What does Linkedin really mean to Microsoft?

Microsoft has stirred up a swirling buzz of discussion around the Linkedin acquisition for $26.2 billion. There are a number of angles that have been considered in the gazillion news stories floating around. Here’s a few of those threads:

  • Linkedin is a Salesforce counter by Satya Nadella — It has been argued by Steve Nellis and others that Linkedin’s efforts at developing and selling the tools in the company’s Sales Solutions unit have not gone very far, but the data in Linkedin’s network — when coupled with Microsoft’s own Salesforce competitor — Dynamics — could become a real player. Note that Nadella’s rumored efforts to acquire Salesforce stalled because of a too-high price tag (10X revenues), while Linkedin was much more affordable (7X revenues). Plus, with Linkedin in there are other angles to play.
  • Linkedin is a professional social network, and could counter Facebook for Business — Facebook has not yet released its business variant, Facebook for Business, but it’s supposed to roll out this year. Nadella might be trying to get there first by offering a fusion of Linkedin’s current mix of blogging, social networking, and recruitment use cases with Office 365 productivity options. Linking together the professional graph (Linkedin) with the work graph (Office 365)– as Nadella talked about in a call with the NY Times — and getting a premium on the integration of the two is probably a smart move so long as the seams can be made low friction. There is a devil in these details, but this is one of the most powerful visions for the merger.
  • Linkedin alone was a company with real problems — Linkedin stock got hammered earlier this year after lowered sales estimates. This would be bad in itself but doubly bad for Linkedin, since many of its best and brightest are compensated in part by stock grants, so when the stock falls, so does compensation. As a result, Linkedin was facing a mass exodus unless they could right the boat. This is one of the reasons Microsoft got the terms that it did. And now, people will be compensated in the more standard Microsoft way (as will the accounting for these expenses, which were clouded by non-GAAP practices).
  • Microsoft sees Linkedin as a way to deflect Slack — Personally, I don’t buy this conflation of threats to Microsoft. Yes, Slack is making huge inroads in work technology — specifically as the defining product in the exploding work chat space — but just because is has some of the features of a ‘social network’ (in that people are logged in for long periods of time each day, message each other, can coordinate outside of company boundaries) that doesn’t mean Slack and Linkedin are in some way head-to-head competitors. Yes, Slack is a competitor to Microsoft’s productivity/work technology products — most specifically Yammer, but also the core functionality slowly growing in Office 365 — but that doesn’t mean that Linkedin is intended as a Slack killer. Although Microsoft should be working on that, as well. I just don’t expect it will come from the Linkedin side of things.

After all the dust settles I expect that we’ll see a reoriented Linkedin, with a greater focus on CRM technologies and networking, and also a much enlarged focus on people operations (HR) technologies and networking, an area that Microsoft has functionally no offerings. This will take the form of enlarged platforms, and an ecology of partners building on Microsoft/Linkedin capabilities, as well as other, subsequent acquisitions. And Linkedin will immediately find its operational core — and culture — pulled toward CRM and HR by the Microsoft sales operation.
I also don’t believe that Jeff Weiner will be at Microsoft for longer than his required tenure, two years or whatever it is, and Kara Swisher agrees. More likely he will find new worlds to conquer, and Satya will find someone in Microsoft or Linkedin who will better execute what will rapidly become an integration strategy, rather than a trailblazing one.

Nimble HR is like Trello for hiring

I’ve written about Trello, the popular teak task management app designed around Kanban-style “boards” (see “Trello and Atlassian are quietly making inroads and announce new funding” and “The 2013 task management tools market”) Nimble HR is a “people operations” app that starts with a Trello-like user experience then turns into a social tool for hiring employees.

Nimble’s founder, Darren Bounds, tells me that the idea came from his experience using Trello when involved in hiring at another company. Trello worked well, but it remains a general purpose task-management tool. So Darren has built in the remaining 80 percent of the particulars of hiring.

Here’s a screenshot of the tool opened to a particular job. The various panels are the states for applicants. Note that the state changes are made by users either dragging and dropping candidates’ cards onto a panel or by automated mechanisms.


Below you can see a candidate’s card. Stacy may have initiated the process from one of the many job boards Nimble HR has partnered with, and the data from that site is mapped to the candidate card. Note that the social media handles are prepopulated by Nimble HR based on the email address. You can see that the team are sharing thoughts in the activity stream, which can be used to communicate with the applicant as well.


The usual conventions for social communication — @mentions, up votes, down votes — are supported. And the application has useful analytics for tracking progress, and other features.


Darren showed me a beta feature, which is in context video conferencing, which includes recording video sessions. These are managed in the activity stream with other artifacts, like files, chat, and state changes.

The tool integrates with others like Slack, Dropbox, Hipchat, and Google Apps.

