If you are one of the many Irish businesses experiencing a COVID-19 related slowdown, and you find that you have some additional time for new projects, then you should consider adding some data cleaning to your ‘To Do’ list.
Not to be confused with ‘busy work’, the benefits of regular data cleaning are enormous, especially in a post GDPR environment.
So, what is clean data?
It’s actually not that complicated. Think relevance, accuracy and completeness. Do you need the data to conduct your business or to meet legal obligations? Is it up to date and accurate? When was the last time it was checked? How often is it looked at? Is there missing information? Would adding additional information help you conduct your business more efficiently or meet your obligations more easily?
Why should you clean your data?
Aside from the General Data Protection Regulations and other Data Protection legislation governing how personal data should be collected and held, data cleaning is just good practice. The more relevant, accurate and complete your data is, the more useful it will be to your business. For example, a company has, say, 1,000 active business accounts on its books. Addresses are included for all of them but because of a system change and subsequent bulk upload five years ago, the county and town fields are not filled in consistently for all of them.
Healthy data superpowers
Manually updating only these two fields, for all 1,000 accounts, means that you will be able to produce more accurate sales reports showing exactly which areas bring in the most cash for your business.
Adding in an additional field such as a sector or business type will allow you to see exactly what types of businesses are buying from you.
This information also enables you to identify your weak areas geographically and by sector so that your sales and marketing teams can come up with intelligent, targeted campaigns to drive sales and acquire new customers.
In a lot of cases, simply removing duplicated or legacy customers will result in a much clearer picture of the businesses current position.
Dirty data dangers
Using only the example above, it’s not hard to see the damage that dirty data can do to your business. If your data is not being examined and updated regularly, then more than likely you are making key business decisions on supply chain and communications based on inaccurate information. Decisions that are likely costing your business money. Poor data also affects your sales team’s ability to do their jobs effectively. Calling a business and asking for someone that no longer works there is a common frustration and doesn’t create a very positive impression. From a GDPR point of view dirty data and lack of processes for cleaning can make you vulnerable to hefty fines. From a marketing perspective, campaign personalisation is almost impossible with inaccurate data. For instance, if your customers are receiving emails with misspelled or incorrect names, their perception of your brand is immediately negatively affected. And if you are targeting areas that you are already performing strongly in, then your marketing spend is unlikely to deliver anything additional from a ROI perspective.
Information created globally 2010-2025
Release date December 2018 | Region Worldwide | Survey time period 2010 to 2018
Published by S. O’Dea, Feb 28, 2020
“The rapid development of digitalization contributes to the ever-growing global datasphere. The total amount of data created in the world is forecast to increase dramatically in the coming years, reaching 175 zettabytes in 2025.”
“Between 1986 and 2007, the world’s technological capacity to receive information through one-way broadcast networks was 0.432 zettabytes of optimally compressed information in 1986, 0.715 ZB in 1993, 1.2 ZB in 2000, and 1.9 (optimally compressed) ZB in 2007, this being the informational equivalent to every person on Earth receiving 174 newspapers per day.”
1ZB = 1 trillion GB
The Five Tips
Explain the why…
As an employer it’s all too easy to dish out what looks like ‘busy work’ without explaining the why. The truth is that employees need to be brought on a journey to understand exactly what they are doing and why – and how this feeds into the bigger picture for your business. Make sure your employees know the benefits of data cleaning and how this will help the company in the long run.
Give clear instructions…
Your data cleaning exercise might seem fairly straightforward but even so, document the steps and give this to your employees as a guide. It will reduce the likelihood of errors. Ask for regular feedback in case anyone comes across anomalies or errors elsewhere in the data. Find out how these are being dealt with and update your guidance document if necessary.
Spread the load…
Let’s be honest. Data cleaning is not the most exciting job, even when you know exactly why you’re doing it. Where possible, split the work among a few people so it’s a team effort and nobody feels like they’re carrying the entire load.
Calculate timings and set achievable targets…
Figure out how many lines of data can realistically be cleaned per hour. Set some targets for your employees based on this so that they have something to work towards.
Data cleaning is tough. It requires long hours and patience so it’s important to make sure your employees are as comfortable as possible and that they are not straining their eyes or body in any way by sitting in front of a screen for extended periods. Encourage them to take regular breaks and to stretch often.
Three essential items for your data cleaning projects;
1. Decent sized HD monitor – to reduce eye strain.
2. Monitor / screen riser – the top of your monitor should be at eye level to reduce neck and back strain.
3. Sit stand desk converter – standing while working for 15 minutes out of every hour can do absolute wonders for your physical (and mental) health – check out our other article for more on this;
‘Take a Stand for Office Wellbeing with Leap Desks’, … https://www.stacked.ie/leap-desks-stacked-office-wellbeing/
It’s also important to mention that having a robust process in place for collecting up to date and accurate data at the first point of contact is essential. This will help to reduce the amount of poor-quality data in your system, as time goes on.
Contact information will always need to be checked and updated as it will go out of date naturally but if you are collecting and properly recording key information on things like addresses and sectors, then the workload is being reduced and the process simplified.
It is also a good idea to do a bit of research to see if any of your data cleaning or checking processes can be automated. There are lots of tools and software on the market today that may be able to help you streamline and speed up these processes.