the 47th percentile. Those reporting to positive rating managers had engagement scores at the 60th percentile. This difference is statistically significant.

We acknowledge that that negative rating managers may select less engaged employees, but the far more likely explanation is that the engagement levels of these employees was roughly the same, but the diverse day to day interactions capped by very divergent performance reviews had a big impact on engagement levels.

Possible Motives of Positive or Negative Rating Managers

Negative raters would typically say something like, “I want my people to get the message that I have high expectations.” The positive rating manager’s motive and message was quite different. They too had high expectations, but the message they desired to send was that they had confidence in their people. They believed that they had selected the greatest people for those jobs and they expected them to succeed.

Impact of Manager Expectations Did those expectations change the behavior of the subordinates of these high and low rating managers?

The following chart shows the overall leadership effectiveness results for those leaders who worked for the positive and negative rating managers. Negative-rating managers rated their direct report leaders at the 19th percentile, while positive rating manager rated their subordinates at the 76th percentile. The ratings of peers, the next level down direct reports and others also tended to be lower for negative rating managers and higher for positive rating managers.

Possible Conclusions

Both high and low rating managers had perceptions that differed widely from all other raters, which suggests that those who are at either extreme deliberately should look for information that is contrary to their bias. “Believing” leads you to see what you want and expect to see.

Believing their perceptions are correct and that everyone else’s are incorrect is akin to the person in the marching band who believes that everyone else is out of step except them.

Having a boss with a strong positive or negative bias appears to influence subordinates’ behavior to the extent that others ultimately can see it. The bosses’ emotions are contagious and infect those who work for them. It is unlikely that these two groups of subordinates started out their careers as higher or lower performers, but it is clear that they have become different.

There is apparently a positive motivational effect that comes from reporting to a boss who is positive. Conversely, there is a demotivating “downer” impact that comes from working for the low rating boss. Should people just accept that getting one or the other kind of boss is to be expected and simply the “luck of the draw,” or should people expect that it is their right to work for an excellent boss?

There is an interesting study that is related to the issue of believing is seeing called “Predicting non-marital romantic relationship dissolution: A meta-analytic synthesis.” This was a meta-analysis of 137 studies collected over 33 years with 37,761 participants. These studies were looking at factors that cause non-married couples to break up or stay together. The number one factor listed in the study that impacted couples staying together was something they called “positive illusion.” In other words, the person you are dating thinks you are “awesome.” It turns out if the person you are dating thinks you are awesome, your satisfaction with the relationship is significantly higher. Is it possible, then, that if a boss thinks you are awesome you then become more awesome? It is hard if not impossible for most of us who have had a boss who thought we were awesome not to believe and embody the description because of the tangible impact their belief had on us. Many people also know the impact of the negative expectation from a boss. Typically our performance went down.

Implications

Having spoken with hundreds of leaders whose bosses thought they were awesome, we know the impact is real. It is our hope these findings can have a positive impact on the ratings—and the messages—leaders are sending to their current and future employees. Your ability to build their engagement is much higher than you may have believed.

tech360 post on http://betterhiring.com/why-cloud-databases-are-in-your-future/

Why Cloud Databases Are In Your Future

Why Cloud Databases Are In Your Future

The cloud has gotten pretty complicated—and crowded. There are more new “as a service” offerings popping up lately than reality TV shows.

Yet, one of those offerings in particular has a great shot at becoming an enterprise staple, and a long-term platform for IT innovation—database as a service. Indeed, Larry Ellison, Executive Chairman and CTO of Oracle made this prediction recently: “Database is our largest software business and database will be our largest cloud business.”

A database cloud service, or database as a service (DBaaS), makes database capabilities available online, when and where those capabilities are needed. The user can access a slice of a database (a schema), or, more likely, a complete, dedicated database instance. Or an enterprise can offer DBaaS running in its own data center for internal customers.

Done right, DBaaS promises significant cost advantages over traditional database strategies. That, as well as the other big benefits the cloud is so often touted for: agility, scalability, speed of deployment, and a steady flow of new capabilities.

That’s why DBaaS, though a relatively new cloud category, is generating a lot of interest. One estimate has the market for cloud databases and DBaaS growing from $1 billion this year to $14 billion by 2019.

Even as that momentum builds, it’s important to understand that the corporate data center is not going away any time soon. Many businesses will take a phased approach, in which certain types of databases are moved to the cloud while others remain on premise.

“Customers today are primarily running mission-critical database systems on dedicated servers and storage in their data centers,” says Andy Mendelsohn, Oracle Executive VP for Database Server Technologies. These vital databases often support an organization’s crown jewels, such as a bank’s customer accounts system or a discount store’s merchandising system. Because of their criticality to the business, these databases “will likely remain on premise for many years to come” Mendelsohn says.

That doesn’t mean there aren’t plenty of databases that could benefit from cloud computing’s efficiencies. Large companies “have thousands of databases,” many of which may be well suited for the cloud, Mendelsohn points out. Those include databases that are used for developing new applications or testing them and less critical production systems.

And the prime directive regarding those thousands of dev/test systems at most enterprises is “lower the cost of running all those databases,” says Mendelsohn.

The cloud, in combination with virtualization, can help do that. Virtual machine (VM) technology allows a single physical server to run many virtual servers or VMs, which enables server consolidation.

That means you can take say “9,000 databases running today on 9,000 servers, and consolidate them onto 500 servers,” Mendelsohn says. The problem with that scenario, however, is that you still have 9,000 databases to manage. The solution: “What if I could consolidate those 9,000 databases down to 40 databases?” Mendelsohn asks.

That’s where Oracle’s new database architecture comes in. The most recent release of Oracle’s flagship system, Oracle Database 12c, features a fundamental new architecture called Oracle Multitenant that lets developers create “pluggable” databases—up to 252 of them—that run in one “container” database. DBAs can now do most common administration functions like patching, upgrade, and backup at the container database level. This drastically reduces the cost of managing your databases.  Plus efficiencies in the new multitenant architecture allow up to 5x more databases to be run on a given server or VM, which ups the ante considerably on the hardware savings represented by server consolidation.

Oracle Multitenant “lowers your hardware costs, but the big win is around lowering labor costs,” Mendelsohn points out.

That’s because there are now far fewer databases to manage, and Oracle Enterprise Manager 12c, the company’s advanced database administration tool, works in conjunction with Oracle Multitenant to automate the monitoring and tuning of Oracle pluggable databases. It also provides metering and chargeback capabilities that let managers monitor and report database usage. That chargeback capability is an important function in a service-oriented private cloud architecture, which is where most customers are looking to implement Oracle DBaaS technologies today.

Business Agility

Customers want the cost savings—both CapEx and OpEx—represented by DBaaS, and they’re realizing they can get them using cloud database capabilities in a private cloud architecture. As well, they want to provide the efficient and available IT resources that many LOB managers have been looking outside their organizations to get. “One of the reasons they want to do database as a service on premise is to give business units the same agility they can get in the cloud,” Mendelsohn says.

That’s why Oracle cloud database capabilities—Oracle Database 12c with Oracle Multitenant, Oracle Enterprise Manager 12c, along with tools for database security, performance, and recoverability Oracle has been honing over years—“resonate very strongly with them,” Mendelsohn says. He expects to see significant adoption of Oracle Database12c related to DBaaS.

