IT Human Resources Management

Human resources management can also be termed “people management”. It is distinct from supply chain and technology management, being concerned with the identification and recruitment, onboarding, ongoing development of, and eventual exit of individuals from an organization. This brief section covers the topic as it relates to digital management, incorporating recent cases and perspectives.

Here is a typical hiring process:

Your organization has been hiring people for some time now. It has always been one of your most important decisions, but you have reached the point where a more formal and explicit understanding of how you do this is essential.

First, why do you hire new staff? How and when do you perceive a need? It is well established that increasing the size of a team can slow it down. Legendary software engineer Fred Brooks, in his work The Mythical Man Month, identified the pattern that “adding more people to a late project makes it later” [Brooks 1995].

Are you adding people because of a perceived need for specialist skills? While this will always be a reason for new hires, many argue in favor of “T-shaped” people – people who are deep in one skill, and broad in others. Hiring new staff has an impact on culture – is it better to train from within, or source externally?

Second, how are you hiring staff? In a traditional, functionally specialized model, someone in a human resources organization acts as an intermediary between the hiring manager, and the job applicant (sometimes with a recruiter also in the mix between the company and the applicant). Detailed job descriptions are developed, and applicants not explicitly matching the selection criteria (e.g., in their resume) are not invited for an interview.

Such practices do not necessarily result in good outcomes. Applicants routinely tailor resumes to the job description. In some cases, they have been known to copy the job description into invisible sections of their resume so that they are guaranteed a “match” if automated resume-scanning software is used.

A compelling case study of the limitations of traditional human resources-driven hiring is discussed by Robert Sutton and Huggy Rao in Scaling up Excellence: Getting to More without Settling for Less [Sutton & Rao 2014]. The authors describe the company Lotus^® Software, one of the pioneers of early desktop computing: “With [company founder] Kapor’s permission, [head of organizational development] Klein pulled together the resumes of the first 40 Lotus employees …​ [and] submitted all 40 resumes to the Lotus human resources department. Not one of the 40 applicants, including Kapor, was invited for a job interview. The founders had built a world that rejected people like them”.

Sean Landis, author of Agile Hiring [Landis 2011], believes that: “accepted hiring wisdom is not very effective when applied to software professionals”. He further states that:

In short, hiring is one of the most important decisions the digital enterprise makes, and it cannot be reduced to a simple process to be executed mechanically. Requiring senior technical talent to interview candidates may result in improved hiring decisions. However, such requirements add to the overall work demands placed on these individuals.

Finally, it is important to understand the costs of a bad hire. One risk is hiring “toxic” individuals who do not work well with others, degrade team morale, and even drive good employees to leave.

Recent research by Michael Housman and Dylan Minor suggests that while the benefit from hiring a highly qualified “superstar” worker at most is $5,303, the cost of hiring a “toxic” worker (one destructive of morale and team norms) averages $12,489 – certainly a risk to consider [Housman & Minor 2015].

Sometimes new employees come in expecting that you are following certain processes. This is in part because “process” experience can be an important part of an employee’s career background. A skilled human resources manager may consider their experience with large-scale enterprise hiring processes to be a major part of their qualifications for a position in your company.

This applies to both “business” and “IT” processes. In fact, in the digital world, there is no real difference. Digital processes:

It is not clear which of these are “IT” versus “business” processes. But they are definitely processes. Some of them are more predictable, some less so, but they all represent some form of ordered work that is repeatable to some degree. And to some extent, you may be seeking people with experience defined at least in part by their exposure to processes.

Human resources departments are frequently responsible for education and training. Sometimes, employees take trainings and then through some form of examination or other proof, achieve a “certification” which can further their career. ITIL and PMBOK have been well-known IT certifications offered to individuals.

More recently, organizations have embraced a “dojo” approach; immersive environments where entire teams are trained [Schwartz & Schauer 2016]. Such approaches focus more on learning by doing, as opposed to passing multiple-choice tests (the basis of basic ITIL and PMBOK certification).

When a new hire enters your organization, they enter a complex system that will structure and direct their daily activities through a myriad of means. The various means that direct their action include:

Notice again the appearance of the “three Ps”.

Product, project, and process become challenging when they are all allowed to generate demand on individuals independently of each other. In the worst-case scenario, the same individual winds up with:

When demand is un-coordinated, these multiple channels can result in multi-tasking and dramatic overburden and, in the worst case, the individual becomes the constraint to enterprise value. Project managers expect deliverables on time, and too often have no visibility to operational concerns (e.g., outages) that may affect the ability of staff to deliver. Ad hoc requests “smaller than a project, bigger than a ticket” further complicate matters.

The Phoenix Project presents an effective and realistic dramatization of the resulting challenges. Work is entering the system through multiple channels, and the overburden on key individuals (such as Brent, the lead systems engineer) has reached crisis proportions. Through a variety of mechanisms, they take control of the demand channels and greatly improve the organization’s success. One of the most important lessons is well articulated by Erik, the mentor: “Your job as VP of IT Operations is to ensure the fast, predictable, and uninterrupted flow of planned work that delivers value to the business while minimizing the impact and disruption of unplanned work, so you can provide stable, predictable, and secure IT service …​ You must figure out how to control the release of work into IT Operations and, more importantly, ensure that your most constrained resources are doing only the work that serves the goal of the entire system, not just one silo” [Kim et al. 2013].

