In reinterpreting Bernays, and as a result of his own interview with him in 1984, Olasky discovered a philosophy of public relations that holds that, (a) because among the masses emotion is more powerful than reason, and (b) because there is no God watching over the world, (c) therefore, manipulation of these masses through public relations techniques is essential to prevent chaos and ensure public order. Olasky argued that this “rationale for public relations manipulation based on his lack of confidence in either God or man . . . was his [Bernays’] most significant contribution to 20th century public relations” (p. 83).

Source: Pearson, 2009, p. 104 (in book: Rhetorical and Critical Approaches to Public Relations II)

Thank you SAGE (and authors Shoemaker, Tankard, Lasorsa, 2012):

Noting that model is sometimes used as a synonym for theory, Kaplan (1964b) rightly asked, “If ‘model’ is coextensive with ‘theory,’ why not just say ‘theory’?” (p. 264). The answer is that although they are sometimes confused, there is a good reason to keep the two terms conceptually distinct. A theory is a set of systematically related generalizations suggesting new observations for empirical testing. As such, the purpose of a theory is to explain or predict. A model does not explain or predict anything. We might say that the purpose of a model is to describe and imagine.

Though a model is not a theory, a model can be used to represent a theory. As Neuliep (1996) noted, “Theorists use models because they can describe and simulate physical, logical, or conceptual processes that may not otherwise be observable or presentable” (p. 30). He gave the example of theories of listening. Because listening is a psychological phenomenon impossible to touch, a model can provide a valuable method of indirect observation. Neuliep stated that models enable theorists to illustrate, delineate, and depict the structural features (i.e., what the object or process looks like—its form) and functional features (i.e., what the object or process actually does—its purpose) of their theories in varying degrees of abstractness and detail. Some models may be very detailed and literal and others rather general and abstract. No matter how detailed or literal a model is, however, it is nothing more than a description of an object or process. If we want to understand how the object or process works, we need something more—a theory.

Full text can be found here:

http://sk.sagepub.com/books/how-to-build-social-science-theories/n7.xml?term=lasswell

Interesting line in the work of Tkalac Verčič et al. (2012, p. 224):

"We disagree with the assertion of Cheney and Christensen (2001) that the fluidity of organizational environments demands internal and external communication to be integrated and that the difference between the two is becoming meaningless or even misleading."

Full reference: Tkalac Verčič (Ana), Verčič (Dejan) & Sriramesh (Krishnamurthy). Internal Communication: Definition, Parameters, and the Future. In: Public Relations Review, 2012, Vol. 38, 2, pp. 223-230. 

Op artikel gevallen van Bloovi.be:

"Volgens Hinssen zal Europa, en België al zeker, altijd achterop hinken op The Valley. "In San Francisco wordt er bijvoorbeeld aan een sneltempo business gedaan, mensen in huis genomen en gegroeid. Hier is ook een ongelooflijke concentratie aan geld, talent en ervaring. San Francisco is een magneet voor iedereen ter wereld die iets wil bereiken. Kijk naar Davy Kestens, die zegt zelf dat hij nooit zo snel had kunnen groeien als hij zijn start-up uit de Belgische grond zou hebben gestampt."

Fatalistisch? Misschien. Realistisch? Zeker wel.

Yes, the title sounds weird, I'm ok with that. What I am not "ok" with is the fact that a lot of HR business is actually not helping the "business" at all and - therefore - should be better referred to as "HR overhead" with *zero* added value. Sure, there is compensation and benefits, payroll and legal matters that are absolutely necessary. However, these items will increasingly be outsourced in the future. Actually, I personally know HR managers who effectively made a career out of decimating their own teams and showing the board how much they saved bottom-line. Are these people really concerned about the HR profession? Doubtful. Did they resonate with the board by proving their ability of cut costs? Absolutely.

Cutting costs is easy: let's move on to the hard parts now

I was still in college when I saw an entire crowd of (non-HR) executives go wild when a (famous - or should I use the word "notorious"?) "happiness manager" boasted how she saved the organization millions of Euros by turning individual offices into office landscapes, allowing people to work from home (using their own printers, extending the life of office furniture) and cutting a number of benefits. To my amazement I saw how several executives offered her a job before the presentation came to a close.

Giving this display of HR bravado a long and hard thought I came to the conclusion that one could make a career in the field by cutting costs even further. Why not turn off the heating and promote sweaters as a "green initiative"? Why keep people working on payroll and the like if they can be outsourced or replaced by a digital system? Why keep in-house recruiters if an agency or (a computer) can do it for us?

What I want to say is that clearly, organizations - even government agencies - are increasingly competing with each other in order to survive. The mechanisms are astonishingly simple really: increase revenue or cut costs. Only part of increasing revenue hits bottom-line results. A more direct way is to cut costs. Therefore, HR leaders - traditionally at the helm of a service considered overhead - make themselves popular by self-cannibalism. A proven short-term success strategy that does not "add" anything valuable in the long term.