Customers can reap the benefits of Oracle DBaaS in Oracle’s public cloud or in private clouds that they implement and manage on their own. “Oracle Database 12c Multitenant Architecture is the cornerstone of our effort to redesign the database for the cloud, whether public or private cloud,” Mendelsohn says.

Increasingly, enterprises are moving test, dev, and production applications, and the databases they run on, to the public cloud. A key requirement here is to support hybrid cloud, where some databases remain in the corporate data center and some are in the cloud. Oracle’s strategy is to make sure any database application that runs on premise can also run in the public cloud and vice versa.   At Oracle OpenWorld 2014 in San Francisco, Ellison demonstrated how customers can move an on-premise Oracle database to the Oracle Public Cloud in minutes without changing a single line of code.

As more CIOs look for that kind of flexibility, Oracle is well positioned to support those critical systems with its cloud infrastructure and its advanced cloud database technology. Customers will understand, Mendelsohn says, that Oracle is “best in the world at doing database as a service in the cloud.”

tech360 post on http://betterhiring.com/15-programming-languages-you-need-to-know-in-2015/

15 programming languages you need to know in 2015

If you’re a programmer, these are good times. Jobs in the segment are projected to grow 8% over the next seven years, according to the U.S. Bureau of Labor Statistics. If you’re a hotshot coder, you can make up to $300 an hour or more.

Those at the high end of the pay scale have mastered the languages that are most in demand. Which are those? We asked Doug Winnie, director of content for online learning platform Lynda. Here’s his assessment:

1. Java

Image: Mashable Composite/Wikimedia

Java is one of the most popular languages for building back-ends for modern enterprise-web applications. With Java and frameworks based on it, web developers can build scalable web apps for a variety of users. Java is also the main language used to develop native Android apps for smartphones and tablets.

2. JavaScript

Every modern website uses JavaScript. It’s the go-to language if you want to create interactivity for your site, or build user interfaces with one of the dozens of popular JavaScript frameworks.

3.C#

C# is the primary language for developing on Microsoft platforms and services. Whether you’re building modern web applications using Azure and .NET, apps for Windows devices or powerful desktop apps for your business, C# is the quickest way to harness all that Microsoft has to offer. Want to play, as well? The popular Unity game development engine also uses C# as one of its primary languages.

4. PHP

Building a web app that needs to work with data? PHP, along with databases like MySQL, are essential tools for building modern web applications. PHP powers a majority of today’s data-driven websites, and is the foundation technology for powerful content management systems, like WordPress, which you can extend to make your site more powerful.

5. C++

Want to get a little lower level with your programming? When you need to connect directly to hardware to get the most out of your processing power, C++ is the perfect choice for developing powerful desktop software, hardware-accelerated games and memory-intensive apps on desktops, consoles and mobile devices.

6. Python

Python can almost do it all. Web apps, user interfaces, data analysis, statistics — whatever your problem, there’s likely a framework for it in Python. Most recently, Python has been used as a key tool for data scientists to sift through giant data sets for any industry.

7. C

Image: Mashable Composite/Wikimedia Commons

Why is the C language still popular? Size. C is small, fast and powerful. If you’re building software for embedded systems, working with system kernels or just want to squeeze every last drop of the resources you have at hand, C is lean, mean and ready to scream.

 8. SQL

Data is massive, it’s everywhere and it’s complex. SQL gives you the ability to find the exact information you want in a fast, repeatable and reliable way. Using SQL, you can easily query and extract meaningful data from large, complex databases.

9.Ruby

Want to kickstart your project in record time, or prototype a new idea for your next big web app? Ruby (and Ruby on Rails) can get you there quickly. The Ruby language is straightforward to learn and incredibly powerful, plus it powers tons of popular web apps around the globe.

10. Objective-C

Image: Mashable Composite/Wikmedia Commons

If you’re interested in making an app for iOS, you’ll need to know Objective-C. While last year’s hype centered on Apple’s new language Swift, Objective-C is still the foundational language if you want to build apps for the Apple ecosystem. With Objective-C and XCode, the official software development tool from Apple, you’ll be in the App Store in no time.

11. Perl

Is Perl esoteric? Yes. Is it confusing? Yes. Is it a super powerful language, and a key component of anyone’s cyber security arsenal? Also true. Perl has powered the web since its early beginnings, and is still considered a key tool for any IT professional.

12 .NET

Although not a language in itself, .NET is a key Microsoft platform for cloud, service and app development that gets more advanced and valuable with each release. Due to the recent open-sourcing efforts of Microsoft, .NET is now coming to Google and Apple platforms. As a result, you can use .NET today with a variety of programming languages to build apps that easily support multiple platforms.

13. Visual Basic

Visual Basic is the language that gets business done. A key language of the .NET platform, it enables you to build applications to support your business, and automate powerful Office applications like Excel to accomplish super-human feats of computation, as well as streamline your most common tasks.

14. R

R is powering the revolution of big data, and is a must-know language in 2015 for anyone in need of serious data analysis. From science and business to entertainment and social media, R is the language to learn for statistical analysis across nearly every field of interest.

15. Swift

Not even a year old, the Swift programming language has captured the eyes and keyboards of developers worldwide as a new, fast and easy way to develop for Apple’s Mac and iOS operating systems. Swift’s broad power and friendly syntax makes it possible for anyone with a Mac to build the next killer app for iOS or Mac OS X.

via 15 programming languages you need to know in 2015.

tech360 post on http://betterhiring.com/facebooks-emotional-experiment-is-most-shared-academic-research/

Facebook's 'emotional experiment' is most shared academic research

Facebook’s notorious emotional manipulation study received more online attention than any other scientific research in 2014, according to an analytics company.

The paper, “Experimental evidence of massive-scale emotional contagion through social networks”, was published in the respected US journal the Proceedings of the National Academy of Sciences in July.

It sparked outrage by revealing that Facebook had been experimenting on hundreds of thousands of unwitting users, attempting to induce an “emotional state” by selectively showing positive or negative stories in their news feeds.

Academic analysts Altmetric suggests that the research will have done wonders for the scientists’ public engagement metrics after it ranked number one for attention out of every scientific article published in 2014.

Perhaps surprisingly, the majority of the recorded attention was on Twitter, where the article was shared 4,000 times to almost 10 million people. On Facebook itself there was little reaction to the research, which was shared publicly just 344 times. However, there were likely to have been more private wall posts on Facebook, so the total cannot be determined.

The article was also mentioned in 300 news sites, 130 blogposts, 13 subreddits and even 113 Google+ profiles.

But while Facebook may be a natural topic for online attention, the rest of the top five articles are more varied – and so are their reasons for getting so much attention. Second place went to a seemingly unassuming paper in the Journal of Ethology titled “Variation in Melanism and Female Preference in Proximate but Ecologically Distinct Environments”. But a quick scan of the articles citing the paper reveals the reason for its notability: the article was published with an author’s comment left in, asking “should we cite the crappy Gabor paper here?”.

The rest of the top five at least made the list for their contents. Third place went to a study from Nature suggesting that artificial sweeteners could induce glucose intolerance, while fourth place was a breakthrough in stem-cell research also published in Nature.

And the fifth place? Research published in Frontiers in Zoology in which animal behaviourists watched dogs defecating and discovered that they were sensitive to small variations in the Earth’s magnetic field.

Euan Adie, founder of Altmetric, said: “It’s no surprise to see that the most shared articles of the year heavily mirror the media agenda, but interesting to note that on occasion online communities are drawing attention to studies that have not received a significant amount of mainstream coverage.

