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PeopleAnalyst Code of Conduct

Table of Contents

Competence
Scope of Professional Services
Communication
Confidential Information
Conflicts of Interest
Duties to Client
Evidence, Quality of Data and Quality of Evidence
Misconduct
Terminology

Competence

People Analyst shall provide competent People Analytics professional services to a client. Competent People Analytics professional services requires the knowledge, skill, thoroughness and preparation reasonably necessary for the services.

Scope of Professional Services With Client

(a) Subject to paragraphs (b), People Analyst shall abide by a client's decisions concerning objectives of the services and shall consult with the client as to the means by which they are to be pursued. People Analyst may take such action on behalf of the client as is impliedly authorized to carry out People Analytics professional services.

(b) People Analyst shall not counsel a client to engage, or assist a client, in conduct that the People Analyst knows is criminal or fraudulent, but People Analyst may discuss the consequences of any proposed course of conduct with a client and may counsel or assist a client to make a good faith effort to determine the validity, scope, meaning or application of the People Analytics provided.

Communication with Clients

(a) People Analyst shall:
(1) reasonably consult with the client about the means by which the client's objectives are to be accomplished;
(2) act with reasonable diligence and promptness in providing services;
(3) keep the client reasonably informed about the status of the People Analytics services;
(4) promptly comply with reasonable requests for information;
(5) consult with the client about any real, perceived and potentially hidden risks in relying on People Analytics results; and
(6) consult with the client about any relevant limitation on the People Analyst's conduct when the People Analyst knows that the client expects assistance not permitted by the Code of Professional Conduct or other law.

(b) People Analyst shall explain People Analytics results to the extent reasonably necessary to permit the client to make informed decisions regarding the People Analytics.

Confidential Information

(a) Confidential information is information that the People Analyst creates, develops, receives, uses or learns in the course of employment as People Analyst for a client, either working directly in house as an employee of an organization or as an independent professional. It includes information that is not generally known by the public about the client, including client affiliates, employees, customers or other parties with whom the client has a relationship and who have an expectation of confidentiality. The People Analyst has a professional duty to protect all confidential information, regardless of its form or format, from the time of its creation or receipt until its authorized disposal.

(b) Confidential information is a valuable asset. Protecting this information is critical to a People Analyst's reputation for integrity and relationship with clients, and ensures compliance with laws and regulations governing the client's industry.

(c) People Analyst shall protect all confidential information, regardless of its form or format, from the time of its creation or receipt until its authorized disposal.

(d) People Analyst shall not reveal information relating to the representation of a client unless the client gives informed consent, the disclosure is impliedly authorized in order to carry out the representation or the disclosure is permitted by paragraph (e).

(e) People Analyst may reveal information relating to the representation of a client to the extent the People Analyst reasonably believes necessary:

(1) to prevent reasonably certain death or substantial bodily harm;
(2) to prevent the client from committing a crime or fraud that is reasonably certain to result in substantial injury to the financial interests or property of another and in furtherance of which the client has used or is using the People Analyst's services.

(f) People Analyst shall make reasonable efforts to prevent the inadvertent or unauthorized disclosure of, or unauthorized access to, information relating to the representation of a client, which means:

(1) Not displaying, reviewing or discussing confidential information in public places, in the presence of third parties or that may be overheard;
(2) Not emailing confidential information outside of the organization or professional practice to a personal email account or otherwise removing confidential information from the client by removing hard copies or copying it to any form of recordable digital media device; and
(3) Communicating confidential information only to client employees and authorized agents (such as attorneys or external auditors) who have a legitimate business reason to know the information.

(g) People Analyst shall comply with client policies that apply to the acceptance, proper use and handling of confidential information, as well as any written agreements between the People Analyst and the client relating to confidential information.
(h) People Analyst shall protect client confidential information after termination of work for the client.
(i) People Analyst shall return any and all confidential information in possession or control upon termination of the People Analyst client relationship and, if requested, execute an affidavit affirming compliance with obligations relating to confidential information.

Conflicts of Interest

(a) Except as provided in paragraph (b), People Analyst shall not provide professional data science services for a client if the services involves a concurrent conflict of interest. A concurrent conflict of interest exists if:

(1) providing services for one client will be directly adverse to another client; or
(2) there is a significant risk that providing professional People Analytics services for one or more clients will be materially limited by the People Analyst's responsibilities to another client, a former client or a third person or by a personal interest of the People Analyst.