In order to understand the work, measuring the consumption of people’s time is important. There are various time-tracking approaches:

There is little industry consensus on best practices here. There are reasonable concerns about the burden of time tracking on employees, and poor data quality resulting from employees attempting to “code” activities when summarizing their time on a weekly or bi-weekly basis.

Regardless of whether the company is a modern digital enterprise or more traditional in its approach, the commitment, performance, and results of employees are critical concerns. The traditional approach to managing this has been an annual review cycle, resulting in a performance ranking from 1 to 5:

This annual rating determines the employee’s compensation and career prospects in the organization. Some companies, notably GE™ and Microsoft, have attempted “stack rankings” in which the “bottom” 10% (or more) performers must be terminated. As the Davis and Daniels quote above indicates, such practices are terribly destructive of psychological safety and therefore team cohesion. High-profile practitioners are therefore moving away from this practice (Brustein 2013 and Olson 2013).

The traditional annual review is a large “batch” of feedback to the employee, and therefore ineffective in terms of systems theory, not much better than an open-loop approach. Because of the weaknesses of such slow feedback (not to mention the large annual costs, expensive infrastructure, and opportunity costs of the time spent), companies are experimenting with other approaches.

Deloitte^® Consulting LLP, as reported in the Harvard Business Review [Buckingham & Goodall 2015], realized that its annual performance review process was consuming two million hours of time annually, and yet was not delivering the needed value. In particular, ratings were suffering from the measurable flaw that they tended to reveal more about the person doing the rating, than the person being rated!

They started by redefining the goals of the performance management system to identify and reward performance accurately, as well as further fueling improvements.

A new approach with greater statistical validity was implemented, based on four key questions:

In terms of the frequency of performance check-ins, they note: “…​ the best team leaders …​ conduct regular check-ins with each team member about near-term work …​ to set expectations for the upcoming week, review priorities, comment on recent work and provide course correction, coaching, or important new information …​ If a leader checks in less often than once a week, the team member’s priorities may become vague …​ the conversation will shift from coaching for near-term work to giving feedback about past performance …​ If you want people to talk about how to do their best work in the near future, they need to talk often …​” [Buckingham & Goodall 2015].

Sutton and Rao, in Scaling up Excellence, discuss the similar case of Adobe^®. At Adobe, “annual reviews required 80,000 hours of time from the 2,000 managers at Adobe each year, the equivalent of 40 full-time employees. After all that effort, internal surveys revealed that employees felt less inspired and motivated afterwards – and turnover increased”. Because of such costs and poor results, Adobe scrapped the entire performance management system in favor of a “check-in” approach. In this approach, managers are expected to have regular conversations about performance with employees and are given much more say in salaries and merit increases. The managers themselves are evaluated through random “pulse surveys” that measure how well each manager “sets expectations, gives and receives feedback, and helps people with their growth and development” [Sutton & Rao 2014].

Whether incentives (e.g., pay raises) should be awarded individually or on a team basis is an ongoing topic of discussion in the industry. Results often derive from team performance, and the contributions of any one individual can be difficult to identify. Because of this, Scrum pioneer Ken Schwaber argues that: “the majority of the enterprise’s bonus and incentive funds need to be allocated based on the team’s performance rather than the individual’s performance” [Schwaber 2007]. However, this runs into another problem: that of the “free-rider”. What do we do about team members who do not pull their weight? Even in self-organizing teams, confronting someone about their behavior is not something people do willingly, or well.

Ideally, teams will self-police, but this becomes less effective with scale. In one case study in the Harvard Business Review, Continental Airlines found that the free rider problem was less of a concern when metrics were clearly correlated with team activity. In their case, the efforts and cooperation of gate teams had a significant influence on On-Time Arrival and Departure metrics, which could then be used as the basis for incentives [Knez & Simester 2002].

Ultimately, both individuals and teams need coaching and direction. Team-level management and incentives must still be supplemented with some feedback loops centering on the individual. Perhaps this feedback is not compensation-based, but the organization must still identify those with leadership potential and deal with free riders and toxic individuals.

Observed behaviors are a useful focus. Sean Landis describes the difference between behaviors and skills as follows: “Two things make good leaders: behaviors and skills. If you focus on behaviors in your hiring of developers, they will be predisposed for leadership success. The hired candidate may walk in the door with the skills necessary to lead or not. If not, skills are easy to acquire through training and mentoring. People can acquire or modify behaviors, but it is much harder than skill development. Hire for behaviors and train the leadership skills.” [Landis 2011]

He further provides many examples of behaviors, such as:

Evidence of Notability

Many executives and military leaders have identified the central importance of hiring decisions. In large, complex organizations, choosing the right people is the most powerful lever a leader has to drive organizational performance. The organizational context these new hires find themselves in will profoundly affect them and the results of their efforts.

Limitations

Hiring the right individuals will not lead to organizational success if other aspects of the operating model are ineffective; e.g., demand and execution management that encourage too much work-in-process.

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