The IT sector is full of a lot of fancy phrases, professional buzzwords, buzzwords in English that have leaked from jargon to professional public discourse. Some of these terms are a passing buzzword, and at most they are good for creating the appearance of insider with it. However, there are also those that indicate basic tendencies, development directions, or draw attention to real problems and important challenges, and for this reason they should not be missing from our leadership dictionary. At the same time, it is important to be aware of their meaning and apply them in place, without twisting them out of their real content – because the greatest danger to buzzwords is that they will be completely emptied by unscrupulous overuse.
we take turns. However, our compilation is not intended as a small lexicon, but as thought-provoking, and instead of word-of-mouth explanations, we draw attention to the most common mistakes in the use of terms.
Digital digital transformation is the concept that IT managers may have the most trouble with, because many people toss it around completely irresponsibly and see it as a solution to all the problems of modernizing legacy structures in one fell swoop.
Another major concern with the digital transformation is that in some it gives the appearance that it is working on its own. Yet the goal and meaning of all technological development is business transformation, but this can only be achieved if technological renewal is aided by process transformation and the development of the appropriate professional background. The digital transformation alone is not enough for salvation – or as a large enterprise IT leader puts it a little crudely but aptly: we can leave a fool in the hands of any tool, leaving only one fool.
It is often said in connection with the digital transformation that one of the biggest challenges is the transformation of management. At the same time, the approach that this can be done with a single large-scale transformation program is now considered very outdated. Adaptation must be continuous and uninterrupted, and the workforce must also adapt flexibly to ever-changing circumstances. Lasting success can only be hoped for if everyone at the organizational level, from managers to subordinates, is aware that what was enough yesterday is now lacking.
Agile development offers a software production model that greatly aids business agility. But experts estimate that true agility is specific to only one-third of the teams, with the remaining two-thirds working in a hybrid construct that can be described as neither agile nor efficient. In other words, in addition to repeating the magic word, it would be worth paying attention to whether the principle has been put into practice.
DevOps (Development, Operations) it links the links between software development and software operation, but there is also some ideological confusion about the use of the term. Organizations often flip through DevOps-related tasks into the cloud instead of implementing the procedures and changes that result from merging development and operation. And unfortunately, the developers are not helping to clear up this misunderstanding either, because they often see DevOps as a “boxed” solution.
Minimally functional product
Minimally functional product (Minimal Viable Product, MVP) has been brought into vogue by startups, but is now used by everyone who aims to enter the fast market. However, the MVP is also a source of many misunderstandings. In most cases, they mean some conceptual, basic solution, but it’s good to know that while it’s really important to produce something quickly and put it in the hands of the end user, MVP isn’t ready until the company, based on user feedback, made the necessary adjustments to it. Matt Seaman, Lockheed Martin’s director of data analysis, draws attention to another common problem with the concept: businesses focus on the cost of producing a “minimally functional product” instead of focusing on the value of the solution
Artificial Intelligence (AI / MI)
The term artificial intelligence is also a victim of unscrupulous overuse. : nowadays – out of fashion, marketing – they are pulled on almost any tool whose intellectual level exceeds that of a coffee grinder. In fact, the meaning of the term is so confusing, so understood by everyone that it might be more worthwhile to use machine learning with much more precisely defined content for solutions that are capable of self-improvement based on different types of data.
But unfortunately machine learning itself is a term that, also for the sake of marketability, is used unnecessarily for solutions that are simply cleverly programmed, automated, but not further developed at all. by processing incoming data. Yet real machine learning applications can give an incredibly useful view of business information: by analyzing different datasets, we can use them to filter out, for example, which of the competing providers work best.
If there is an industry buzzword that is amazingly overused and watered down, it is in Section 5G. According to an industry leader, everyone in the industry today explains 5G, but in their experience, 90 percent of them have no idea what they’re talking about. Undoubtedly, this is a technology that will transform our world in a dramatic way, but when and how, we still have very vague notions about it today.
Previously, virtual reality (VR) and augmented reality (AR) were the two cool terms, and now the successor to both, augmented reality (XR), has been born. This category includes solutions and offers experiences in which real elements are mixed with virtual ones. The term is very flexible and has an astonishing number of possibilities for which it can be legitimately used, but it is certain that a video stream, for example, is not XR – and sometimes someone will advertise their product specifically.
It is also a new buzzword with a very flexible meaning: according to its original meaning, it was used for solutions that destroyed but built new ones from the rubble, in which new business models and technologies dismantled and shattered old frameworks. affect the business value of the products. A classic example of disruptive technology is Amazon, which has revolutionized the book and media market – first cursed, then everyone tried to follow.
However, drones, self-driving cars, XRs or blockchains are not disruptive technologies. Their impact is not unpredictable, explosive, but incremental: for example, the blockchain does not transform the retail sector, as it is not a revolutionary but an evolutionary novelty, and its impact is slower than many would expect.
Less is more
We are by no means claiming that the ten buzzwords in our compilation have no raison d’être in professional public discourse, we have only tried to point out that it is very easy to toss them irresponsibly – even though they don’t deserve it. because their true meaning is also very important.
Experts advise to eliminate possible terminological problems by using these magic words when we want to describe something with them that we have already done. So, for example, we can safely talk about digital transformation if we want to show how successfully we have changed our business model by properly applying processes and technologies. But let’s leave that at the forefront of implementing the strategy, because with the digital transformation, we may also be sewing around our necks tasks that have nothing to do with it. In other words, this term can be life-threatening in a room full of decision-makers – it is better to refrain from stabbing ourselves with it.
Article in the February 24, 2021 issue of Computerworld magazine (Volume LII, Issue 4). )
Hardware, software, tests, curiosities and colorful news from the IT world by clicking here!