(b) Notwithstanding the existence of a concurrent conflict of interest under paragraph (a), a People Analyst may represent a client if:

(1) the People Analyst reasonably believes that the People Analyst will be able to provide competentand diligent services to each affected client;
(2) the professional People Analytics services is not prohibited by law; and
(3) each affected client gives informed consent, confirmed in writing.

Duties to Prospective Client

(a) A person who consults with People Analyst about the possibility of forming a client relationship with respect to a matter is a prospective client.

(b) Even when no client People Analyst relationship ensues, People Analyst who has learned information from a prospective client shall not use or reveal that information.

(c) People Analyst subject to paragraph (b) shall not provide professional People Analytics services for a client with interests materially adverse to those of a prospective client in the same or a substantially related industry if the People Analyst received information from the prospective client that could be significantly harmful to that person in the matter, except as provided in paragraph (d).

(d) When the People Analyst has received disqualifying information as defined in paragraph (c), providing professional People Analytics services is permissible if: 

(1) both the affected client and the prospective client have given informed consent, confirmed in writing, or:
(2) the People Analyst who received the information took reasonable measures to avoid exposure to more disqualifying information than was reasonably necessary to determine whether to provide professional People Analytics services for the prospective client; and written notice is promptly given to the prospective client.

Evidence, Quality of Data and Quality of Evidence

(a) People Analyst shall inform the client of all People Analytics results and material facts known to the People Analyst that will enable the client to make informed decisions, whether or not the People Analytics evidence are adverse.

(b) People Analyst shall rate the quality of data and disclose such rating to client to enable client to make informed decisions. The People Analyst understands that bad or uncertain data quality may compromise People Analytics professional practice and may communicate a false reality or promote an illusion of understanding. The People Analyst shall take reasonable measures to protect the client from relying and making decisions based on bad or uncertain data quality.

(c ) People Analyst shall rate the quality of evidence and disclose such rating to client to enable client to make informed decisions. The People Analyst understands that evidence may be weak or strong or uncertain and shall take reasonable measures to protect the client from relying and making decisions based on weak or uncertain evidence.

(d) If People Analyst reasonably believes a client is misusing People Analytics to communicate a false reality or promote an illusion of understanding, the People Analyst shall take reasonable remedial measures, including disclosure to the client, and including, if necessary, disclosure to the proper authorities. The People Analyst shall take reasonable measures to persuade the client to use People Analytics appropriately.

(e) If People Analyst knows that a client intends to engage, is engaging or has engaged in criminal or fraudulent conduct related to the People Analytics provided, the People Analyst shall take reasonable remedial measures, including, if necessary, disclosure to the proper authorities.

(f) People Analyst shall not knowingly: 
(1) fail to use scientific methods in performing People Analytics;
(2) fail to rank the quality of evidence in a reasonable and understandable manner for the client;
(3) claim weak or uncertain evidence is strong evidence;
(4) misuse weak or uncertain evidence to communicate a false reality or promote an illusion of understanding;
(5) fail to rank the quality of data in a reasonable and understandable manner for the client;
(6) claim bad or uncertain data quality is good data quality;
(7) misuse bad or uncertain data quality to communicate a false reality or promote an illusion of understanding;
(8) fail to disclose any and all People Analytics results or engage in cherry picking;
(9) fail to attempt to replicate People Analytics results;
(10) fail to disclose that People Analytics results could not be replicated;
(11) misuse People Analytics results to communicate a false reality or promote an illusion of understanding;
(12) fail to disclose failed experiments or disconfirming evidence known to the People Analyst to be directly adverse to the position of the client;
(13) offer evidence that the People Analyst knows to be false. If People Analyst questions the quality of data or evidence the People Analyst must disclose this to the client. If a People Analyst has offered material evidence and the People Analyst comes to know of its falsity, the People Analyst shall take reasonable remedial measures, including disclosure to the client. A People Analyst may disclose and label evidence the People Analyst reasonably believes is false;
(14) cherry pick data and People Analytics evidence.

