Because we live in a time where every company should be a data company, there’s one major thing we’ll need to cover on this little series of ours – purchasing software. More specifically, we’ll go over all the hidden costs that come with selecting the platform you’ll be analyzing your data on, a.k.a. the total cost of ownership (TCO). No matter if you’re just starting up a new company or if you’re a market giant deciding to invest a bit more into your company’s data analytics, this article will help inform you about all the things you’ll need to keep an eye out for. So, let’s get this train rolling because there are a lot of stops to go over.
Purchasing Software – A Hidden Iceberg
If you ask the owners of recent company startups how they decided on a platform, they’d likely reply that they choose one based on their current project. This is quite common, and usually, companies like these move between different software in-between projects, so they can experiment with a few. This is a great approach, and it’s likely the one to be used by most small startups.
However, from what we’ve observed, bigger companies often go with a different approach. It usually involves a choice based on questionnaires or scorings formed with their previous experience at heart. This all sounds fine until you realize that big companies most often make changes like these once in a blue moon, so usually, this previous experience is filled with gaps or lacks a certain modern understanding. Jumping on a new software based on what you want from it and not on experience would result in quite the error in judgment, do you think?
Well, we believe so. And this brings us to our main point – it’s not so much about the tool than it is about your combination of internal and external skills. In other words, as long as you got the competence, you can make any tool work in your favor. But does that mean you should just buy the first one that pops up? Well, no! Because, as we’ll now show you, determining the total cost of ownership is trickier than it may at first seem.
The price on the package is usually the most decisive factor when browsing, but just looking at the numbers won’t be enough in the world of analytics software. Just because one product is cheaper on the surface doesn’t mean that its TCO is as well. Additionally, when you throw in the good ol’ marketing tricks, it’s going to be quite the challenge to discern the best deal for your company. So, it’s advisable to break down every little expense for a clear picture.
Cost of License – This is the first hurdle you’ll need to go over, and even though the marketing and sales teams try to make it sound like it’s as simple as picking what book to read, it’s far from it. Different companies setup their licenses in different ways; some charge per user, others per usability, and others combine the two. Additionally, you often have tiers to choose from, which in some cases may even lock functionalities between the various levels. So, this first hurdle will require a lot of detailed inspection of multiple price plans and will most likely involve you digging deep to be sure that you know what you’ll be paying for initially. Research carefully, since some companies like to hide some hidden costs in the fine print.
Cost of Setup – It’s always something to keep in mind because it will be paid for one way or another. If you decide that you want the vendor to set up its platform, they’ll charge you for it. On the other hand, you could choose a third-party company to come and set it up since it’ll likely be a bit cheaper. And finally, if you decide that you can read up and set up the platform on your own, it’ll still cost you a lot of time and effort, which you won’t be able to use for any projects. In this phase, you’ll need to carefully weigh your options and determine what’s a bigger priority for you – saving money, saving time, or a happy middle ground. The cost here isn’t as high if you choose to go with a cloud version but will mount up if you decide you need an on-premise solution. Don’t stress too much over this, though, since this is a one-and-done sort of deal that won’t make or break you.
Cost of Computing Power and Storage – Here, the cost calculation mainly revolves around whether your company will utilize the cloud or will acquire and maintain some servers. Obviously, the cloud would be the cheaper option, and it’s seen as ideal by most startups. However, the choice may not be so simple for other companies due to their organization, culture, legacy systems, or other factors. In any case, you’ll be facing more price plans combined into different tiers and lists. The upside is that companies sometimes bundle the storage together with the software license, so that might be one cost you won’t have to worry about. Again, as before, do your best to research any hidden fees that may come up while you’re working with the platform. There’s nothing worse than being gated in the middle of a project and being forced to cough up more money, to be able to continue.
Cost of DataOps – A big focus needs to be put on data availability and data quality since that will affect the nature of your insights. Choosing which tools and features to go with will dictate the costs at this stage. You may want to go with a traditional data warehouse, an ETL, or an ELT approach. Let’s be fair – setting up, operating, improving, and managing all the data extraction, ingestion, movement, transformation, and so on can cost you quite a bit. However, it is a necessary cost to ensure that you have clean and reliable data to work with. In the long run, you could mitigate some of the costs if you choose a platform that can solve as many of the DataOps challenges as possible. It should be capable of working with many different data sources, should not require a specific kind of DBMS or architecture, and should be, well … as versatile as possible. In general, you’d need to consider how you’d approach maintaining quality data to work with and how you’d manage and differentiate it, for example, through the help of data dictionaries or data catalogs.
Cost of Development – So, we’ve come to the end of the rainbow, but is a pot of gold awaiting you here or something else? Well, it all depends on the speed of development. From our experience, businesses usually hire outside development companies to help with new implementations, updates, automation, etc. Careful, though. You’ll need developers that would best fit your company’s field of interest and specialize in your platform of choice. Without the necessary research, you might end up with a company that has a harder time grasping your internal processes. Generally, anything that slows down the speed of development will also postpone your return on investment.
Cost of Training – This cost is relative to your company’s size. However, it’ll be imperative for your success to integrate data literacy. We’ve been talking about the importance of this for quite a while now, so check out some of our previous articles to find out more. But just know that at this point, you’ll either have to hire some already data literate employees or integrate data literacy education within your company as a long-term strategy.
But don’t be discouraged from all this. As we mentioned at the start – it’s not so much about the tool as it is about combining internal and external skills. Yes, your projects might take a bit more time initially to get going, but once everything clicks and the experience and skills start piling up, you’ll start seeing more opportunities for your company’s future. And even if the first software you’ve chosen doesn’t work out so well, at least your employees will have the skills to deal with similar problems in the future.
Still, we’re here to offer solutions and not sympathy. Most companies don’t want to buy software for visualizations, after all. They want a product that gets them from raw data to insights. Well, Qlik recently produced a great comparison toolkit that you can use to determine what software will best fit your company. It contains checklists, comparison tables, and success stories. If you’re feeling intimidated and don’t know where to begin, this might be a good starting point.
Determining the total cost of ownership might be a tough thing to nail down, but with the right amount of research, you’ll be able to make the best choice for your company. Remember the five points we covered, and always keep scalability in mind. Because when you’ve decided on a platform that’s a good fit for you, you’re going to want to start automating certain processes so you can focus on the generated insights. At that point, integrating machine learning will be your best bet, but more on that another time. Happy hunting, everyone!