Research-based and evidence-based have become the new HR buzzwords. They are everywhere. Practitioners start their presentations with a bunch of academic references and the audience becomes quiet. Nobody will ever question the validity and applicability of a Schmidt & Hunter (1998) paper, right?
This has been my final assignment for the first course of my Master’s studies about digital literacy (Winter 2014). I was fascinated by the interconnection of (adult) education and getting a job, as well as the discussion about what it meant to be workplace literate. It was an ambitious assignment which I still find interesting to read, even though it is a bit too lengthy and not straight to the point. Enjoy!
The struggle for finding a superordinate definition of literacy can be retrieved regarding workplace literacy discussions (Mikulecky, 1988; Perin, 1997; Hull 2000; Belfiore, Defoe, Folinsbee, Hunter, and Jackson, 2004) and the influences of technology, being of interest for the workplace as a transforming key factor (Reinking, 1998). When literacy is seen as an age-independent continuum, distinguishing sharply between young and adult learners becomes hindering (UNESCO, 2009). In addition, the traditional dichotomy between literate-illiterate slows down the acknowledgement of lifelong learning (UNESCO, 2013). Rather, literacy is synonymous with “fundamental components of a complex set of foundational skills (or basic competencies), which require sustained learning and updating” (UNESCO, 2013, p. 17) to function as an empowering tool enriched by literate environments (UIL, 2010). The workplace connects various age groups with an enriched literate environment, where a social practice view of literacy is appropriate. When literacy is perceived as context-specific (UNESCO, 2005), a context definition backs the detection of skills and competencies for successful participation. Recruiting as a potential interface bridging literacy and context contributes by specifying required competencies to apply functional literacy in the work context. However, the expansion of literacy concepts complicates analysing it and distinguishing from “expressions such as knowledge, competence and learning” (Säljö, 2012, p. 6).
Den här texten var min sista inlämningsuppgift under kursen “Språk, rekrytering och mångfald” på Stockholms universitet (och jag är väldigt stolt över att den blev intygat med A). Den analyserar och definierar språkkrav för en tjänst i min organisation och ska ge dig en idé hur man skulle kunna gå till väg med en sådan analys. Längs ner har jag nämnt mycket läsvärda resurser som har betydligt förändrat hur jag tänker kring språk inom rekrytering och arbetsliv. Hör gärna av dig om du vill veta mer eller har frågor, antingen direkt här på bloggen eller via “About me” sidan.
Be it via Skype, Google Hangout or the like, video interviews are a great alternative for a first contact to interesting candidates. Compared to telephone interviews, video offers a more personal way to get to know each other. In addition, you don’t have to invite all candidates to personal interviews, which is more resources-efficient. But it’s important to keep in mind that a lot of applicants are still new to video interviews. Even though it’s a widely used tool for private conversations, job hunting via camera needs a different way of preparation.
Here are some ideas on how to support video interview preparation in the recruiting process.
Everybody talks knowledge sharing in corporations. I never really understood what knowledge management (KM) departments were up to. So I decided to take a course in knowledge management to learn more from both a theoretical and a practical perspective. One result was the below assignment which I modified for this blog post. It summarises my thoughts about the tacit/explicit knowledge debate and about how technology can foster knowledge and information exchange in the workplace.
The main points
- By arguing that tacit knowledge is hard to write down but most valuable, KM departments are keen to extract knowledge from individuals in an organization. To do this, a lot of tools, methods and standards force them to literally write down all they know. I argue, that this is not the best way to share knowledge. Technological support based on this tacit/explicit dichotomy does not make knowledge sharing more effective. It only reinforces the idea of writing down knowledge in a digital environment.
- From my perspective, knowledge is socially-constructed. Rather than beeing either tacit or explicit, knowledge becomes information as soon as it is seperated from the original knowledge-holder and the context. While this definition holds true for others in the field, I believe that the implications for KM technology support are often overlooked.