(g) People Analyst shall use reasonable diligence when designing, creating and implementing algorithms to avoid harm. The People Analyst shall disclose to the client any real, perceived or hidden risks from using the algorithm. After full disclosure, the client is responsible for making the decision to use or not use the algorithm. If People Analyst reasonably believes an algorithm will cause harm, the People Analyst shall take reasonable remedial measures, including disclosure to the client, and including, if necessary, disclosure to the proper authorities. The data scientist shall take reasonable measures to persuade the client to use the algorithm appropriately.

(h) People Analyst shall use reasonable diligence when designing, creating and implementing machine learning systems to avoid harm. The People Analyst shall disclose to the client any real, perceived or hidden risks from using a machine learning system. After full disclosure, the client is responsible for making the decision to use or not use the machine learning system. If a data scientist reasonably believes the machine learning system will cause harm, the People Analyst shall take reasonable remedial measures, including disclosure to the client, and including, if necessary, disclosure to the proper authorities. The People Analyst shall take reasonable measures to persuade the client to use the machine learning system appropriately.

(i) People Analyst shall use reasonable diligence when assigning value and meaning to the following concepts when conducting People Analytics: (1) "Statistically Significant" (2 ) "Correlation"(3 ) "Spurious Correlation"(4) "Causation"

(j) People Analyst shall not engage in "Cherry picking" (pointing to individual cases or data that seem to confirm a particular position, while ignoring a significant portion of related cases or data that may contradict that position) when conducting People Analytics. The People Analyst understands that engaging in "Cherry picking" may constitute scientific fraud, suppressing evidence, or the fallacy of incomplete evidence.

(k) People Analyst shall not present incomplete evidence as real People Analytics evidence. A People Analyst may present a theory constituting incomplete evidence but shall label and clearly communicate the use of incomplete evidence.

(l) People Analyst shall use reasonable diligence to question assumptions and avoid engaging distorting assumptions “if’s” and calling it “science” and “evidence” (also known as the “Protagoras Problem”).

(m) People Analyst shall use reasonable diligence to recognize, disclose and factor “agency problems” when conducting People Analytics. The prudent People Analyst understands that agents may hide risks and structure relationships so when she/he is right, he collects large benefits, when she/he is wrong, others pay the price.

(n) People Analyst shall use reasonable diligence to detect, recognize, disclose and factor real, perceived and potentially hidden risks in using People Analytics. The prudent People Analyst understands that data creators and the designers and builders of data management systems have more knowledge than the People Analyst and can hide risks in the foundations and interpretations / bias of the raw, created and manipulated data. The People Analyst shall take reasonable remedial measures, including disclosure of risks to the client.

(o) People Analyst shall use the People Analytics method which consists of the following steps:
(1) Careful observations of data, data sets and relationships between data; 
(2) Deduction of meaning from the data and different data relationships;
(3) Formation of hypotheses;
(4) Experimental or observational testing of the validity of the hypotheses. To be termed scientific, a method of inquiry must be based on empirical and measurable evidence subject to specific principles of reasoning.

Misconduct

It is professional misconduct for People Analyst to knowingly:
(a) violate or attempt to violate the People Analytics Code of Professional Conduct, knowingly assist or induce another to do so, or do so through the acts of another;
(b) commit a criminal act related to the People Analyst's professional services;
(c) engage in People Analytics involving dishonesty, fraud, deceit or misrepresentation;
(d) engage in conduct that is prejudicial to methods of science;
(e) misuse People Analytics results to communicate a false reality or promote an illusion of understanding.