Nimble HR is an amazingly intuitive social hiring tool, with what I think must be as close to a zero learning curve as is feasible. I expect that once Darren has rolled out a few more features — and raises some venture capital — he will start thinking about how to tackle the other parts of HR that are crying out for a new user experience.


Checkr gets $9M in the hot background checks market

Checkr is a competitor in the new hire background checks space, which is seeing a lot of growth due to the growth of freelance work platforms, like Homejoy, Instacart, and so on. The company has raised a round of $9 million, led by Accel Partners, with participation of Khosla Ventures, SV Angel, Data Collective and Google Ventures, and a long list of angels.

Checkr is unusual in that the company is providing an API to its customers — around 50 at the present time — who post information about new hires to Checkr’s background-checks-as-a-service offering, and a few days later Checkr posts results, which are based on both public and private data sources. These include criminal records, traffic violations, sex offender databases, and so on.

The reports cost $25-$35, based on degree of information desired.

Here’s an example record from the company website, in this case a positive search for someone on the US terrorist watch list:

Screenshot 2014-10-15 11.52.57

Checkr joins a small but extremely important group of companies that are providing businesses a critical service through APIs, like Stripe. The company has only four employees and is processing over 500 reports a day. Obviously the funding will allow them to expand considerably, and to compete more effectively with others, like Goodhire and BeenVerified. BeenVerified does have an API, but these older start-ups are organized around more traditional interactions with customers — through email and web pages.

The company was founded in April, and the founders met Accel partners at a Y Combinator Demo Day in August.

All watched over by machines of loving grace

I recently wrote about concerns about the role of big data that arose from Facebook’s research effort where the researchers sought to determine if emotional state could be manipulated by what appeared in their Facebook activity streams (see The fear of big data is growing). But directed efforts to shape our emotional state or to control our behavior are not the only ways that application of big data analysis might prove to be questionable.

Peter Capelli has posted a piece at the Harvard Business Review that poses some important questions about the application of big data and predictive analysis about future behavior and performance of individuals based on what big data may reveal. At core is the question of what businesses might do when confronted with the possibility of peering into the statistical future, and choosing who to hire — for example — based on big data-based predictions.

Peter Cappelli, We Can’t Always Control What Makes Us Successful

Many of the attributes that predict good outcomes are not within our control.  Some are things we were born with, at least in part, like IQ and personality or where and how we were raised.  It is possible that those attributes prevent you from getting a job, of course, but may also prevent you from advancing in a company, put you in the front of the queue for layoffs, and shape a host of other outcomes.

So what, if those predictions are right?

First is the question of fairness. There is an interesting parallel with the court system where predictions of a defendant’s risk of committing a crime in the future are in many states used to shape the sentence they will be given. Many of the factors that determine that risk assessment, some of which include things like family background that are beyond the ability of the defendant to control. And there has been pushback: is it fair to use factors that individuals could not control in determining their punishment?

Likening the assessment of an employee’s fate in a corporate downsizing to the judicial review of criminals may seem farfetched, but the parallels are obvious. The power lies in the hands of the courts and management in the two cases, and the employees and the criminals are powerless. One attribute of that powerlessness is that judges and management have access to statistical information — and its analysis — while the criminals and employees do not, in general.

Capelli makes an argument that the psychologists — who have been grappling with the ethics of human assessment in the enterprise for decades — are now being pushed aside by data scientists and software companies that are providing new ways to read the crystal ball. Instead of personality or IQ tests, machines are crunching big data, mined from hundreds or thousands of companies, that reveal who is most likely to be a good call center worker.

Xerox is using software from Evolv that is based on the analysis of the testing and performance tracking of tens of thousands of call center workers

Joseph Walker, Meet the New Boss: Big Data

By putting applicants through a battery of tests and then tracking their job performance, Evolv has developed a model for the ideal call-center worker. The data say that person lives near the job, has reliable transportation and uses one or more social networks, but not more than four. He or she tends not to be overly inquisitive or empathetic, but is creative.

Applicants for the job take a 30-minute test that screens them for personality traits and puts them through scenarios they might encounter on the job. Then the program spits out a score: red for low potential, yellow for medium potential or green for high potential. Xerox accepts some yellows if it thinks it can train them, but mostly hires greens.

The terminology — reds, yellows, greens — sounds more like the caste system of a dystopic science fiction novel than a contemporary business analytic tool, but it’s not. This is what is going on in business, today. And the reasons are simple, despite the ethical questions that accompany them. One driver for the rise of algorithmic HR is that people are bad at making hiring decisions: we have too many cognitive biases, and our capacity for balancing many independent factors for a candidate’s suitability for a job is limited. So the logical decision — as we have seen at Xerox — is to hand over the decision of who to hire and train to the machines.

The result is that there will be less turnover at Xerox, saving the company money, and the customers benefit from better customer support. The only ones iced out are the ‘reds’: those individuals who might have desired a job at the call center, but who will now have to find a job where their curiosity is a plus not a black mark.

