Thursday, August 25, 2011

How to Motivate Project Teams


Ultimately a project manager must determine the best method to motivate their team; the greatest leaders in business use oration to inspire; money to reward and business intelligence to analyze effectiveness.

Methods and Tests

Schwable states that there are the following motivationsi;
Intrinsic Motivation is classified as motivation that is derived from the nature of the work; ie; a boat builder probably enjoy's sailing, which may be why they studied the profession; a writer may enjoy writing; a programmer may enjoy thinking in mathematical abstraction or the challenge of reorganization abstracted data in a useful way.

Extrinsic Motivation is classified as the tratditional risk reward axis, reward of money for services rendered, risk of bieng unemployed or homeless. These are “Extrinsic” to the subject in question.

The following psychological models may be used;

Myers-Briggsii otherwise refereed to as the MTBI indicator test.

Abraham Maslow, and his Hierarchy of Needsiii

Frederick Herzberg, and his Hygienic theory behind the Motivation to work.iv

David McClelland developed the Thematic Aperception Test which is similar to a Roschact test and designed to be analyzed to discern the subjects unconscious intent. The formal methods include the DMM and SCOR standards.v

Douglas McGregor's Theory X and Thoery Y.

As with the information age, the nature and power of computers coupled with magnetic resonance imaging has allowed us to realize that most psychological arguments and models are incorrect in fact the entire ontology of human motivation is now being remapped within medical science; including the nature of being (self) and the nature of motivation; this shift in paradigms will supplant most psychology with functional neuroanatomy; where motivation is classified as a given state within a persons connectome as mapped by the anatomy of their mind.

The nature of human anatomy

Levey States the following about Motivation.vi
To relate motivation, a psychological concept, to a neurobiology substrate requires that this concept should be translated in operations relevant at the biological level. The term of motivation includes mental elementary processes decoding the emotional value of a stimulus (endogenous or exogenous) and integrating it into the elaboration, control and execution of goal-directed behaviors in order to ensure the maintenance of homeostasis, the well-being and survival of the individual and the species. Thus, in experimental condition, responses to aversive or appetitive situations are the classical markers of motivation. Consequently, the cerebral network of motivation particularly relates to the limbic system, i.e., the amygdala, the orbital and ventromedial prefrontal cortex, the anterior cingulum and the ventral striatum. Within this network, it is possible to distinguish: on one part structures such as the orbital and ventromedial prefrontal cortex, which are essential for the highest level of adaptive responses, allowing the individual to decode the variations of the emotional contingencies in real time, to integrate them into the behavior, and to maintain a behavioral choice during a long course, regardless of endogenous or environmental constraints; on the other part structures like the amygdala allow to build stable and invariants behaviors, that can be automatically activated and are essential for survival and avoidance of noxious situations”


Vilayanur Ramachandran states that the only difference between humans and their individual perception of reality is due to the input from their skin via the autonomous nervous system; which is located and occuled (limited or restricted) within the mirror neurons and the fusiform gyrus; both of these components of the human mind have evolved in the last 75,000 to 100,000 yearsvii leading to our use of language, fire tools and every last component in civilization; his research with functional MRI's and Phantom limb pain has shown that all abstracted thought is centered upon the fusiform gyrus located in annular gyrus region of the brain; in humans this portion is eight times larger than in other primates.viii Thus the nature of all abstracted thought, the center of all creativity lies in this area of the mind it is the intersection of stimuli of the visual, auditory and sensory regions; as he states it's the seat of self.

Management Tools


Motivational Theories since they are based in psychology are suspect as they lack objective specificity when compared to an FMRI study using modern medical techniques; however we may infer from Ramachandrands and Levy's findings that due to very basic motivation either greed or the desire for positive outcomes from various challenges as mentioned in Intrinsic and Extrinsic motivations as they filter through the structure of our minds as specific stimuli; these could theoretically be mapped with fmri to determine the exact areas of the mind the specific anatomy that objectively requires stimulation; however as Project managers we cannot implant neural stimulation devices and must substitute tangible rewards and penalties involving the models mentioned in this lecture which we hope have an equal net effect in said regions; these include monetary gain and peer acceptance, as well as loss and rejection. The old add age holds true that it is far easier to bait a horse than to whip it.