“For example, we had more than 2,000 tweets for a study on how gaining basic certification affected nursing confidence levels. This reached a combined following of more than 2.2 million followers, demonstrating how social media can really boost the profile of some online published studies.”

via Facebook’s ‘emotional experiment’ is most shared academic research | Technology | The Guardian.

tech360 post on http://betterhiring.com/restless-at-work-linkedin-can-guess-what-youll-do-next/

Restless At Work? LinkedIn Can Guess What You'll Do Next

A generation ago, if you felt restless in your job and weren’t sure what to do next, you could ask your boss or friends for advice — or you could visit the local fortune-teller. Now however, an intriguing new LinkedIn tool provides some pretty good guesses about what you’ll do next.

LinkedIn’s data-visualization team has created a giant sphere that’s speckled with nearly 300 types of jobs, ranging from actors to firefighters, insurance agents and Oracle database administrators. Click on any one of those categories — and an animated version of connect-the-dots will spring forth, showing you the most common career moves of people in those fields. This link will let you test the system yourself.

To create these forecasts, LinkedIn research consultant Sohan Murthy explained in a blog post, the company’s data scientists culled through the career histories of more than 300 million people with LinkedIn profiles. Researchers focused on cases where people switched to at least a slightly different category, instead of simply moving up the ladder in their chosen specialty. LinkedIn’s analysts also discarded cases involving people who had switched careers multiple times, or whose current careers straddle multiple categories.

Many of the career paths are exactly what you’d expect. Financial consultants tend to become accountants and data analysts. Psychologists end up as social workers or university professors. And when today’s job becomes unbearable,  just about everybody is willing to give sales a try.

But in an intriguing number of cases, LinkedIn’s mapping system unearthed job hops that are far from obvious. Among them:

Soldiers and military officers, when they transition to civilian life, may pick new jobs as diverse as corporate strategists, business owners or police officers.

Geologists sometimes end up as information-technology support specialists or environmental specialists.

Pharmacists cross over to the other side of the counter and become medical representatives.

People who start out as political staffers can end up as everything from lawyers and judges to public-relations offices.

Another oddity: fields that offer very little mobility. As LinkedIn’s Murthy points out, people who become web developers, paralegals or physicians have hardly any common career options beyond staying in their current field. Bad news? Not necessarily.

In Murthy’s words, “this is a classic sign of specialization,” and that’s nothing to weep about. If demand for these skills stays strong, and the work is enjoyable, people in such aspects of law, tech and health care may never feel the urge to switch.

via Restless At Work? LinkedIn Can Guess What You’ll Do Next.

tech360 post on http://betterhiring.com/why-so-many-new-tech-companies-are-getting-into-health-care/

Why So Many New Tech Companies Are Getting into Health Care

A flood of new health care IT companies has been pouring into the U.S. health care market. The cause of this torrent: the recognition that as market and regulatory forces alter incentives in health care, IT companies will play a powerful role in combating the overemployment and declining productivity that has plagued this industry and in helping providers improve the quality of care.

The dam broke in September 2007, when Athenahealth went public, the price of its shares jumping by 97% on the first day. Since then, the company’s value has risen to $5 billion. Athenahealth proved to entrepreneurs, software engineers, and investors that the health care sector is fertile ground for creating large technology-services companies that use a subscription-based business model to offer software as a service (SaaS).

Despite its size and growth rate, the health care sector was long considered an impenetrable, or at least an unattractive, target for IT innovation — the entrepreneurial equivalent of Siberia. Athenahealth broke the ice by proving that it could sell SaaS efficiently to small physician businesses, get doctors to accept off-premises software, and achieve the ratios of customer-acquisition costs to long-term value that other sectors already enjoy.

As Athenahealth accomplished its goals, several larger forces have dramatically widened the scope of opportunity in the sector:

The Great Recession led to a loss of 8.8 million U.S. jobs and big declines in demand throughout the economy (including health care services) — yet health care employment grew by 7.2%. That reality increased awareness that a decline in labor productivity was driving much of the excessive spending in health care.

The American Recovery and Reinvestment Act of 2009 included the Health Information Technology for Economic and Clinical Health (HITECH) Act, a $25.9 billion program to give doctors and hospitals incentives to adopt electronic health records. EHR adoption has now grown to nearly 80% of office-based physicians and 60% of hospitals, fueling many successful software start-ups, such as ZocDoc, Health Catalyst, and Practice Fusion.

The Affordable Care Act (ACA) requires that an enormous amount of data on cost and quality be made freely available. In addition, digital health applications, mobile phones, and wearable sensors, as well as breakthroughs in genomics, are creating truly big data sets in health care. These data contribute to greater market efficiency, more consumer-oriented products and services, and clinical care that is evidence-based and personalized.

The ACA has led to a proliferation of risk-based (rather than fee-for-service) payment models. For example, providers in accountable care organizations are rewarded for generating annual savings, and providers who use bundled payments get a fixed budget for an end-to-end course of treatment. Effectively responding to these changing economic incentives will increase reliance on software that helps providers manage population risk, understand costs and trends, and engage patients.

These macro-level developments set the stage for other SaaS companies to follow Athenahealth’s lead in enormously improving labor productivity and quality of care.

Within the next decade, software tools will eliminate thousands, perhaps millions, of jobs in hospitals, insurance companies, insurance brokerages, and human resources departments. Not the jobs of people who actually provide care — but those of administrative middlemen, whose dead weight contributes to economic loss. Here are five examples:

Digital insurance markets, combined with ACA-enacted regulatory changes such as guaranteed issue and community rating, make it possible to price and sell health plans to anyone immediately. These developments will decimate the armies of brokers who act as intermediaries between customers and insurance services.

Price transparency, digital insurance products, and tools such as reference pricing make it possible to generate an exact price and instantly collect payment for a health care service. As a result, revenue cycle managers in hospitals and claims adjudicators in insurance companies will be displaced.

The inevitable shift to the cloud will render obsolete the costly, insecure data centers that most doctors and hospitals are now building, staffing, and running.

Adopting self-serve mobile applications will eliminate the forms, faxes, and excess staffing at many call centers, thereby improving satisfaction for everyone in the process.

Centralized clearinghouses that share information across organizations and state lines will eventually replace the byzantine, paper-based process of credentialing doctors, tracking continuing medical education, and keeping licenses up-to-date. That means smaller staffs in hospitals’ medical affairs divisions, health plans, medical boards, and state and local health departments.

Given that wages account for 56% of all health care spending, improvements in labor productivity could generate enormous value. Simply reducing administrative costs could yield an estimated $250 billion in savings per year.

As compelling as the prospective labor efficiencies are, the benefits of SaaS extend beyond direct labor costs. Easier access to data on physician quality, specialization, and adherence to evidence-based care will better match patients with doctors who provide high-quality, efficient services, thereby averting health complications for their patients. Moreover, software can help bring relevant clinical guidelines and personalized risk scores to patients and clinicians as they improve care plans, engage in shared decision making, and avoid duplicative services. Such efficiencies will, in turn, enhance how patients perceive and experience the care they receive. SaaS companies can trumpet all of these advantages, not just the employment savings they yield.

To seize on the new opportunities in the health care sector, SaaS companies can take these steps:

Attack economic inefficiencies in order to generate immediate, tangible customer return on investment. Witness how Castlight Health’s transparency tools are generating annual savings for employers and employees. And be clear about the source of the ROI, given that in most cases the revenue comes from another health care stakeholder who may be able to undermine the business.