Terminology

(a) "Data" means a tangible or electronic record of raw (factual or non factual) information (as measurements, statistics or information in numerical form that can be digitally transmitted or processed) used as a basis for reasoning, discussion, or calculation and must be processed or analyzed to be meaningful.
(b) "People Analytics" means the scientific study of the creation, manipulation and transformation of HR data to create meaning.
(c) "People Analyst" means a professional who uses scientific methods to liberate and create meaning from raw HR data.
(d) "Data Quality" means rating the veracity of data.
(e) "Data Volume" means a measurement of the amount of data.
(f) "Data Variety" means the different types (written, numerical, sensor...etc) and structures (structured, unstructured, semi structured) of data.
(g) "Data Velocity" means the measurable rate that data is collected, stored, analyzed and consumed.
(h) "Big Data" means large data sets that have different properties from small data sets and requires special data science methods to differentiate signal from noise to extract meaning and requires special compute systems and power.
(i) "Signal" means a meaningful interpretation of data based on science that may be transformed into scientific evidence and knowledge.
(j) "Noise" means a competing interpretation of data not grounded in science that may not be considered scientific evidence. Yet noise may be manipulated into a form of knowledge (what does not work).
(k) "Knowledge" means information backed by scientific evidence that creates meaning.
(l) "Machine Learning" means the field of study that gives computers the ability to learn without being explicitly programmed.
(m) "Algorithm" means a process or set of rules to be followed in calculations or other problem solving operations to achieve a goal, especially a mathematical rule or procedure used to compute a desired result, produce the answer to a question or the solution to a problem in a finite number of steps.
(n) "Data Mining" means using sophisticated data search capabilities and statistical algorithms to discover patterns and correlations in data sets to discover new meaning in data.
(o) "Statistics" means the practice or science of collecting and analyzing numerical data in large quantities.
(p) "Statistically Significant" means a statistical assessment of whether observations reflect a pattern rather than just chance and may or may not be meaningful.
(q ) "Correlation" means any of a broad class of statistical relationships involving dependence.(r ) "Spurious Correlation" means a correlation between two variables that does not result from any direct relation between them but from their relation to other variables.
(s) "Causation" means the relationship between cause and effect backed by scientific evidence (e.g. relationship between an event (the cause) and a second event (the effect), where the second event is understood as a consequence of the first).
(t) "Heuristics" means simple rules of thumb to assist in decision making or problem solving by experimental and especially trial and error methods and the evaluation of feedback to improve performance. Simple and practical easy to apply rules of thumb that make life simple. These are necessary (we have no mental powers to absorb all information and tend to be confused by details) but they get us in trouble as we do not know we are using them when forming judgments.
(u) " Variable" means a value that may change within the scope of a given problem or set of operations and may be independent or dependent
(v) "Cherry picking" means pointing to individual cases or data that seem to confirm a particular position, while ignoring a significant portion of related cases or data that may contradict that position and may constitute scientific fraud, suppressing evidence, or the fallacy of incomplete evidence.
(w) "Correlation does not imply causation" is a phrase used in science and statistics to emphasize that a correlation between two variables does not necessarily imply that one causes the other.
(x) "Substantial" when used in reference to degree or extent means a material matter of clear and weighty importance.
(y) "Predictive Analytics" means using techniques from statistics, modeling, machine learning, and data mining that analyze current and historical facts to help simulate scenario based decision making and make speculative, rationalistic and probabilistic predictions about future events (e.g. used in actuarial science, marketing, financial services, credit scoring, insurance, telecommunications, retail, travel, healthcare, pharmaceuticals and other fields).
(z) "Non predictive approach" means designing and building stuff in a manner not based dependent on perturbations and thus durable and robust in changes in future outcomes.
(aa ) "Ludic Fallacy" means mistaking the ecological complex real world to the well posed problems of mathematics and laboratory experiments.
(bb) "Iatrogenics" means harm done by the healer, like the doctor doing more harm than good. Generalized Iatrogenics: By extension, applies to the side effects of People Analysts, policymakers, researchers and academics.
(cc) "Naive Interventionism" means intervention with disregard to iatrogenics. The preference, even obligation, to “do something” over doing nothing. While this instinct can be beneficial in emergency rooms or ancestral environments, it hurts in others in which there is an “expert problem".
(dd) "Naive Rationalism" means thinking that the reasons for things are, by default, accessible to you.
(ee) “Confidential Information” means information that you create, develop, receive, use or learning the course of employment as People Analyst for a client, either working directly in house as an employee of an organization or as an independent professional. It includes information that is not generally known by the public about the client, including client affiliates, employees, customers or other parties with whom the client has a relationship and who have an expectation of confidentiality.