Influence And Power

Influence and power are mentioned by Schwable, however I have found that influence is subjective and power often fleeting; Power is too often abused by those that wield it to an end where the team is dissolved and the risk of failure is high.

Effectiveness

Determining effective methods for team motivation include developing a performance assessment program that is concise and driven by the subject in question; if we allow our team members to specify their respective goals than we may find that they will be aided or determine what these goals may be and may help formulate them in the process. This standard is practiced by a number of organizations; using training subsities and or mentoring programs are excellent methods to develop effective influence over employees and project members alike; the goal is to instill a relationship of trust and empowerment within the team to accomplish whatever task lies ahead, the methods used to do so are quite moot.



Distributed Projects

Since this discussion is about motivation in distributed projects, we can use the entire “Open Source” community as a refrence. RedHat, Ubuntu, Seles, Gentoo in fact every distribution of linux are developed as geographically diverse sets of programmers use standard and formal methods for revision control, auditing and review to develop large families of tool sets. A distribution is defeined by it's parent organization with respect to the organization they have a different business model than the traditional one of a software house in that by opening their code responsibilities to public editing they have further reduced the over all cost of development whilst only maintaining key control over functions and quality of the thousands of programs that make up an OS. Opensource and it's movement uses the primary motivation of programmers to distinguish themselves within their chosen peer group; the financal reward with this business model comes in the forms of consulting, support and administration of said systems. Organizations that make billions on their backs include SAP, IBM, Oracle and others.

The Truth about Managers

The truth about great project managers and leaders is that they do not manage at all; they simply find the best method to remove apathy from the team they are working with and find ways to challenge them to achieve the desired goal. I have in the past used only Expert Advice and Rapport alone to achieve our project goals as defined by my clients; these have included Compliance with SOX, Implementation of X509/ PKI systems according to federal government standards and distributed security systems; in each project I worked as a member of a team and my primary contributions apart from technical expertese was direction and guidance on how to achieve our desired goals.

References
iSchwable, Kathy; (Cenguage Learning, 2009) Informaiton Technology Project Management 6th ed ISBN:978-0-324-78692-7
iiMyers,Peter B; Briggs Isabel(Davies-Black Publishing, 1995). Gifts Differing: Understanding Personality Type. ISBN 0-89106-074-X
iiiMaslow, A. H. (Psycological Review, 50, 1943) A theory of Human Motivation [Online] World Wide Web, Avaiable from: http://psychclassics.yorku.ca/Maslow/motivation.htm (Accessed on August 24th 2011)
ivHerzberg, Fredrick; Mausner, Bernard; Synderman, Barbra Bloch (Transacation Publishers, 2009; 12th Reprint of John Wieley and Sons 1959 ed) The motivation to work ISBN: 1-56000-X
vWesten, Drew. (Journal of Personality Assessment, Volume 56, Issue 1 February 1991 ) Clinical Assessment of Object Relations Using the TAT. p. 56 - 74.
viLévy R. (Fédération de neurologie et Inserm U 610, Hôpital de la Salpêtrière, Paris., December 24th 2004) The neuroanatomy of motivation in man [Online] PDF Document, Available from: http://www.ncbi.nlm.nih.gov/pubmed/15683980 (Accessed on August 25th 2011)
viiVS Ramachandran (TED Talks, November 2009) The neurons that shaped Civilization [Online] Video Lecture, Ted Talk, avaiallbe from; http://www.ted.com/talks/vs_ramachandran_the_neurons_that_shaped_civilization.html (Accessed on August 25th 2011)
viiiS Ramachandran (TED Talks, March 2007) VS Ramachandran on Your Mind [Online] Video Lecture, Ted Talk, avaiallbe from; http://www.ted.com/talks/vilayanur_ramachandran_on_your_mind.html (Accessed on August 25th 2011)

