Wednesday, January 23, 2008

3) Activity Control Versus Outcome Control

Now we are getting down to the nitty-gritty of why the majority of CRM initiatives fail. For most CRM initiatives to succeed, users must be willing to record their activities with customers. The benefits in doing so cannot be denied however in most cases, users strongly resist entering their customer activities into CRM, forgoing the benefits of doing so and despite their assurances that they will use the tool. From my research, I now believe this "Trust Dilemma" is articulated very well in a quote by Douglas Hartle

"It is a rare dog that will carry the stick with which it is to be beaten."


Perfect Versus Imperfect Knowledge (Outcome control versus activity control)
Typically, evaluative processes in business are focused on outcome controls such as sales numbers and product mix because sophisticated ERP systems should provide perfect knowledge of these results.
Perfect knowledge in activity control is rare in that it involves knowing exactly what steps were done by individuals that led to the (overall) documented outcomes, as well as the results of each individual activity.

Current examples of perfect knowledge in activity control include:



  • Professional televised sports where the activities of each individual player and position are recorded during play using video and manual documentation by others. Combined with the final game result and individual player statistics, this information exists as perfect knowledge of individual activities and overall team performance.



  • High level chess where player moves and counter moves are documented and published along with results. 2,138 games played by chess master Garry Kasparov, against all opponents, have been meticulously recorded showing each move and countermove by each player, and the final result of each game.
    The benefits of perfect knowledge of past activities (and results) by coaches and upcoming opponents are obvious. Such knowledge allows for decisions to be made and strategies to be created that can dramatically affect future outcomes. An important note
    here is since, in these two examples, every activity and result is always recorded without input from the players themselves, players cannot choose to “opt out” of activity controls, if they wish to continue to receive the benefits of being in the game. This study will attempt to demonstrate the length that players will go through to “opt out” of activity-based control systems that do not provide a disproportionately larger reward to perceived risk ratio.














Hypothetical Suppositions
If an active, professional basketball player could, through self-effort, remove their image from all previous game recordings (Activity controls), so only their comprehensive individual and team outcomes (Stats) remained http://www.databasebasketball.com/about/aboutstats.htm
-Would they choose this option?
-If yes, would they encourage others on their team to do the same?
-What if they were given the option of only removing themselves from select games?
It is conceivable that players would prefer outcome controls over activity controls, particularly during “Slumps” or if they received any negative feedback based on activities, rather than outcomes. This decision would be much easier if other players also opted out of activity controls to spread the blame or justify the decision.
If, when Garry Kasparov was actively playing chess, he could choose, through self-effort, to remove his previous individual moves from public record, leaving only win/lose outcomes http://www.chessgames.com/perl/chessplayer?pid=15940
-Would he have chosen this option?


“CRM has to be easy for users to input their activities into or they won’t use it”
How easy does CRM have to be for users to input their activities?
Before one can answer this question, it is important to look at user resistance to automatic activity control systems in use, that require no effort by users to provide the information about their activities.

Opting out of a non-user-inputted, automated activity control

For users that have been assigned an automated activity control system, any opportunity or decision, to disengage or “mutiny against” the control system, will be weighed against perceived value or penalty by the user in doing so. One such anecdotal example came out of a conversation with a friend that has served with the Canadian military in Afghanistan. All Canadian military personnel are equipped with GPS transmitters that provide their information and location, to officers remotely guiding their actions. These GPS transmitters are used both in non-combat maneuvers here in Canada as well as in combat situations in Afghanistan. The purpose of GPS in training situations, is primarily to evaluate the activities and movements of troops as they perform their maneuvers to documented results (Low Cards).This information provides perfect knowledge of user activities and subsequent results, without any effort required by users to provide the information. Unlike peacetime training, in combat situations air cover is provided and GPS information is used to keep bombs from being dropped on troops and to generally keep them out of harms way (High Card), as well as activity controls. While activity control in peacetime serves to prepare troops for combat situations and thus protect them from harm, the perceived value by troops is far less and “Big Brother” is the common term used to describe GPS-based activity controls in training situations. My friend confided that a course of action sometimes taken by troops during training, is to turn off the GPS transmitters whenever possible. This collaborative, “Mutiny” approach against the “Low Card” activity controls, are often endorsed by junior officers that are held accountable for activity control information gathered about troops under their command. The same users, I was told, would never consider “opting out” in combat by disabling their GPS transmitters because the perceived value of higher safety outweighs activity controls.

Customer benefit is often weighed against the self-interests in activity controls
No where is this statement more appropriate than in the bitter battle between Yellow Cab drivers in New York City (NYC) and the Taxi and Limousine Commission (TLC) regarding the “Low card” activity controls of drivers using Global Positioning System (GPS) transmitters. Historically, NYC Taxis were not dispatched but were “flagged” by passengers and only accepted cash as payment. Manual “Trip sheets” were maintained by drivers listing pickup and drop-off points and the fare amount. This documentation formed the basis of declared income by drivers. In 2005 the TLC mandated that as of October, 2007, all NYC Taxis must have GPS transmitters installed with passenger terminals that also allow passengers view their location and pay by credit card. Passenger pickup and drop-off points with fare paid are recorded automatically recorded by the GPS units and transmitted real-time to the TLC. This system eliminates manual trip sheets and provides the TLC with an accurate and unbiased view of NYC Taxi driver activities and income. Many punitive controls have been put into place by the TLC to ensure compliance by drivers and continuous system usage is mandatory for employment
NYC taxi drivers have rallied heavily against these new “Low Card” activity controls, complaining about the cost of the units as well as the loss of privacy and autonomy. Interestingly, no statements by drivers admit the benefit to passengers of paying by credit card, nor address the (unsubstantiated) possibility that drivers rely on undeclared income made easier in a manual trip sheet system. TLC statements have focused on benefits to
passengers and for drivers, the end to manual trip sheets. To my knowledge, driver income accuracy has not been addressed in statements by the TLC except that the automated trip reports will only be available to the IRS by subpoena. The TLC has also addressed driver concerns regarding the issuance of tickets for traffic by stating “There are currently no plans to issue traffic citations based on GPS data.”

Hypothetical Suppositions
When the IRS is aware that automated, accurate records of taxi-driver income are available, will subpoenas for these records increase over those for the manual trip sheets?
If a taxi-driver is involved in a traffic accident and there will be a GPS record of how fast the cab was travelling, will the claimant demand the record?
If the TLC receives traffic complaints about drivers, will they be forced to look at GPS driver data?
Can activity control (Low card) data such as this be left unused once its existence is known?

Automating the decision to “Do the right thing”

If toll booths were completely run on the “Honor System” without automated enforcement, would drivers stop to pay the toll for the good of all or would they justify to themselves why they do not need to pay?

If the TLC allowed cab drivers to choose whether or not to install GPS and rely on “Market forces” instead, would drivers install the units to the benefit of passengers or justify to themselves why they do not need such activity controls?

When police departments can decide whether or not to have forward facing video cameras in their patrol cars, why does it usually only come about after racial-profiling lawsuit settlements?

A study on medical morbidity published in 2003 by Folkman, McPhee and Lo found that of training physicians who made serious errors causing death or injury to patients:
  • Only 54% shared the error with a colleague
  • Only 24% told the family of the patient

The bottom line is that people are highly resistant to providing any information on their activities that can be used against them.

My next post will explore how CRM can actually succeed if activity control elements are replaced by P.A.C.T.

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