(ff) “Agency Problem” means moral hazard and conflict of interest may arise in any relationship where one party is expected to act in another's best interests. The problem is that the agent whois supposed to make the decisions that would best serve the principal is naturally motivated by self-interest, and the agent's own best interests may differ from the principal's best interests. The two parties have different interests and asymmetric information (the agent having more information), such that the principal cannot directly ensure that the agent is always acting in its (the principal's) best interests, particularly when activities that are useful to the principal are costly to the agent, and where elements of what the agent does are costly for the principal to observe. Agents may hide risks and structure relationships so when he is right, he collects large benefits, when he is wrong, others pay the price. These also affect politicians and academics.
(gg) “Hammurabi Risk Management” means a builder has more knowledge than the inspector and can hide risks in the foundations.
(hh) “Ethical Inversion” means fitting one’s ethics to actions (or profession) rather than the reverse.
(ii) “Protagoras Problem” means engaging in consequently distorting assumptions “ifs” and calling it “science” and “evidence”. The key is sincerity in assumptions.
(jj) “Narrative fallacy” means our need to fit a story, or pattern to series of connected or disconnected facts. The statistical application is data mining.
(kk) “Narrative discipline” is a discipline that consists in fitting a convincing and well sounding story to the past. Opposed to experimental discipline. In medicine, epidemiological studies tend to be marred with the narrative fallacy, less so controlled experiments. Controlled experiments are more rigorous, free of cherry picking.
(ll) “Rational Optionality” means not being locked into a given program, so one can change his mind as he goes.
(mm) “Subtractive knowledge” means you know what is wrong with more certainty than anything else. An application of via negativa.
(nn) “Via negativa” is the focus on what something is not, an indirect definition. In action, it is a recipe of what to avoid, what not to do subtraction not addition, say, in medicine.
(oo) “Subtractive prophecy” means predicting the future by removing what is fragile from it,rather than naively adding to it. An application of via negativa.
(pp) “Thalesian thinking” focuses on exposure, payoff from decision.
(qq) “Aristotelian thinking” focuses on logic, the True False distinction.
(rr) “Neomania” is a love of change for its own sake and forecasts the future by adding, not subtracting.
(ss) “Opacity “ means the state or quality of being opaque (not transparent or hard to understand). Some things remain opaque to us, leading to illusions of understanding.
(tt ) “Mediocristan” is a process dominated by the mediocre, with few extreme successes or failures (say income for a dentist). No single observation can meaningfully affect the aggregate. Also called “thin tailed” or member of the Gaussian family of distributions.
(uu) “Extremistan” is a province where the total can be conceivably impacted by a single observation. Also called “fat tailed”. Includes the fractal, or power law family of distributions.
(vv) "Writing" or "written" denotes a tangible or electronic record of a communication or representation, including handwriting, typewriting, printing, photostating, photography, audio or video recording, and electronic communications. A "signed" writing includes an electronic sound, symbol or process attached to or logically associated with a writing and executed or adopted by a person with the intent to sign the writing.
(ww ) "Belief" or "believes" denotes that the person involved actually supposed the fact in question to be true. A person's belief may be inferred from circumstances.
(xx) "Fraud" or "fraudulent" denotes conduct that is fraudulent under the substantive or procedural law of the applicable jurisdiction and has a purpose to deceive.
(yy) "Informed consent" denotes the agreement by a person to a proposed course of conduct after the People Analyst has communicated adequate information and explanation about the material risks of and reasonably available alternatives to the proposed course of conduct.
(zz) “Scientific method” means a method of research in which a problem is identified, relevant data are gathered, a hypothesis is formulated from these data, and the hypothesis is empirically tested. The scientific method consists of the following steps: (1) Careful observations of data, data sets and relationships between data. (2) Deduction of meaning from the data and different data relationships. (3) Formation of hypotheses. (4) Experimental or observational testing of the validity of the hypotheses. To be termed scientific, a method of inquiry must be based on empirical and measurable evidence subject to specific principles of reasoning.
(aaa) "Knowingly," "known," or "knows" denotes actual knowledge of the fact in question. A person's knowledge may be inferred from circumstances.
(bbb) "Reasonable" or "reasonably" when used in relation to conduct by People Analyst denotes the conduct of a reasonably prudent and competent People Analyst.
(ccc) "Reasonable belief" or "reasonably believes" when used in reference to a People Analyst denotes that the People Analyst believes the matter in question and that the circumstances are such that the belief is reasonable.
(ddd) "Reasonably should know" when used in reference to People Analyst denotes that a People Analyst of reasonable prudence and competence would ascertain the matter in question.