No matter what kind of business you run, your employees are constantly working with data.
- Assuming you have clients and suppliers, you’ll be keeping information about other businesses and the people that run them.
- You’ll have an invoicing or accounting system.
- Sales staff may use a CMS to store leads or a CRM system.
- You’ll probably have a payroll system, a project management tracker and a record of your inventory or pricing.
All of this data becomes interwoven into your day-to-day activities. Over time, the quantity and complexity grows.
Failure to maintain data quality can be disastrous for staff, clients and your bottom line.
The Importance of High Quality Data
No matter what your industry, your employees have a responsibility to work with that data within ethical and legal boundaries. But the issue doesn’t end there. All of this data becomes critical to the health of your business: over time, your employees become more and more dependent on its accuracy. And despite your best intentions, data quality always decays over time, unless you proactively step in and maintain it.
So how do we avoid the impact of poor data? Let’s look at five DQ Global® ‘proverbs’ that will help us understand how to tackle the ongoing challenge of keeping all of our systems up to date.
1. A chain is only as strong as its weakest link.
In any organisation, data is continuously reused, recycled and changed. Maintaining data quality means ensuring data is managed consistently and correctly.
Investing in a data cleansing project is a great idea, assuming your overall processes and workflows support the maintenance of that data in the long term.
2. A good beginning makes a good ending
Cleansing data and improving its quality is far easier if that data has been collected in the right way.
Even if your data quality is poor, revising your collection methods after an audit should ensure that you maintain a reasonable standard, rather than letting quality slip again.
3. A miss is as good as a mile
When it comes to the quality of your business data, it’s no good to make do with what you have, or patch up a subset of data and hope for the best. Any break in quality affects the entire dataset.
When cleansing, your aim should be a complete overhaul and a total improvement; no half-measures.
4. A new broom sweeps clean
No company can claim to have been entirely squeaky clean when it comes to data quality. Whether it’s due to ignorance, poor collection methods or a simple lack of resources, businesses often let standards slip.
As long as you take steps to remedy the problem, there’s no need to dwell on the past.
5. A journey of a thousand miles begins with a single step.
Data quality projects are rarely straightforward, and it would be unrealistic to expect data cleansing to be straightforward. But it’s a challenge that you can overcome.
The sooner you deal with your data quality issues, the more time and money your business will save. It also becomes far easier to keep your house in order going forward. That’s where DQ Global® can help.