Now that I cooled down I will gladly share my point

Currently I am working at a fast-growing tech company in the San Francisco bay area. No, not Silicon Valley, increasingly the action happens "in the city" instead of a boring overpriced plot of land where no man/woman roams the streets after you left the organizational campus. That said, today I was looking into a set of tools that people (at different levels including the organization, the team, the individual) can use to optimize and track their performance. While I was talking to someone from the sales team it struck me that HR has been understaffed. This has been apparent in their lack of time to actually speak to people. This resulted in ignorance about what different teams are doing and how they are tracking their productivity. For sales in particular increased productivity comes down to more and better deals, as such increasing revenue. But due to understaffing HR acts as a buyer, choosing between numerous OKR (Objectives & Key Results) platform providers as if it were a kid in the candy store. Months ago a (rather expensive) tool was launched. People did not use it. HR had spent money without any visual return. Why? Because the emphasis was on the tool and the number of features it had and how much more awesome in looked in comparison with other tools. Ok, so what was the problem? HR did not understand that sales was already using salesforce to set goals, making another tool completely redundant. It made me think: maybe we have to rethink HR, consider the people working there as "productivity engineers", who might want to learn skills by being humble and learning from others. Only by thinking how they can help others to increase their productivity, they can themselves add value instead of giving the head of HR a short moment of fame by decimating its own ranks. The magic word: productivity engineer, not "happiness manager" or "human resources professional".

"Although we concluded that it is difficult to place a monetary value on relationships with publics, in order to measure ROI exactly, our interviews with CEOs and senior public relations officers revealed numerous examples of how good relationships had reduced the costs of litigation, regulation, legislation, and negative publicity caused by poor relationships; reduced the risk of making decisions that affect different stakeholders; or increased revenue by providing products and services needed by stakeholders. Those examples provided powerful evidence of the value of good relationships with strategic publics" (Grunig, 2013, p. 9).

Full reference:

Grunig (J.E). Furnishing the Edifice. Ongoing Research on Public Relations as a Strategic Management Function. In: (Eds.) Sriramesh (K.), Zerfass (A.), Kim (J.-N.). Public Relations and Communication Management. Current Trends and Emerging Topics. New York, Routledge, 2013, pp. 1-26.

When you are planning to use survey research, keep in mind that internet-distributed surveys are the easiest way to complete the task. However, most of the available tools are not free. So, compare survey tools well before you start and make sure you reserve part of your budget to pay for a likely and most-needed upgrade. Also inquire the administration of your institution (university or otherwise) to make sure there is not yet a deal with one of the major providers of software on the market.

To cut a long story short: there are great tools on the market but be prepared that the ones that are user friendly can come at a steep price. Please keep also in mind that not every tool offers you carefree export of data to Excel or SPSS in their free version (or their cheapest price plan). Most offer you enough information, making comparing the different solutions a bit easier. What I found is that there are three major alternatives (and one niche player):

1. SurveyMonkey
2. Qualtrics
3. LimeSurvey (freeware, but very complex - not at all user friendly)
   
4. SoGoSurvey (niche)

What frustrated me is that Qualtrics does not offer a clear overview on their pricing plans. This is why I went at length to make a dummy account (because we have a subscription at our university) to find out what you can and can't do with a free account. My major conclusion: options are really limited and export to SPSS is not possible. However, you can look up the answers of each respondent and hand-code them in SPSS afterwards (which is very time consuming). They also have this price plan if you click "upgrade":

Today I stumbled upon a (relatively old) article that was published in Administrative Science Quarterly (Miles, 1979, vol. 24, no. 4, pp. 590-601) about the "problems" that scholars encounter when digging into qualitative data. A few of the pros and cons of working with qualitative data were listed. As you will notice, most of them feel really familiar:

Pros of qualitative data (p. 590):

1. Rich, full, earthy, holistic, "real"
   
2. Strong face validity
3. Preserve chronological flow
4. Suffer minimally from retrospective distortion
5. More precise way to assess causality in organizational affairs
6. Minimal front end instrumentation
   

Cons of qualitative data (p. 590):

1. Collecting and analyzing data is a highly labor-intensive operation
   
2. Difficulty to make data "comparable" when working with several people on the same dataset
   
3. Methods of analysis not well formulated
   

Of particular interest to me was a fragment found on pages 594-595:

"We also learned that much analysis was going on in the mind of the fieldworker. Each one developed a fairly rich set of working hypotheses about what was going on in his or her site, along with a fairly retrievable store of specific anecdotes and incidents supporting the hypotheses. But without interaction with colleagues, the hypotheses went unchallenged and usually untested, and the anecdotes remembered were only those in support of the hypotheses."