Focus on building in network effects so that improvements made by one user enhance the product’s value for current and future users, just as Athenahealth does when it rapidly disseminates changes in payment rules at one provider to all other providers. Most SaaS businesses in health care IT cannot protect their intellectual property; so it is important to continually augment the value of the product to achieve scale.

Use software-enabled service models, rather than pure SaaS. For example, Grand Rounds’ software not only recommends an expert doctor for a patient but also collects, organizes, digitizes, and summarizes the patient’s records — and then books the appointment for the patient. In effect, the software makes it easier for patients to adhere to high-quality, cost-effective care, thereby enhancing the overall ROI for the product.

It took Athenahealth a decade, from 1997 to 2007, to go public on the strength of its SaaS model. It took Castlight Health only six years, from 2008 to 2014, to do the same. Now an array of highly valued healthcare SaaS companies, each worth more than $100 million, is emerging. They include Zenefits, Grand Rounds, Doctor on Demand, Omada Health, Health Catalyst, Doximity, and Evolent Health. Indeed, Zenefits is one of the fastest-growing SaaS companies ever, regardless of industry, surpassing $500 million in enterprise value in its first year.

The success of SaaS companies in health care is thanks, in part, to an influx of leaders from other sectors. They bring with them teams of technical talent that deliver consumer and enterprise software faster, better, and more cheaply than many legacy health care IT companies can do. Witness ZocDoc, founded by first-time entrepreneurs from McKinsey; Grand Rounds, founded by Owen Tripp, who cofounded Reputation.com; Zenefits, founded by Parker Conrad, who cofounded SigFig; and Doctor on Demand, founded by Adam Jackson, who cofounded Driverside (just to name a few). This type of cross-pollination is an essential ingredient of innovative change.

The barriers between health care IT companies and IT in other industries are clearly coming down, and we expect the number of sector disruptions and billion-dollar companies to swell. As each innovation wave generates more data, disruption-cycle times will shorten, thereby forcing all players in the health care ecosystem to address inefficiency as they compete on quality and value creation. Those who fail to act will be washed away by the tide that lifts all other boats to greater productivity.

via Why So Many New Tech Companies Are Getting into Health Care.

tech360 post on http://betterhiring.com/retailers-secret-weapon-lies-in-their-it-department/

Retailers' Secret Weapon Lies In Their IT Department

In today’s world, customers are looking for an experience that streamlines the shopping process and caters to their needs. In fact, the quality of their shopping experience is playing a larger role than ever when it comes to making purchasing decisions.

A 2014 study by TimeTrade, for instance, indicated that 90 percent of shoppers leave a store empty-handed if they don’t get the help they need – while 86 percent of those very same shoppers would buy more than planned if they got that help, and 90 percent would be more likely to return to the same store again. In other words, retailers who effectively and efficiently guide customers through the buying process will win sales and customer loyalty.

Today’s technology increasingly plays a role in customer satisfaction. It streamlines the process and makes new forms of customer interaction possible. In fact, as technology begins dominating the landscape, retailers who fail to embrace it will find it hard to compete. And it has positioned IT managers and specialists as vital players in retail strategies.

IT managers must find and coordinate teams of people with different specialties to ensure tech operations run smoothly in the store. Tech systems are growing increasingly complex, often requiring people with different skills and backgrounds, changing the hiring needs of most retailers.

“[IT specialists] have always been important, but with the evolution of technology, just from a home use to a people perspective, companies are looking more and more toward IT to gain a competitive edge,” says Ed Smith, an IT specialist and VP and CEO of Abt Electronics, a Chicago-area electronics superstore which is known for its cutting edge use of IT in a retail environment.

“[Retail IT] is our DNA” he says.

The IT factor

A single store might need someone who specializes in mobile development, another who specializes in supply chain implementation, and another who focuses on analytics or on a real-time data and memory platform. A manager coordinates these efforts so they can actually produce useful results and coordinate actual programs and strategies with a high ROI.

Selling products online and making them available in-store for pickup has made the buying process easier for customers – and it also can save valuable space and resources for the retailer. And the use of beacon technology, such as Samsung’s newly introduced Proximity, enables retailers to reach customers like never before. Beacon technology is a location-based service that allows retailers to provide in-store offers to consumers and can even provide customers with floor plans of a mall. For customers, it’s convenient and appealing, and for retailers it provides a streamlined way to create and manage marketing campaigns.

Another key use of technology that every retailer should consider is making product information and branding available in-store. This may mean using video screens to display product detail, but there are other options. Providing free Wi-Fi is a simple, affordable and extremely powerful one. Shoppers with smart phones and tablets can simply connect to Wi-Fi and research products, or even find sales tailored to their personal interests and purchase history.

Some stores – like Smith’s Abt – equip their staff with tablets or smartphones so that they’re ready to answer any customer question with the click of a button.

Ben Davis is an IT consultant with the British firm Econsultancy, which specializes in using technology to bring together online and offline retail strategies. He notes that while many retailers overemphasize integrating social media into the store environment, mobile technology can be extremely powerful. Giving price comparisons, sales alerts and product information can guide customers through the purchase process. It can also help develop strong customer-retailer relationships while providing retailers with valuable data and analytics.

All of these projects require teams of people with different specialties – mobile technology, programming, analytics – to succeed. Retail managers’ coordination efforts make this possible. These can facilitate every step of the selling process – from stocking stores to attracting customers and driving sales.

“Multichannel customers are worth more than offline- or online-only ones,” says Davis. “It pays to implement tech that allows operational improvement – not just a flashy experience for the customer.”

  via Retailers’ Secret Weapon Lies In Their IT Department.

tech360 post on http://betterhiring.com/tech-jobs-minorities-have-degrees-but-dont-get-hired/

Tech jobs: Minorities have degrees, but don't get hired

Top universities turn out black and Hispanic computer science and computer engineering graduates at twice the rate that leading technology companies hire them, a USA TODAY analysis shows.

Technology companies blame the pool of job applicants for the severe shortage of blacks and Hispanics in Silicon Valley.

But these findings show that claim “does not hold water,” said Darrick Hamilton, professor of economics and urban policy at The New School in New York.

“What do dominant groups say? ‘We tried, we searched but there was nobody qualified.’ If you look at the empirical evidence, that is just not the case,” he said.

As technology becomes a major engine of economic growth in the U.S. economy, tech companies are under growing pressure to diversify their workforces, which are predominantly white, Asian and male. Leaving African Americans and Hispanics out of that growth increases the divide between haves and have-nots. And the technology industry risks losing touch with the diverse nation — and world — that forms its customer base.

On average, just 2% of technology workers at seven Silicon Valley companies that have released staffing numbers are black; 3% are Hispanic.

But last year, 4.5% of all new recipients of bachelor’s degrees in computer science or computer engineering from prestigious research universities were African American, and 6.5% were Hispanic, according to data from the Computing Research Association.

The USA TODAY analysis was based on the association’s annual Taulbee Survey, which includes 179 U.S. and Canadian universities that offer doctorates in computer science and computer engineering.

“They’re reporting 2% and 3%, and we’re looking at graduation numbers (for African Americans and Hispanics) that are maybe twice that,” said Stuart Zweben, professor of computer science and engineering at The Ohio State University in Columbus.

