What is data?

In the 1970’s humankind entered what’s now become known as the information age, this era marked a worldwide shift towards an economy based on information technology. Fast forward to 2019 and life on planet earth looks pretty different. These days everything is online, we read our newspapers online, we work towards our qualifications online, we can make our doctor’s appointment online and we can purchase our weekly food shop without ever leaving the house.

Our personal lives have become so intrinsically linked to the online world, that we even socialise online. And as the world has rapidly become more digitalised, data has become a big deal and is a word that gets thrown about a lot. But what is it?

Data is defined by the Cambridge Dictionary as “information, especially facts or numbers, collected to be examined and considered and used to help decision-making, or information in an electronic form that can be stored and used by a computer”.

Digital data in its simplest form can be represented in binary; a collection of 1’s and 0’s, with 1 representing a switch being “on” and 0 representing a switch being “off”. The more 1’s and 0’s you have in a line, the greater the number of possible outcomes. Although generally speaking, we understand data after it has been converted into a form that we can better understand such as: text documents, spreadsheets, software programmes and even images, videos and audio.

As a modern world business, you’ll quickly realise we are surrounded by data and therein lies a messy nightmare or a fantastic opportunity.

Why is data important to your business?

Quality data helps to process, analyse and store large amounts of information in a way that is impossible for the human brain to compete with. Quality data can help you to see through the fog, allowing you to make educated and informed decisions.

It can reveal something about your current client base; which will inform your marketing strategies and generate new leads. This could be in the form of a social media system that uses algorithms to assemble and target audiences that are similar to your existing client base. Using data to understand your target audience is not something to be scoffed at; Business Insider has named bad advertising decisions as one of the most likely ways a small business will waste money. You probably wouldn’t want to schedule that swanky new mass email campaign to send at a time when your clients are least likely to engage with it, but with the right tools and quality data you can avoid leaving such things to chance.   

What is Quality Data?

Quality data can give you insights into the good, the bad and the ugly; the benefit of unbiased information is that it gives you the opportunity to play to your strengths and improve on your weaknesses. Data is integral to any performance management tool.

Quality data can also help you to make better use of your resources, better ensuring a ROI (Return on Investment). Imagine you learn that your team spends 20% of their time typing data into an Excel spreadsheet but it really shouldn’t take that long. Depending on the root cause of the issue you might consider using various methods of automation to speed up the process, such as macros, tools to extract text from scanned images or changing your processes entirely so that the data is digitised from the source. By eliminating the tedious task of transferring data from paper to spreadsheet, you will speed up your delivery and ROI.

Hard facts in a sea of opinions can be the confidence boost you need to take a proactive, rather than reactive approach to any issues your business might be experiencing. It also provides a strong evidence base which gives transparency and confidence to your stakeholders.

How to make your data useful

Like with any project you want to plan your approach. Throughout the planning process ask yourself these simple questions: what data are you going to collect? Why are you going to collect the data? How are you going to collect the data? Who is responsible for collecting the data? When are you going to collect it?

KPIs or Key Performance Indicators are critical for ensuring that the data you collect is useful. KPI’s are success criteria that support and influence business objectives; in order to successfully track a KPI, the data used needs to be relevant. For instance, you would like 70% of your clients to consider using your service again – this is your KPI. However, it would be difficult to extrapolate whether 70% of your clients would use your services again if you’ve only asked them if they were happy with your service.

While raw data (also known as unstructured data) does hold some value, simply looking at it won’t tell you anything. What you need is structured data, which is highly organised data usually in database form. Structured data is much more accessible and in a tight spot can help you to make snap decisions with accuracy. You might also want to consolidate your data into one place and ensure that the data is presented in a way that is easily digestible.

Data that is incomplete, corrupt, lost, compromised or out of date is useless. You need to implement a process by which efforts are made to consistently provide as complete a data set as possible. Where those efforts are futile and unable to be completed, incomplete data is deleted. You should also employ robust security measures to protect your data from criminal activity and solid back up plans should be put in place in case something happens to your critical data.

When is data not useful?

We don’t want to be negative but here is a quick check list of things you might want to avoid:

  • Data that is outdated
  • Data that is incomplete
  • Data that is not relevant to your business goals
  • Data that is biased
  • Data that is messy
  • Data that is unstructured
  • Data that is difficult to access
  • Data that is compromised

Any structured and complete data is good, but relevant and quality data is so much better for your business. 

Why is quality data important to your business? Share your story in the comments section below.

 

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