- IT support for knowledge exchange should focus on connecting knowledgable people, enrich information by context and offer various formats for sharing information. Concrete examples could be suggestions for colleagues who have worked on similar projects, case studies (instead of “lessons learned”) and a variety of formats such as video, blog posts or forums.
Tacit vs explicit knowledge?
The difficulty with the tacit vs explicit knowledge dichotomy is that it does not highlight the relevant aspects of knowledge which are crucial in an organizational context. According to this dichotomy, tacit knowledge is difficult to write down or extract. Yet, the crucial difference does not exist between tacit and explicit knowledge but rather between knowledge and information. Explicit knowledge becomes information, tacit knowledge becomes knowledge. Without comprehending the context in which knowledge has been generated in, a receiver of the information will not be able to enhance her knowledge. Instead of placing extensive efforts on how to extract every single bit and bite of knowledge, the tasks of technology in knowledge management (KM) should be to create social connections between people and build on existing sources of information in an organization to link knowledge supply and demand. This text outlines, how moving beyond tacit-explicit-knowledge can shape more precise requirements for IT tools in knowledge management.
How “Thinking, Fast and Slow” gives hands-on ideas for improving candidate selection
I cut myself through Kahneman’s bestseller, which is admittedly a bulky book. Whereas I admire Part I-III, it is Part IV (about the way we make choices) which was a tough chapter for me. However, I can highly recommend this book to those being interested in the way humans work and how this plays into principles of economics.
Chapter 21 “Intuition vs. formulas” covers comprehensive advise on how to improve interview procedures using concrete language beyond the human resources jargon. If you are about to have a training with line managers or a talk to management about why you need to build up structured interview competence, read this chapter first. Or send it out as a copy. It is a great way to describe the importance of structured decision-making without being at risk of throwing around HR buzzwords.
Kahneman describes that experts are always inferior to algorithms – a bold statement that most probably you are about to disagree on. He sees two reasons for his claim. First of all, experts try to be clever by making situations more complex, which reduces validity. Secondly, humans are inconsistent when summarising their judgement of complex information.
How does this apply to interview procedures?
If you are not amongst the lucky ones having well-established structured interview guidelines at hand, Kahneman compiles all you need to know in two paragraphs. The below main points are enriched by my own thoughts and experience.
- Decide on roughly six success criteria (traits) for the position you are about to fill. They should be as independent from one another as possible and assessable by asking questions during the interview.
- Decide on how you want to weight each trait in the overall final result of an interview. This is also one of my major learnings after I implemented my first structured interview together with a line manager. If you are unsure on how to weight, rate all traits as equally important.
- Decide on questions you want to ask to assess each trait, decide on a rating scale (maybe 1-5, make sure to leave room for comments) and discuss, what a good/bad answer would look like for you. The last point is especially crucial, if you have more than two assessors and if you want to brief other assessors later on.
- By leaving time for open questions at the end of each interview, you can give some power back to the line manager (especially interesting for sceptical line managers). Be careful that the answers to those questions do not interfere with the answers to the standardized questions before.
- During the interview, each trait should be evaluated one after the other, only rate the next one after you rated the preceding one. This means: continue to the next question only after everybody has evaluated the recent trait based on the current answer to the interview question.
- When you have several interviewers, mention, that it does not help to cheat. Rather than looking at the rating of others for help, assors should make comments about a candidate answer to justify their ratings afterwards.
- Plan some minutes after each interview to discuss the results with all interviewers. If the results differ, ask for concrete examples from the candidate’s answers. After the discussion, average all assessors ratings per question.
- Add up the scores based on the weighting you have agreed upon.
- Truly believe that you will make a better decision based on this procedure. Be bold and choose the candidate with the best average rating.
The most difficult part of structured interviews and candidate assessment is actually sticking to the procedure. It demands a lot of discipline. Keep this in mind. Sometimes it takes some iterations and trials until everybody can agree on the benefits of making sound decisions. From my experience it’s worth the effort.