How do you feel when a recommendation you give winds up bad?
-
CloudatCost - There are dozens of posts in this community alone about their issues, yet in the early days they were recommended as amazing, great product, must buy.
As IT pros, we often give opinions on our experiences with products/services/solutions, in some cases with a "Buy this, it's amazing"
What do you do when that recommendation was a disaster? Do you reach out and say "Well, that was a bad call, sorry I recommended that to you"
-
Did anyone actually recommend them? I think it was just stated that it was available and cheap. And that you should make your own decision about it. Most went in pretty skeptical.
-
I've had recommendations for products go bad before. Comes with the trade. Often it's things that we just can't foretell. Or it's things that you can't learn about until you've actually owned the product awhile. In that case, you address it as an "oops, well, let's try again".
-
Just always add "this may work" so later if it fails just say "I said may dude, this isn't on me"... I'm half joking about this.
-
@thecreativeone91 said:
Did anyone actually recommend them? I think it was just stated that it was available and cheap. And that you should make your own decision about it. Most went in pretty skeptical.
This is an important point, I don't remember anyone recommending them. I know that I was very careful to state that we were testing them out as the price point was really interesting. Talking about a potentially interesting product between peers and recommending are very different things. At one point we were happy with CloudatCost for our lab boxes, but would never have considered them beyond that, but then they went downhill and now even for a lab I would not consider them.
But I think there is an issue around the perception of talking about something that we are testing or even using compared to making a recommendation. I had some people, more than a month ago, mention that they were surprised that several of us had recommended CloudatCost because even then it was so bad. I asked who these "several people" where and was told it was mainly me. I said that I had no memory of having done so and asked when I had said it. After searching, I never had. People had just taken conversations about using it as implicit recommendation for use (what kind of use I have no idea since they were trying to use it in production and I was talking about using it in a lab.)
I think that there is a natural tendency to see people talking about how they are using something as a recommendation for that product - mostly because most people recommend things that they have purchased. If you read the excellent book "Predictably Irrational", it talks about why this is. Most people have an irrational desire to support positively their decisions after the fact and will promote things that even they dislike because it is what they chose and they want their decision to look good. I do this too, it is an unavoidable aspect of human nature.
However, as an IT person running a lab where I choose things to test for the purpose of finding out if they are good or not, I am, more or less, immune to this in that setting, as are most IT people, and I have the additional advantage of understanding the irrational behaviour to watch out for and attempt to overcome. The nice thing about a formal lab is that products that we use don't imply that we decided on them - it means we are testing them and choosing to put them in our lab doesn't reflect on us thinking that they are good or even likely good, it may even mean that we thought that they couldn't be good but we needed to prove so!
We do lots of things in our lab that make sense in a lab but not in production too. We run an entry level SAN, single point of failure, in an inverted pyramid of doom on RAID 6, for example. We do it to lower cost at scale (we have ~20 physical lab servers beyond our cloud instances!!) and it makes total sense. But I hope that people don't look at that and think that I am recommending it for production usage. But likely, somebody somewhere looks at our lab planning and equates that to a production recommendation
No good answer, we need to talk about lab and testing usage. We need to test and evaluate products. We need to discuss that testing. And in this particular case, the promise of the platform and the early testing was going moderately well. The price was so low, and many people were getting heavy discounts and many got free instances which they were discussing, that it was a common lab exercise that lots of people were able to do together which made it very popular. Everyone wanted to support a vendor participating, so it seemed, in the community. It was a fun, shared experience. And it was cheap, a lot of people were only spending $15 and several had spent nothing having won their instances. So I think that this created a certain energy around a product that no one thought was great, but everyone thought was interesting and low risk to test. So it got a lot of attention that was easy to misread.
-
@thanksajdotcom said:
I've had recommendations for products go bad before. Comes with the trade. Often it's things that we just can't foretell. Or it's things that you can't learn about until you've actually owned the product awhile. In that case, you address it as an "oops, well, let's try again".
That's a tough one. Typically people want you to own a product or have serious use on it before recommending it. That's one of the reasons that I work with more than half a dozen cloud providers on a regular basis - so that I really know what the issues are like over time, not just what their marketing pages say. What's funny is that, in this case, a lot of people looked at me testing one product and deciding not to use it in production myself as a recommendation for that product but did not determine the same thing from my production usage of competing products. An odd interpretation, IMHO.
-
@Breffni-Potter said:
What do you do when that recommendation was a disaster? Do you reach out and say "Well, that was a bad call, sorry I recommended that to you"
That one is very tough. But, I think, one of the most important jobs of IT professionals is to have used and evaluated a wide array of products (not for helpdesk people, but at a certain level and job type) and understand much of their technical strengths, quality differences, support value and the integrity of the companies that stand behind them (or the communities that do, as the case may be.) Our job is to determine what is the best chance of success for someone, what is cost effective, what is likely to work out the best. Companies change, products change, some things cannot be foreseen.
Sometimes it is on us for actually making bad recommendations. That's a given. I see completely insane and reckless recommendations given regularly. Recommendations that I think should fall into a "fire them and consider pressing charges" category - like overspending by six figures without any technical or business reason for the spend, just because the recommender thinks that a product sounds cool, they like the brand or, often, they are getting some cool toy in exchange for selling the company down the river. This really happens, and industry wide it happens very often, this is true in any industry: the average person giving recommendations is not well prepared or capable to be doing so.
But assuming we are competent and honestly attempting to give good recommendations, hopefully good customers or businesses understand that we are not just being asked for a very complex recommendation in the moment (knowing all relevant products or approaches on the market) but also gauging both those products' futures as well as the business' future. Being asked to predict the future comes with risk, always. Even the best possible recommender, with the best possible intentions, with the most unlimited research budget and time can't get things right every time because that's not how predictions work.
When we make an honest mistake and recommend something completely wrong, yes, I think it is good if we own up to that and/or somehow fix the situation. But should we apologize for the times when we did the research, tried hard, used the available information and simply could not predict the future? Probably not, it sets an expectation that we are responsible for things we cannot be responsible for.
In many cases, one of the worst things about being in IT is that other people push impossible demands upon us as if it is acceptable. In what other job is nearly every single person in the field expected to be a fortuneteller, even without them claiming to be, and often held accountable for having failed to predict the future accurately?
