Nowadays all businesses have a huge amount of data to process every day. It’s pivotal for them to make sure that they rely on all that information so they can improve the decision-making system.

Is the data actually significant when it comes to the sample size?

Most of the time the business intelligence information feels accurate, but is it really like that? The thing to keep in mind is that you don’t always have enough information. You need to try and make sure that you get as many views as possible in order to get a proper sample size. Once you know that, the results will be a lot better and the experience will be incredible.

Sampling problems like having a lower than optimal sample size or selection bias are things that really end up being a problem in the business intelligence world. That’s especially true when you are a startup. You can end up misusing stuff if it’s way too appealing to use that information and it feels relevant.

If your business just started to get customers, then it might not always be a very good idea to already start questioning the few customers you have. Even if it feels like the right thing to do, this is not going to help you that much. It’s better to wait for a larger sample size. Rushing business intelligence just so you can have a decision might sound great, but it really isn’t like that, and you do want to make it right.

Relying on historical data

One business intelligence mistake that a lot of companies will do comes from the fact that companies will use historical data to create current goals. They also establish their business processes around that. Which may work at times, but not always. The most challenging thing when it comes to business intelligence is that relevant data might be hard to acquire at the right time. You do want to make it work and adjust it to your own requirements. Once you use that to your own advantage, you will find that nothing is impossible, and all you have to do is to make it work in a clever manner.

Using historical data certainly helps just because it’s simpler and more convenient, and it will always continue to push the boundaries while still adjusting and adapting stuff in a clever manner. The relevancy of your business intelligence data will always be a metric to consider. Even if that might not always feel like a crucial metric for you to take into account, it certainly is one, and you must consider everything.

At the end of the day, variables changed and what worked in the case of historical data from a year ago might not be suitable for business intelligence today. That’s one of the main issues that can arise here. As long as you are tackling it in a proper manner, you will still find it to work quite well every time. But at the same time, historical data is not bringing in the growth you want because it’s not fully adaptable to your own needs. So you do need to tweak the business intelligence you acquire here and there so you can obtain the best experience.

We at NextBee can help you avoid these mistakes and make the right moves in the Data Science world. Let’s connect to discuss more.