“Why are they not getting more of a share of at least the doctoral-granting institutions?” said Zweben, who co-authored the 2013 Taulbee Survey report.

USA TODAY

An even larger gulf emerges between Silicon Valley and graduates of all U.S. colleges and universities. A survey by the National Center for Education Statistics showed that blacks and Hispanics each made up about 9% of all 2012 computer science graduates.

Nationally, blacks make up 12% of the U.S. workforce and Hispanics 16%.

Facebook, Twitter, Google, Apple and Yahoo declined to comment on the disparity between graduation rates and their hiring rates.

LinkedIn issued a statement that it was working with organizations to “address the need for greater diversity to help LinkedIn and the tech industry as a whole.”

Google said on its diversity blog in May that it has “been working with historically black colleges and universities to elevate coursework and attendance in computer science.”

USA TODAY

In his blog post on diversity, Apple’s CEO Tim Cook cited improving education as “one of the best ways in which Apple can have a meaningful impact on society. We recently pledged $100 million to President Obama’s ConnectED initiative to bring cutting-edge technologies to economically disadvantaged schools.”

All of the companies have insisted they are hiring all of the qualified black and Hispanic tech workers they can find.

In an interview earlier this year, Facebook Chief Operating Officer Sheryl Sandberg said the key to getting more women and minorities into the technology field had to start with improvements to education.

Tech companies lag in hiring minorities

Only half of black and Hispanic graduates with computer science degrees from leading universities are being hired by major technology companies. Percentages of minority staff at seven major companies and minorities graduating with CS degrees from major universities*:

Wage disparity among high-tech workers

Minority tech workers are paid less than their white coworkers, with Hispanic women at the bottom of the pay scale, according to a new study.

“We are not going to fix the numbers for under-representation in technology or any industry until we fix our education system,” she said.

Others say tech giants simply don’t see the programmers right in front of them.

Janice Cuny directs the Computer Education program at the National Science Foundation. She says black and Hispanic computer science graduates are invisible to these companies.

“People used to say that there were no women in major orchestras because women didn’t like classical music. Then in the 1970s they changed the way people auditioned so it was blind, the listeners couldn’t see the players auditioning. Now the numbers are much more representative,” she said.

The same thing happens in the tech world, said Cuny. “There are these subtle biases that make you think that some person is not what you’re looking for, even when they are.”

USA TODAY

One of the key problems: There are elite computer science departments that graduate larger numbers of African-American and Hispanic students, but they are not the ones where leading companies recruit employees. Stanford, UC-Berkeley, Carnegie Mellon, UCLA and MIT are among the most popular for recruiting by tech companies, according to research by Wired magazine.

“That is the major disconnect,” said Juan Gilbert, a professor of computer and information science at the University of Florida in Gainesville.

“The premise that if you want diversity, you have to sacrifice quality, is false,” he said. His department currently has 25 African-American Ph.D. candidates. Rice University in Houston has a large number of Hispanic students.

“These are very strong programs, top-ranked places that have excellent reputations,” he said. “Intel has been hiring from my lab, and they say our students hit it out of the ballpark.”

Justin Edmund says he was fortunate to attend Carnegie Mellon. Today he’s the seventh employee at Pinterest and one of the top designers at the San Francisco start-up valued at $5 billion.

He’s also one of the few African Americans in his company.

“There’s a lot of things that can be done to fix the problem, but a lot of them are things that Silicon Valley and technology companies don’t do,” Edmund said. “If you go to the same prestigious universities every single time and every single year to recruit people … then you are going to get the same people over and over again.”

Contributing: Paul Overberg

via Tech jobs: Minorities have degrees, but don’t get hired.

tech360 post on http://betterhiring.com/whats-driving-greater-adoption-of-it-operations-analytics/

What's Driving Greater Adoption of IT Operations Analytics?

With modern business becoming more complex and facing constant changes, unpredictable events, and dynamic demand by the end users – all happening at unprecedented speed – IT Operations & Management is looking to adopt the right tools to optimize operations to handle the complexity and pace of change.

Need to Do More With Less

In 2009, IT budgets fell sharply. According to Gartner, they shrank 8.1 percent in 2009, and another 1.1 percent the year after. Though IT budgets started growing again in 2011, they are only at the level they were in 2005.

At the same time, IT operations teams are running with fewer people and resources, while not only managing an increasing number of systems, but also dealing with the new complexity that comes with hybrid environments and the rapid pace of changes nurtured by agile processes. Increasing productivity while lowering costs seems like a difficult proposition, especially since increased demands are placed on operations staff to manage a variety of rapidly evolving applications across the environment.

Managing Enormous Amounts of Data

Everything from system successes to system failures, and all points in between, are logged and saved as IT operations data. IT services, applications, and technology infrastructure generate data every second of every day. All of that raw, unstructured or polystructured data is needed to manage operations successfully. The problem is that doing more with less requires a level of efficiency that can only come from complete visibility and intelligent control based on the detailed information coming out of IT systems.

Frequent Changes Occur in IT Operations

With the operations staff responsible for the health of the entire business it is in their DNA to resist anything that might introduce unpredictable changes within the IT infrastructure or applications, so much so that IT Ops are rewarded for consistency and for preventing the unexpected or unauthorized from happening.

However, solving business problems requires creativity and flexibility to meet the frequent changes dictated by business requirements. New agile approaches eschew the standard method of releasing software in infrequent, highly tested, comprehensive increments in favor of a near-constant development cycle that produces frequent, relatively minor changes to applications in production. With hundreds or thousands of dependencies, even if the agile iterations are properly tested throughout development, unforeseen problems can arise in production that can seriously affect the stability.

Since every IT service is based on many parameters from different layers, platforms, and infrastructure, a small change in one of the parameters amongst millions of others can create significant impact. When this happens, finding the root cause can take hours and days particularly given the pace and diversity of changes. In many cases unplanned changes lie at the root of many failures. This can create business and IT crises that should be resolved quickly to avoid productivity and business losses.

Traditional Approaches Failed

Problems can be difficult to manage or even identify because so many businesses rely only on monitoring software, which is not sufficient alone to address challenges described above. In fact, problems are often not detected until they have grown out of control. If these issues are not resolved quickly, the result is downtime.

All of the technology infrastructure running an enterprise or organization generates massive streams of data in such an array of unpredictable formats that it can be difficult to leverage using traditional methods or handle in a timely manner. IT operations management based on a collection of limited function and non-integrated tools lacks the agility, automation, and intelligence required to maintain stability in today’s dynamic data centers. Collecting data, filtering it to make it more manageable, and presenting it in a dashboard is nice, but not prescriptive.

One of the holy grails still unresolved in IT management is intelligent IT automation. There are pieces of activities that are automated, targeted at the repetitive, well-known, mundane activities. This can free up people and resources to perform more innovative activities, and offer a more agile, speedy response from IT.

However, while automation is an important tool in the kit, it’s just one of the tools. The effort to automate complex environments is proportional to the complexity. Essentially, automation is just another generation of scripting of those activities that are running as part of operations designed to spawn and manage slave automation gofers.

The Rise of IT Operations Analytics

Given that changes to the operational model are almost guaranteed, a change in perspective is needed where IT operations takes a proactive approach to service management. Applying big data concepts to the reams of data collected by IT operations tools allows IT management software vendors to efficiently address a wide range of operational decisions. Because of the complexity of environments and processes and the dynamics of the environment, organizations need to have automation that is analytics driven.