Thursday, August 18, 2011

Zen and the art of the accurate estimate

Schwable states that Estimates are difficult for the following Reasonsi:
  • Estimates are done too quickly
  • Lack of Estimate Experience
  • Humans are biased towards underestimation
  • Management Desires Accuracy
In addition to these difficulties there are many methods that may be used to estimate the cost of a software project including:
  1. Top-Down Estimatesii
  2. Bottom Up Estimatesiii
  3. Parametric Modeling iv
  4. COCOMOv
  5. COSYSMOvi
  6. Event Chain Methodologyvii
  7. Function Pointsviii
  8. Program Evaluation Review Technique (PERT)ix
  9. Proxy Based Estimation (PROBE)x
  10. The Planning Gamexi
  11. Weighted Micro Function Pointsxii
  12. Wideband Delphixiii
Thus far within the confines of project estimation that we have examined the art of “triangulating” a project estimation method using a top-down and bottom up approach promises to be both the most efficent and accurate method; However Grimstad et al. State that one of the greatest risks of failure for any software project is a “Reliable cost estimate” as previously stated by various studies.xiv

The etymology of the term to “Estimate” is from Latin, and it's origin is a “Builders statement of projected costs”, from 1796 OED. Builders have the luxury of using tangible assets to develop costs upon.

Software is intangible, that is to say ultimately we may use metrics to measure software but these standards include “Guessing” how many lines of code may be required for a non-existant function, or how many man hours may be derived using Bohem's COCOMO estimates. Since software is based in the art of describing functions in a language of Mathematica abstraction, this abstraction itself further lends to the difficulties of developing an “estimate” of how many lines of code may be needed in what programming language for which function.

Given that we may select a methodology and develop metrics based upon empirical data with a given project; we may assume that we must use estimates based on previous projects with the same group of people, that is to say we must have previous work completed to compare against to help in developing a more accurate method to estimate future projects; this is a common practice derived primarily from fiscal budgeting and actuarial standards ; ie if a given business wishes to develop estimates of income they will use the previous years sales as a starting point; so to would a software development house use the previous years number of lines of code vs profit gained and man-hours of work as metrics for the next or any other quoted project.

The biggest problem in software cost estimation is the simple fact that even considering all of the research, and formal methods we may use; it's still just a very educated and formalized guess at a given cost.
Just as the old proverb states; the only constant in life is change; that is next to death and taxes, so given that the industry of software development is that with the greatest risk and potential for profit the amount of change within the software market in a given year is gargantuan when compared with more traditional areas or segments of industry.

The core business of mining resources for use has not changed in a millennia, neither has farming or travel; all of these sectors realize greater efficiencies in the information age by using software and automated systems along with great leaps in technology.

In the information age the rate of change and evolution is increasing as stated previously by Ray Kurtzweil; although he predicts systems with greater intelligence than their human agents at some point in the near future until then we are the agents of change within the software industry.

The biggest problem in developing accurate cost estimates for any given software project is change; Change in the scope of the project, change in the market forces driving the products development, internal recursive changes in the code used by the programmers to develop the project and a change in the project environment and business including change in it's risk profile or even change composition of the development and testing team of resources for said project.

We can model projects with a fair degree of accuracy given a few constants; these include the teams of people involved in the project, their expected salary, the variance in the software market which is far more volatile than most commodities and securities markets and the expected revenues from the project given previous years market data. However if any of those constants change with respect to the project then we must revisit it's model and cost estimate to maintain an accurate view.

A simple analogy for project costing would include how economists model the prime interest rate for a country. The models used over time vary; but the goal of the rate remains the same to maintain a stable level of inflation. 
They may use any models at their disposal or even develop custom models using automated systems but ultimately at the highest levels of research the numbers used for CPI, GDP and the like are aggregates of averages; thus the amount of removal or abstraction in the process may not compensate for a change in the global economic environment. These models are slow to react to change.