Notice the words "anecdotes", "hypotheses" and the claim that qualitative researchers have a tendency to remember those fragments of data that support the hypotheses. A proposed solution is member checking although we cannot establish how strongly this protects us against "self-delusion".

As you might know already I organized a series of interviews with internal communicators in 2014. The overall aim was to gather data from semi-structured interviews in order to gain a better understanding of how these professionals make sense of their work. I consider this research  to be valuable because at this point we know relatively little about how PR practitioners reflect on their own work (L'Etang, 2006, p. 27). My impression, that I still need to prove with empirical results, is that internal communicators have a strong feeling that practices in their field of expertise are changing.

Although most of my PhD work revolves around qualitative methods I have also included some quantitative data. This is because I am convinced that different techniques inherited from both methodological traditions can enrich the research by allowing the scholar to approach a problem from different perspectives. During my series of interviews I asked my respondents to answer a limited number of questions from a structured interview. Since it was my first survey and given my focus on the ensuing semi-open interview I was not able to get much useful data from the quantitative questions. I will briefly mention pitfalls that I stepped into and of which I hope that future research will take note.

1. Be careful when using the word "budget", not too many companies are keen on sharing financial data, even if it "only" concerns operational budget

1. The word "budget" is itself a difficult concept. For example, I asked respondents to estimate the internal communication budget as a percentage of the total organizational budget. I did not expect interviewees would question the concept of "organizational budget". However, even though some organizations (e.g.: practically all government agencies) operate with yearly "budgets", more profit-oriented enterprises do not always work with quickly identifiable and yearly fixed budgets. Instead, some respondents understood "organizational budget" as meaning financial turnover while others used it as a shorthand for profit.
   

1. Make sure to test, ideally before you start gathering data, your survey. This means making sure that all your concepts mean the same thing to different respondents. For example, I asked how many employees worked in the internal communication department. I did not factor in the possibility that some respondents would include only full-time employees while others even included people who devote a mere 10 % of their professional time to internal communication.
   

This being said, a question that did generate interesting answers was a question designed to measure the impression communication professionals have of the degree to which different hierarchical groups within the organization value internal communication. I asked my respondents to give a score ranging from 0 to 100 to higher management, line management and employees as an indication of how important these groups consider internal communication to be.

I analyzed the scores with the statistical software package SPSS. With the help of this program I compared the mean scores of the three groups using a repeated measures ANOVA. The descriptive statistics show that line management receives a decidedly lower score than higher management and shop-floor employees. This seems to resonate with my impression I got during the interviews, being that internal communicators are not over-enthusiastic about the (internal) communication skills of line managers.

In the next table I find that the multivariate tests all indicate a significant difference in the mean scores of the different groups. However, we must be careful with interpreting these results. I have found several statistics websites with warnings about the power of multivariate tests in case of a repeated measures ANOVA. On the website of Originlab for example the authors write: "In most cases, multivariate tests are not as powerful as repeated measures ANOVA, so we should use repeated measures ANOVA. However, under certain circumstances, for example large sample size and a serious violation of sphericity assumption, the multivariate tests would be a better choice. " Since I do not have a large sample size (we will get back to sphericity in a moment) it seems that I will need to look more closely at the Tests of Within-Subjects Effects.

It is important, when using a repeated measures ANOVA, to test the assumption of sphericity. To quote from Laerd Statistics: "Sphericity is the condition where the variances of differences between all combinations of related groups (levels) are equal. It therefore shows much resemblance to the homogeneity of variances assumption in a between-subjects ANOVA." To test the assumption of sphericity we used Mauchly's test of sphericity. The test, in our case, indicated that the assumption of sphericity has not been violated ( X^2 (2) = 4,172, p = .124). We can therefore assume sphericity. 

Based on the Tests of Within-Subjects Effects I was not able to confirm the multivariate tests. In this table can be seen that, when assuming sphericity, the scores are not statistically different (F (2, 106) = 2,394 , p = .096). However, given that the p-value is not all that far removed from the critical value of .05 I believe that I might have found something here. With a more homogeneous sample (in this sample were included people who do not identify with the communication profession since their company decided not to hire a dedicated PR professional) and more data points (i.e. more completed surveys) I am overtly convinced my results would turn out to be significant on all tests.

Because I don't want to keep you waiting for another blogpost I can already share that the qualitative interviews revealed an important reason why I formulated the hypothesis that internal communicators have the impression that line management cares less about internal communication than members of higher management or shop-floor employees. Line management is believed to be a group of which the members are very concerned about their (operational) targets, leaving less room for "corporate affairs". They additionally act as important information gatekeepers who, according to one respondent, "like to receive information but are hesitant in passing on information". However, many communicators added that there is considerable variation in the group of line managers as regards their communication skills.