With all of this data, IT Operations Analytics (ITOA) tools stand as powerful solutions for IT, helping to sift through all of the big data to generate valuable insights and business solutions. IT Operations Analytics can provide the necessary insight buried in piles of complex data, and can help IT operations teams to proactively determine risks, impacts, or the potential for outages that may come out of various events that take place in the environment.

Allowing a new way for operations to proactively manage IT system performance, availability, and security in complex and dynamic environments with less resources and greater speed, ITOA contributes both to the top and bottom line of any organization, cutting operations costs and increasing business value through both greater user experience and reliability of business transactions.

via What’s Driving Greater Adoption of IT Operations Analytics? | Data Center Knowledge.

tech360 post on http://betterhiring.com/women-in-tech-you-need-to-know/

Women in Tech You Need to Know 

Good news, according to a report released by the Center for American Progress:

The number of women-owned firms in the US grew by 59 percent from 1997 to 2013 — 1.5 times the national average.

Women of color are the majority owners at close to one-third of all women-owned firms in the nation.

African American women are both the fastest-growing segment of the women-owned-business population and the largest share of female business owners among women of color, at 13 percent.

Recently, I asked my folks to contribute names of impressive women in the STEM field who really have their boots on the ground. We got some really good responses, and have compiled an abbreviated list in no particular order. (You can read the full list here.)

1. Bindu Reddy, CEO and Co-Founder of MyLikes

Before starting MyLikes, Bindu was at Google and oversaw product management for several products including Google Docs, Google Sites, Google Video and Blogger. When she first started at Google, Bindu was a Product Manager for AdWords, where she improved the AdWords bidding model by introducing Quality Based Bidding and Quality Score for keywords. She was also in charge of Google’s shopping engine — Google Product Search and designed and launched Google Base.

Before Google, Bindu founded AiYo — a shopping recommendations service. Earlier in her career, Bindu was the Director of Product Management at eLance and a Computational Biologist at Exelixis.

2. Edie Stern, a distinguished Engineer and Inventor at IBM Edie has more than 100 patents to her name, and has been awarded the Kate Gleason Award for lifetime achievement. She received the award for the development of novel applications of new technologies. The 100 patents to her name represent her work in the worlds of telephony and the Internet, remote health monitoring, and digital media.

3. Ellen Spertus, Research Scientist at Google & Computer Science Professor at Mills University

Ellen’s areas of focus are in structured information retrieval, online communities, gender in computer science, and social effects of computing. She was a core engineer of App Inventor for Android, which enables computing novices to create mobile apps. and she co-authored a book on App Inventor.

Ellen has been working to bring more women into computing for decades now. In 1991, while studying computer science at MIT, she published a paper titled, “Why are there so few Female Computer Scientists.” And Ellen tells girls: “I’m sorry to tell you that Hogwarts isn’t real — but MIT is.”

via Women in Tech You Need to Know | Craig Newmark.

tech360 post on http://betterhiring.com/youtube-offering-bonuses-to-keep-talent-away-from-rivals-says-wsj/

YouTube offering bonuses to keep talent away from rivals, says WSJ

Google is throwing money at its YouTube stars to keep them away from a site that hasn’t even launched yet, according to the WSJ. Vessel, created by Hulu exec Jason Kilar, has offered some YouTube artists exclusive and lucrative deals to attract attention to its launch later this year. Other sites like Facebook and Crackle have also reportedly been poaching YouTube stars. The “broadcast yourself” site leans on talent like style coach Michelle Phan and comedian Colleen Ballinger (as Miranda Sings, above) to keep loyal channels fans engaged. But Phan, who had an early look at Vessel, called it “stunning,” and others have said that they were offered serious money for exclusive deals. Artists that stay loyal are making out better, though — on top of bonuses, YouTube has been offering rich funding deals to help select stars create new channels.

via YouTube offering bonuses to keep talent away from rivals, says WSJ.

tech360 post on http://betterhiring.com/how-to-hire-like-google-and-facebook-evaluating-candidates-beyond-their-technical-ability/

How To Hire Like Google And Facebook: Evaluating Candidates Beyond Their Technical Ability

In a previous Forbes post, we considered the disconcerting reality that even in the midst of an unemployment crisis, employers across industries are still unable to find the talent profiles they need. How is it possible that even highly educated candidates are unable to find skilled work when millions of open positions go unfilled? Evidence indicates that this talent gap is not due to the absence of technical skills, as one might expect, but rather to the absence of “soft skills,” or what we’ll call 21st century skills, in prospective candidates. These primarily refer to interpersonal and general analytic abilities like teamwork, empathy, leadership, negotiation, adaptability, and problem solving.

As we discussed, this is useful information for students and educators, but lessons from this research could be of particular benefit to employers, as well. The problem is that 21st century skills are very difficult to assess with any kind of rigor, especially before one can evaluate a candidate on the job. Can a candidate think innovatively? Collaborate with other team members? Assimilate feedback and coaching? Will the candidate be adaptable to new environments and successfully integrate with teams? It is very difficult to reduce these questions to discrete qualifications and quantifiable metrics in the same way we assess recognized degrees and numerical grades.

Certainly some approaches exist. For example, businesses have used “type”-based personality tests for decades in attempts to measure the soft skills of prospective candidates, assuming that certain personality types would correlate with high performance. One example is the Jung Typology Profiler for Workplace™ (JPTW), which purports to measure qualities such as “Power” (leadership potential), “Assurance,” “Visionary,” “Rationality,” and so forth.

Despite the promise of measuring key skills, the reality is that personality tests have serious methodological flaws and lack the statistical reliability to predict performance among prospective employees. For example, the Myers-Briggs Type Indicator (MBTI) is a closely-related profiler to the JPTW that also has its origins in Jungian typology from the early 20th century. The makers of the MBTI clearly state in their ethical guidelines that “It is unethical, and in many cases illegal, to require job applicants to take the Indicator if the results will be used to screen out applicants.” Because of their shared methodological limitations, the same restrictions should apply to the JPTW.

It’s clear that we need 21st century methods to assess 21st century skills. Unfortunately, that seemingly simple idea proves to be much trickier in practice than it is in theory.

Tools for talent development do not work for pre-employment screening

Part of the problem is that many companies are using the wrong tools for the job.   There is a fundamental difference between tools intended to develop existing teams and tools used for pre-employment selection.

For developing existing teams, there is evidence that “type”-based  personality tests can help managers better develop and deploy the talent they have already hired. For example, Gallup’s StrengthsFinder 2.0 is a tool that helps individuals understand and describe their own talents, and is commonly used by managers to understand and capitalize on the strengths of those they hire. More importantly, it is methodologically sound, and its reliability and validity are backed up by clear evidence.

For example, Facebook uses StrengthsFinder in a clever way to deploy talent efficiently. Regardless of the job openings they have available, Facebook simply hires the smartest people it can find, then uses StrengthsFinder results to understand their talents and create a job tailored to the candidate.

One might naturally assume that the same type of test that helps identify and develop strengths in an existing team could also be used to assess suitable candidates for entry into that team. In the words of Gallup, “Absolutely not… A development-oriented assessment such as StrengthsFinder is markedly different from selection tools because its purpose is not to assess whether an individual is suited for a particular job or role. Instead, it aims to provide talent insights for developing strengths within roles.”