The counter to Capelli’s concern should be the government or the education sector, who — armed with big data and analytic tools of their own — could be guiding those ‘reds’, and everyone else — toward the jobs and careers that line up with their gifts and backgrounds.

And the broadest ethical questions — like what to do about those raised in single parent homes in a world that might rate them a higher risk for all jobs — are beyond the scope of this analysis, today, but as Capelli points out, those questions need to be raised and answered by someone.

In a time when our institutions are in retreat, and the social contract between the worker and the business has been attenuated, you have to wonder who that someone is.

Can CultureIQ help companies manage culture?

I am a real believer in building in feedback into business, where management — and potentially all participants, depending on the degree of enlightenment of the senior team — can learn what the temper of the business is, and what needs to be paid attention.

As a result, I am always on the lookout for new approaches to what we might think of as culture monitoring tools, and in the largest context — when you include the notion of taking action to intentionally respond to what the measures suggest — to organizational culture management.

I had a chance to get a demo and briefing from the CEO of CultureIQ this week, Greg Besner. And what I saw I like.

The premise for CultureIQ is straightforward: companies should be polling their workers on a regular basis — annually or quarterly to discern what’s happening in various critical areas, like innovation, agility, environment, and others. This is the CultureIQ ‘full survey’, shown below. The CultureIQ is the aggregate of all metrics, and falls between 0 and 100.

Full Survey Dashboard

The questions in the survey have been designed to cover the full range of critical factors in business culture, according to Besner, an NYU professor. Note that users can add comments to the answers which in many cases are considered the best source of insight for management. Also Note that the solution is fully anonymized, so workers can speak openly.

The result of the full survey is a set of metrics in 9 areas.

Analytics Dashboard

On a more frequent schedule, the company can ask single, focused follow up questions, to take the pulse of the company between full surveys. These are called Pulse surveys.

CultureIQ surveys can be taken on mobile devices.

Full Survey Mobile (iPhone)



Besner’s solution also integrates with specific initiatives, such as mentoring, wellness, idea sourcing, and others. These are intended to shape the discussion and impact of company initiatives and their impact on worker engagement and job satisfaction.

I’m impressed with the design and philosophy of CultureIQ, and I intend to include the solution in a report later this year on Culture Management, where I will look more deeply into this product and others like tinyPULSE and 15five.


Parklet is a small-and-simple people operations toolset

I’ve decided to adopt the ‘people operations’ term from Google, Dropbox,  and others in place of ‘human resources’, principally because I don’t think that people are ‘resources’, but also because those companies that adopt the mindset of people operations have significantly happier workforces.

I read that a new startup, Parklet, had won the DEMO Enterprise Conference, following in the footsteps of WebEx, Evernote and Salesforce.

Parklet is building a tool kit for people operations support, relying on a small-and-simple design approach. The first two tools are these:

People —  is a new take on a company directory, but one with a moderate amount of interaction built-in. The orientation is toward two major issues: onboarding new employees by helping them get up to speed about the company history, culture, and people, and supporting interaction around public acknowledgement of help received or work done (‘props’).

This is the user landing page on a fictional company account, JobSpice. Note the interactive timeline that can be use to quickly set up a visualcompany history.

Screenshot 2014-05-18 15.09.21

Each user is made part of the company directory when invited, but can fill in details — like Twitter handle, department,  and so on — on their profile page.

Screenshot 2014-05-18 15.10.03

That info shows on the public profile for others to view, as shown below.

Screenshot 2014-05-18 15.10.26

A tree-form of the company organization can be used to find other people or clarify company structure.

Screenshot 2014-05-18 15.11.38

Pulse is the side of Parklet People that automatically creates a stream of activities, allowing users to get a sense of what is going on across the organization. Below, you can see that 13 new employees have joined JobSpice in the past two months, various folks have been giving others props, and Hannah Collins is a featured employee.

Screenshot 2014-05-18 15.34.16


Workflows — Parklet’s second app is Workflows, a tightly focused task management solution that is loosely coupled with People. Basically, Workflows provides the checklists that are associated with the lifecycles in people operations: hiring, provisioning, reviews, documentation, and at the other end, possibly dealing with issues relating to employee’s leaving the company

Screenshot 2014-05-18 15.40.02

Here, people operations and others can keep track of their tasks related to people, as opposed to other sorts of tasks.

My only quibble here is that if my company was using a solution like Asana or Smartsheets for task management, I might like an integration so that I could see these tasks in my current task client, but  I bet they’ll hear that request frequently.

As the CEO of Parklet, Dane Hurtubise, pointed out in the DEMO presentation, this is only the very beginning of tools that Parklet might roll out for people operations, a point of departure for employee engagement, employee satisfaction, and employee productivity.

I continue to believe that tightly focused and deep applications are the way forward for work management, and Parklet seems to be another entrant taking that road. I will have to follow their progress closely.