Much Business Intelligence software, such as Microsoft Power BI, Tableau and Qlik Sense, charges per user. That sounds simple and predictable, but it creates two problems. The first is the question of how AI agents will count, or continue to count, as users. The second is much more important to us: it punishes good behaviour.
Business Intelligence often starts with management, with overviews of finances and production by department, for example. Its value grows significantly, however, when data is used more widely across the organisation. Think of employees who can see where work is getting stuck, view their own time records, or nurses who can see which at-risk patients do not yet have a care plan in place.
With a rollout like this, per-user pricing suddenly becomes expensive. Especially when usage is lower than expected, while you still want every employee in a particular role to have access. I have seen technically inferior options chosen to keep costs down, or decisions to put the rollout on hold. Those alternatives might involve a cheaper but less powerful BI tool for that group, or working with static exports. That means more administration and fewer interactive features, or none at all. In every case, it is a missed opportunity: you are not getting the full value from your data, even though the work needed to make it available has essentially already been done.
Another common pricing model is to charge for the computing capacity used, as in Microsoft Fabric and as an alternative in Qlik Sense. On the one hand, this is fair; on the other, it makes it very difficult to predict what you will pay. Even with a design in place, you often still do not know what it will cost. Sometimes there are unexpected cost drivers, such as the startup costs of an operation to move data. Starting up can consume one minute of capacity per table, while moving the data itself takes just seven seconds.
At DataOwn, we want to reward good behaviour and keep costs predictable. That is why we offer fixed prices for our plans, subject to a fair use policy, of course. If you have a larger company or start using data more intensively, you move up to the next plan and pay more. You know this in advance, however, so you can account for it in your budget. That way, you decide whether the more intensive use of data is worth it!