Personality tests cannot be used for the same purpose as pre-employment selection tools because they simply can’t perform the key function: predicting employee performance. For example, two people who have the same set of innate strengths (according to a personality test) could have widely varying job performance. And of course, two people with a completely different set of strengths could do the same job equally well.

Pre-employment selection tools can predict employee performance on the job

Many pre-employment selection tools succeed at predicting performance because they have a completely different design than talent development tools like personality tests. Instead of seeking general traits and preferences, selection tools are tailored to a particular job in a particular organization, and are statistically calibrated to provide reliable predictive results (i.e., candidates who score highly on these tests also tend to perform well after they’re hired). In addition to the StrengthsFinder development tool, Gallup also offers these pre-employment selection tools, which include analytic services to confirm the validity and predictive value of the measures for candidate screening.

Pairin, Inc. is another organization that seeks to combine the personality test approach with specialized testing (for specific jobs, values, culture, etc.) as part of a pre-employment selection system. Using the Job Pairin System, employers can assess the presence of around 100 coachable/changeable behaviors such as emotional intelligence, leadership, attraction of followers, and even character.

A new spin on the behavioral interview

While services from Gallup and Pairin provide strong, evidence-based methods, the debate on using metrics to assess 21st century skills will certainly continue. For good or bad, it is unlikely that the traditional way to measure 21st century skills – the behavioral interview – will be unseated anytime soon. (Behavioral interviews are those that include situational questions like “Tell me about a time when you worked effectively under pressure.”)

Certainly, behavioral interviewing has problems of its own – for example, canned and otherwise disingenuous responses are all too common. While most companies still use a behavioral interviewing approach, those with top hiring practices are able to mitigate these issues. First and most importantly: skilled interviewers are often able to weed out rote responses by probing on the details of the situation discussed. This can help get the candidate “off script” and thus generate better insights about their true personality.

The behavioral questions themselves can also be written in a way that yields better insights. For example, Teach for America includes tough questions like “What would cause you to want to dropout of Teach For America if you were chosen?” Questions like these, for which the “obvious” answers might not be the best, could evoke a wider spread between canned responses and those that show more nuance and self-awareness.

As another example of innovation, Google also uses behavioral interviews, but structures them in a way that allows HR to perform analytics and prove that certain responses reliably predict employee performance.

Beyond the interview

Whatever method companies use to assess 21st century skills in prospective employees, it’s important that they reflect on the key principles behind the assessment approaches. Findings from research on 21st century skills provide an extremely valuable lens through which companies can view all interactions with candidates. Consider: What can you teach a new hire on the job, and what can you not teach? With information now abundantly available to us, almost anyone can learn basic Photoshop skills, for example, via online seminars. But what about skills like adaptability and empathy – can they be taught on the job?

via How To Hire Like Google And Facebook: Evaluating Candidates Beyond Their Technical Ability – Forbes.

tech360 post on http://betterhiring.com/data-driven-marketing-holds-the-key-to-sales-says-linkedin-exec-russell-glass/

Data-Driven Marketing Holds the Key to Sales Says Linkedin Exec Russell Glass

The rising importance of data to companies (organizations in general and marketing departments in particular) is changing the perception of marketing’s value. In fact, marketing is now so important that CMOs will make the best next-generation CEOs—thanks to their understanding of data and the customer.

Meet Dan Siroker, a new kind of marketer.

As the Obama campaign’s director of analytics in 2008, one of Siroker’s key responsibilities was optimizing the campaign’s website, a critical fundraising tool. Using sophisticated A/B testing, which involved comparing the results of 24 combinations of visuals, copy and calls-to-action, Siroker and his team identified the most effective combination for raising campaign funds from Obama supporters. Not only did this winning combination raise an extra $60 million for the campaign, as Siroker explained in this blog post, but the A/B testing also generated the data to prove it.

Marketing teams have historically found it hard to be considered a revenue center vs. a cost center. But when you generate $60 million—and show exactly how you did it—there’s no longer any doubt.

Now the CEO and co-founder of Optimizely, Siroker is just one of many pioneering, data-driven marketing executives who have become CEOs. Former marketing executive Paul Pellman was the CEO of Adometry before it was bought by Google earlier this year. Audi, Royal Dutch Shell, and Gilt Groupe have all recently named former marketing executives to CEO roles.

Here’s why this is a big deal Only the marketing department has a clear window on the behavior of the prospect during 90 percent of the buyer’s decision making—the time spent doing research via visits to websites, reading online reviews, connecting with peers on social media and conducting online searches.

With the data created by this online behavior, marketers possess tremendous insight into their companies’ potential customers. “When I tell people that we can know, in real time, every single visitor when they arrive on our site and know what company type they are from and that we can target specific titles or regions or individual companies, they’re blown away,” says Bill Macaitis, former CMO of Zendesk, describing the company’s ability to understand their prospects in real time.

Marketing now holds the key to sales commissions Marketing’s possession of this insight into the customer represents a huge shift from the past when the sales department played a much larger role in shepherding the prospect through the sales process. But now, the sales department has little direct knowledge of 90 percent of the buyer’s journey. It is now the marketing department, using data gleaned from the digital footprints left by prospects, that has the insight into this major portion of the sales process. And marketing can supply salespeople with exactly what they need: the qualified leads that are their lifeblood.

So data brings marketing and sales together. And because data can also identify deals that were marketing-sourced, the finance team also gains a new respect for marketing and its contribution to revenue. And finally, these changes have brought marketing closer together with the IT department, which helps install the marketing automation software, analytics tools and dashboards it needs to read the digital body language of customers and prospects.

Marketing is now at the nexus of business The CMO’s team has the clearest window into customer and prospect behavior. To sales, the CMO delivers the leads most likely to buy to sales. To finance, the CMO shows his or her team’s revenue contribution. And with IT, the CMO helps built out the marketing technology stack that mediates critical interactions with customers and prospects.

The winning companies of the future will be data-driven and customer-focused. No one is in a better position to lead this kind of company than the CMO—the executive who is eminently qualified to be your next CEO.

via Data-Driven Marketing Holds the Key to Sales Says Linkedin Exec Russell Glass | Adweek.

tech360 post on http://betterhiring.com/dont-rely-on-salary-data-to-pick-a-programming-language-to-learn/

Don't Rely On Salary Data To Pick A Programming Language To Learn

You can get paid a lot of money to code COBOL, but that’s probably a career-limiting choice. The less popular a language, the more an employer will be likely to pay. It’s a simple matter of supply and demand—or, as MongoDB’s Kelly Stirman defines it, “revenue potential and adoption [are] inversely proportional.”

Which is why Quartz’s list of the “most valuable programming skills to have on a resume” is wrong-headed and deceiving. Which programming language is “best” depends on a host of factors, perhaps the least important of which is how much that skill will pay you today.

Popularity Contests

After all, the best programming language may well be the one that is most likely to help you consistently find a job, not necessarily the one that pays best.

By that metric, Redmonk’s quarterly list of popular programming languages (culled from matching data from GitHub and Stack Overflow) may be a better place to start when figuring out which language to learn next:

Source: Redmonk

In this ranking, Java and JavaScript remain neck-and-neck for the top spot, with Google’s Go language rocketing up the charts to #21. So is one more important than the other?

Maybe.

As Pivotal’s chief scientist Milind Bhandarkar stresses:

Bhandarkar is correct, but while there may not be an objective way to evaluate the importance of programming languages across the industry, there is absolutely a subjective way for each developer to determine the best language for her. Namely, pick the language that matches where you see the future going.