Thus any methodology used to develop cost models may use aggregates of averages or even aggregates of aggregates to develop a high level idea of what an enterprise spends on all of it's projects but ultimately these models are all so completely abstracted from reality that they must be sanity checked against expenditures to ensure that they hold any ounce of accuracy. Each of these processes is sensitive to change and although we excel at placing variance in an automated system; we still require experience and previous data upon which to develop our cost models. 
 
This reason alone is why many software startups fail, even why many business fail.
iSchwable, Kathy (Cengage Learning, 2010) Information Technology Project Management P.263 ISBN: 978-0-324-78692-7
iiSchwable, Kathy (Cengage Learning, 2010) Information Technology Project Management P.264 ISBN: 978-0-324-78692-7
iiiSchwable, Kathy (Cengage Learning, 2010) Information Technology Project Management P.264 ISBN: 978-0-324-78692-7
ivSchwable, Kathy (Cengage Learning, 2010) Information Technology Project Management P.265 ISBN: 978-0-324-78692-7
vBohem, Barry; Clark, Bradford; Horowitz, Ellis; Westland, Chris (USC, USC Center for Software Engineering, Annals of Software Engineering, 1995, 57-94)
viValderi, Ricardo (University of Sothern California, August 2005) THE CONSTRUCTIVE SYSTEMS ENGINEERING COST MODEL [Online] PDF Document, Avaialble from: http://csse.usc.edu/csse/TECHRPTS/PhD_Dissertations/files/Valerdi_Dissertation.pdf (Accessed on August 17th 2011)
viiAktasa , Nihat; de Bodta , Eric, Cousinb, Jean-Gabriel (IAG Louvain School of Management, Université catholique de Louvain, Belgium, November 13 2006) Event studies with a contaminated estimation period [Online] PDF Document, Avaialble from: http://www.sciencedirect.com/science/article/pii/S0929119906000290 (Accessed on August 17th 2011)
viiiCapers, Jones (McGraw-Hill, 2007) Estimating software costs: bringing realism to estimating P.246 ISBN: 978-0-07-148300-1
ixKeefer, Donald L.; Verdini, William A.; (Arazona State University, Departemnt of Decition and Information Systems, Management Science, Vol 39. No. 9 September 1995) Better Estimation of PERT Activity Time Paramaters [Online] PDF Document, Available from: http://www.jstor.org/pss/2632814 (Accessed on August 17th 2011)
xJohnson, Philip M.; Moore, Carleton A.; Dane, Joseph A.; Brewer , Robert S.; (Unversity of Hawaii, IEEE, 2000) Empirically-Guided Software Effort Guesstimation [Online] PDF Document, Avaialble from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.103.5058&rep=rep1&type=pdf (Accessed on August 17th 2011)
xiWilliam A. Wood, William L. Kleb (IEEE, NASA Langley Research Center, Issue 3, May / June 2003) Software Exploring XP for Scientific Research [Online] PDF Document, available from: http://doi.ieeecomputersociety.org/10.1109/MS.2003.1196317 (Accessed on August 17th 2011)
xiiSymons, Charles; (Proc. of the 4th European Conf. on Software, 2001) Comeback Function Point Analisys (Modernized) All is Forgiven! [Online] PDF Document, Avaialble from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.2999&rep=rep1&type=pdf (Accessed on August 17th 2011)
xiiiWiegers, Karl E. (Process Impact, 2000) Stop Promising Miracles [Online] PDF Document, Available from: http://www.uml.org.cn/SoftWareProcess/pdf/delphi.pdf (Accessed on August 17th 2011)
xivGrimstad, Stein; Jørgensen, Magne; Moløkken-Østvold, Kjetil; (Journal of Information and Software Technology 48(4):302-310 , 19 April 2005) Software Estimation Terminology: The Tower of Babel [Online] PDF Document, Availble from: http://simula.no/research/se/publications/Grimstad.2006.1 (Accessed on August 17th 2011)