A Consultant's Casebook

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The Dynamics of Change

From the brief discussion above, it is clear that the recruiter can have considerable effect on his performance.  He works, however, within a mission context.  And, his mission context requires him to pace his work so that he meets the steady demands of his mission.  His perception may well be that if he works too fast, he will squander his pool of leads and prospects and be unable to make mission in the last months of the year.

So, the recruiter learns to balance his work with the current mission requirements.  He prospects enough to maintain a pool of prospects, spends as much time as necessary to sell each prospect, and prepares them for enlistment  processing as the situation demands.  When it is late in the mission month and he is behind, he will sell faster and better prepare his applicants for processing.  When it is early in the mission month, or he is ahead, he can afford to send even mildly interested prospects to the enlistment station, and can take the luxury of working with these mildly interested prospects for as long as he or she wants.

Suppose, that a recruiter has worked himself into a comfortable pattern.  He has balanced his activities so he can achieve mission steadily.  But, 4 months into the year (say at day 74 in our graphs) his mission is increased by 25%.  Now, instead of needing 13 contracts by the end of the year, he is required to have 16.  Regardless of how easily he was making mission during the first 74 days, the new requirement necessitates re-balancing the system.  The recruiter must alter his behavior to achieve a new system balance that will result in more contracts.

The problem of re-balancing the system is precisely that illustrated by the shower analogy.  (There is a complex system behind the shower wall, and there are relatively few controls available with which to balance the system.)  Worse, there is a great deal of delay between the time the recruiter makes an adjustment to his performance, and the time that this behavior results in a contract.  Recall, that such delay typically results in aggressive adjustments (like with the faucet) and likely result in a pattern of dampening oscillations in the performance measure.

Assume, that when the mission is increased, the recruiter does everything in his power to respond to the new demands.  As discussed above, we identified two factors under his control and which will have an effect.  The first is the average number of days spent selling a prospect.  The second is the average number of days necessary for enlistment processing.  By improving his sales technique and more carefully preparing an applicant for processing, a motivated recruiter can affect his performance.  But consider how long it will take a system such as described to respond to a recruiter's efforts.

The figure above summarizes what happens to the recruiting system when the recruiter is notified on day 74 of an increased mission.  Line 1 of presents the baseline of contract performance as established by the basic model.  Assume that the motivated recruiter expends maximum effort to work harder and faster.  He decreases the average sales time from 2 days to 1.  Simultaneously, he prepares applicants more thoroughly for processing, reducing the average processing time from 10 days to 5.  Line 2, above, illustrates the effects of the recruiter's improved performance.

Despite the dramatic effects on factors with known influence on performance, there is a considerable lag time before performance begins to improve.  In fact, it takes 62 days or (3.4 months of 18.4 working days per month) before Line 2 consistently outperforms Line 1.  Thus, for recruiting, it appears that it takes almost 3 1/2 months to "turn the force."

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[1]For an especially  dramatic illustration, see The Face of Battle, by John Keegan, Penguin, New York, 198?.  Keegan suggests that in battle, small cohesive units can withstand almost any odds, yet become completely vulnerable to weak assault when their cohesion disintegrates.

 
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Last modified: October 19, 2000