Defining The Future

So, for example, cloud expert Simon Wardley notes, “If the Internet is the operating system then JavaScript is its language.”

And if you believe cloud is the future, well, Go should be high on your list, as it’s the “most interesting [language] in the cloud era” because it “solve[s] hard problems easily,” according to Red Hat’s Paul Lundin.

Mobile? Hard to argue against learning Swift (Apple) or Java (Android).

And if you don’t trust your own judgment, programming language popularity rankings like the one Redmonk assembles can provide a cheat sheet on the future. Just watch for big spikes in popularity like we’ve seen with Go.

Or look for relative popularity with employers, not ranked by salary but instead by volume of jobs. By that metric Ruby is waning, Python is relatively constant and Go is exploding, according to Indeed.com data. But if you really want to see hyper-growth, Node.js may best them all:

Source: Indeed.com

The Web, presumed dead, seems to be doing quite well.

Getting Paid To Code What You Love

Not that developers must always choose between future relevance and present salary. Quartz’s list sports a number of languages that both pay well and are popular, like JavaScript and Python (an excellent all-around language that doubles as a Big Data heavyweight):

Source: Quartz

Indeed, it’s unlikely that learning any programming language could be considered a bad investment these days, what with developers becoming market makers. Enterprises are falling all over themselves to hire and motivate developers, a trend that won’t diminish anytime soon.

With this in mind, do what you love. And code in the language that best expresses the future you most want to see. There’s never been a better time to be a developers, whatever the programming language you choose.

via Don’t Rely On Salary Data To Pick A Programming Language To Learn – ReadWrite.

tech360 post on http://betterhiring.com/google-is-funding-an-artificial-intelligence-for-data-science/

Google is funding “an artificial intelligence for data science”

Google is funding a project called Automatic Statistician that bills itself as “an artificial intelligence for data science,” it announced Tuesday. The project, which comes out of the University of Cambridge and is still in its early stages, aims to automate the selection, building and explanation of machine learning models.

In a nutshell, Automatic Statistician works by looking at a dataset and then determining which type of model would be best for analyzing it as well as which features, or variables, are the strongest. After the model runs, Automatic Statistician will return a text report explaining its findings in plain English — or as close as you can get when dealing with statistics.

  The project’s homepage quotes Google research scientist Kevin Murphy, who also wrote the blog post announcing Google’s funding for it, explaining the promise of Automatic Statistician like this:

The first problem is that current Machine Learning (ML) methods still require considerable human expertise in devising appropriate features and models. The second problem is that the output of current methods, while accurate, is often hard to understand, which makes it hard to trust. The “automatic statistician” project from Cambridge aims to address both problems, by using Bayesian model selection strategies to automatically choose good models / features, and to interpret the resulting fit in easy-to-understand ways, in terms of human readable, automatically generated reports.

However, Automatic Statistician isn’t the first attempt to deliver this type of service; there have, in fact, been multiple commercial attempts at doing similar things. The most accurate comparison might be to a now-defunct tool by machine learning startup Skytree called Skytree Adviser, which also automatically selected models and generated text reports of its findings. Startups including BeyondCore, Nutonian and even Ayasdi are all promising varying degrees of this functionality, as well.

As sexy as it is to talk about automating the data scientist job, though, it’s a bit early to suggest any software will eliminate the need for such employees any time soon. Even if projects like Automatic Statistician or commercial tools can make it possible for relative laypersons to run machine learning models and uncover patterns, that’s just a step or two down what’s often a much-longer path of turning insights into real value or, possibly, products.

via Google is funding “an artificial intelligence for data science” — Tech News and Analysis.

tech360 post on http://betterhiring.com/2015-technology-predictions-for-cios/

2015 technology predictions for CIOs

As we approach 2015, we asked a few Enterpriser IT executives what they see on the near horizon: trends, watch-outs, and best practices that will make their lives better – and more interesting – in the coming months. Here’s what they had to say:

1. Mobile exploits will rise sharply

“I think whether it’s next year or next week, we are due a major round of weaknesses and security breaches in the mobile space. At the moment, from what I’ve seen in the past and the development cycles of these things, the opportunity for the bad guys to create havoc in the mobile space has barely started.” – Cliff Tamplin, Consultant and Former Vice President of Technology Support & Risk Management, Hyatt Hotels Corporation

2. Docker will live up to the hype

“Docker will largely avoid the ‘trough of disillusionment’ and continue its growth as a cloud-enabling technology.” – Lee Congdon, CIO, Red Hat

3. SaaS and cloud growth will continue to spiral upward

“I see a continued migration to SaaS and cloud technologies that were previously considered premise-only concepts. I think that prices for cloud technologies will continue to drop as well. Amazon Web Services will see increased competition from Google and Microsoft, which will cause prices to drop, and price is one of the last barriers for traditional colocation-focused companies. – Aaron Stibel, Executive Vice President of Technology, Dun & Bradstreet Credibility Corp

4. Execs will schedule more time for work (not meetings)

“In the spirit of leading by example, one thing I plan to do in 2015 is leave my schedule open for at least 50 percent of the time. I’ve noticed that even if a meeting scheduled for an hour is over in 30 minutes, it will still stretch to take all of the hour. I think that’s waste, because most of these things can be done by email. Leaving my schedule open will allow people to walk into my office, talk to me, tell me what they are thinking, share their ideas, and have productive conversations. I plan to make it a point to leave my door open when my schedule is open, too, to create an environment where you can stop by and talk about ideas.” – Venki Rao, CIO, GE Digital Energy

5. Streaming video chips away at traditional TV

“Video streaming over the Internet will continue to make gains against the more traditional television business model in the United States.” – Lee Congdon, CIO, Red Hat

6. Higher digitization will move into every corner of life

“Think screens and sensors on mobile devices and on wearables, so the sensors in your clothes are starting to report into your Fitbit or whatever you own. This will drive interest around personal analytics and allow you to start drawing conclusions about the effects of an extra hour of sleep on your ability to keep off weight, and so on. I’m curious whether this will be a slow progression or whether it’s going to feel so far away and then suddenly cross over a tipping point. Sensors and beacons in retail are still far from common adoption, for example, but you have certain retailers trying things out, and I know there’s much more to come in that area.” –  Peter Buonora, Enterprise Architect, BJ’s Wholesale Club

7. Goodbye laptops, hello mobile devices

“The long-term decline of the laptop computer will continue as more applications move to the cloud and mobile devices.” – Lee Congdon, CIO, Red Hat

8. The customer will be king (even in IT)

“One thing I see becoming prevalent in leadership is to make customer service everyone’s job. In the past you could say we have a customer service team, we have a marketing team, we have a commercial team, and it’s their job. Right now, it’s everybody’s job. So no matter who does what, the customer comes first.  And your job is to service your customers.” – Venki Rao, CIO, GE Digital Energy

9. Cross-platform development will become the norm

“I can’t say I think the web per se is going to go away, but I would see a lot more cross-platform development, where all the things blend together. There are many new development tools out there, including some that enable you to develop once and deploy across iOS, Android, NativeWeb, everything else. So this blurring of the interface will continue to run the gamut.” – Cliff Tamplin, Consultant and Former Vice President of Technology Support & Risk Management, Hyatt Hotels Corporation

via 2015 technology predictions for CIOs | The Enterprisers Project.