8 Data Mistakes No Business Should Make

Data is so very important to businesses. It enables us to work out who our customers are, what they want, and how to give them it, but when it comes to managing data, many of us are still getting to grips with the issues, and making many a mistake along the way.

With that in mind, let’s take a look at some of the most common business mistakes that many businesses make, in the hopes that by knowing about them, you will be able to avoid making them in your organisation, too.

1. Not protecting it

One of the biggest mistakes that any business can make is in not doing enough to protect the data they have stored. Data is very sensitive, and due to GDPR regulations, it is really important that you keep most kinds of data confidential in most cases. If you fail to do so, you should end up getting fined by the authorities or sued by the people whose data has been breached. 

If you don’t want to find yourself looking for a lawyer who can offer you the most effective commercial legal solutions when things have gone wrong, then you should be at least encrypting data, installing firewalls and anti-malware software, and ensuring that you have access to a good IT team who can deal with any breaches quickly and effectively.

2. Casting your net too widely

So many business owners do not have a good understanding of big data and how it should ideally be used to gain insights and bolster business. Often, this means that they end up signing off on projects that collect vast amounts of data from their customers and clients, as well as from their employees and on their processes too. 

This might sound like a good idea because, the more data you have, the more you will understand the inner workings of your business, right? Wrong. When you collect so much data so injudiciously, it just means that you have a huge volume of data to wade through, and in most cases, much of it will not actually be all that useful to you at all. 

What you should be doing is determining which areas of your business it would be useful to have more data in, whether it be customer actions on your website or how efficient your IT processes are, and focus on collecting only that data that will help you solve the problems. Otherwise, you will probably just end up overwhelmed and your data collection won’t do very much for you at all.

3. Not moving data to the cloud

When you are collecting huge amounts of data, then setting up cloud storage for your business is vital. Having a private cloud for your company is not all that expensive, but it will mean that you age a safe space to store your data without the need for lots of extra computers, hard drives and networks within your own offices. This will cut your IT costs significantly, while also enabling you to better control and share data in a way that is flexible and convenient for you and your employees, especially if they are working remotely for you.

4. Not embracing artificial intelligence

If you are a business that relies on data insights to bolster your business and make key decisions about your processes, then investing in artificial intelligence could be a very good move right now. 

Why? Because AI, machine learning, in particular, can vastly streamline your data processes so that you can collect and analyse data more effectively and efficiently. It can also help to ensure the integrity of your data by providing you with unique security solutions such as threat detection, and best of all, it can learn as it collects data, which means it is able to provide you with fsr more accurate insights on the whole. Artificial intelligence is the future of big data, and the sooner you embrace it, the sooner you will be able to get ahead of the curve and start making better decisions that will benefit your business in a big way.

5. Not hiring a data analyst

If you have not yet embraced artificial intelligence and machine learning, but you are collecting a lot of data in the hopes that it will help you to improve your business processes, then hiring a data analyst, even in a freelance position, is a must. Unless you are well versed in data and statistics, it can be difficult to get a handle on what all but the simplest datasets are saying, and if you interpret them incorrectly, you should end up wasting a lot of time and money implementing the wrong processes at the wrong time. A good data analyst will not make such mistakes – they will tell you exactly what the data shows and what it means for your company, so be sure to consult them whenever you need to do so.

6. Not using the data at all

This might sound insane, but a lot of businesses who do take the time to gather data on their customers or their staff productivity or whatever, end up completely ignoring what the data tells them and not making any changes to their business, even though the data shows that it would be prudent to do so.

If you have gone to the time and effort, not to mention the expense, of gathering data, then you really should act on what it is telling you whenever it is viable for you to do sp. You might think it can wait, but things move so quickly in modern business that insight you gathered even just 6 months ago could be out of date by now, so you will need to start all over again to ensure that the data decisions you are making are still viable for your current circumstances.

7. Underestimating the cost and scale

One thing that a lot of companies do when undertaking a new big data project, is underestimating just how much money it will cost to gain the insights they are looking for, and just how big a scale the data project will need to be on to meet their demands. 

It can be a real shock to the system when the data team tell you what you are going to have to spend to implement a data project if you are not au fait with the ins and outs. That’s why, as a business owner, you should be taking more of an interest in big data, what it can and can not do for you and what kind of capture you may require. That way, you can plan for the costs of data collection and analysis in your annual business plans, meaning that they will be less of a shock to the system in the future.

8. Investing too much in tech

Many companies think that the best way to improve their data analysis is to invest in lots of technology to help them do so. Yes, some tech is likely to be needed to ensure you can capture and analyse data, but it is far more important that you know what you are looking for which is why more money should be spent on IT and data experts, and less money on the tech overall.

As you can see, there are lots of things that can go wrong when it comes to your business data, but the more aware you are of any potential pitfalls, the less likely it is that they will cause you any major trouble at all.