Bad data: ever the invisible dilemma for many organisations. Why? It's something that is essentially intangible but, at the same time, something that can wreak havoc on a company's time, revenue, and reputation. It's one heck of a hidden cost - in every sense of the word.
For some organisations, the effects of bad data may lie in uncertainty about the accuracy of their customer database; time wasted in constantly checking and editing this database; revenue loss and unpaid bills due to incorrect records or addresses; or risk to reputation due to unprecedented customer churn. For other organisations, the cost of bad data may rear its ugly head in service delivery - incomplete or incorrect addresses mean deliveries don't get to where they should be; fleet performance is compromised when drivers who could be going simply from A to B are actually going from A to B via Z; or the cost of having so many staff members or vehicles out on the road is really starting to sting.
Regardless of the outcome, the risk of bad data to any business that relies heavily on it to steer their service, revenue, or reputation is a serious one.
What are the four major benefits of improving your organisation’s data quality?
Clean, consistent, and accurate data lends itself to a number of benefits for organisations who depend on it to run smoothly and successfully from day to day. Nearly ten years ago, the ACIL Tasman Report cited an additional $1.2billion worth of benefits to our economy due to trustworthy data - imagine the growth in dollar value and productivity since then for both New Zealand and organisations themselves.
Let's take a look at the four key advantages your organisation can expect to gain from good data quality...
ONE. Get rid of dirty data and significantly reduce cost to your company.
Many organisations collect data in semi-free format which leaves a whole lot of room for error. Typos, incorrect spelling of names, duplicates, or inconsistent use of abbreviations and punctuation (among others) make for data that’s dirty and, essentially, can’t be used properly.
Without the negative impacts of dirty data, there's no need to fix errors, fill gaps, or rely on guesswork. This means you gain back the cost, time, and manpower that was once wasted on manually checking, editing, and cleansing your data.
TWO. The ability to integrate, automate, and innovate with ease.
There's no need to expend people power when you have machines to do it for you.
Clean data can be integrated with other systems and software - the fact that it's readable, consistent, and accurate makes the whole integration process a whole lot easier and far more successful.
The ability to automate your company's "knowledge" infrastructure can be life changing. There's no double handling and no need for manual intervention, just the understanding and confidence that the information being pumped in (and out again) automatically is correct and relevant.
We live in a tech-saturated world, so why not make the most of it and go one step further? With clean data, organisations have the ability to leverage the customer information they have to both develop a system that is unique to the business’ initiatives and goals and, most importantly, understand their customers in order to offer them a service that is tailored specifically to their needs and expectations. Having a machine-led system that is automated and customised brings innovation to the forefront for organisations that rely heavily on data.
THREE. Reliable, accessible data that increases confidence and value add.
Knowing that the data currently in your systems plus any that's entered from hereon in is clean, complete, and consistent gives organisations the peace of mind they deserve. It allows you to geocode effectively, maintain accuracy whilst providing a single source of truth, and join data together easily and correctly.
And let’s not forget, good quality data is shareable data. Dirty data can't be shared - it can't be made readily available, understood, or used properly, which kind of defeats the purpose of collecting and utilising data in the first place, right?
FOUR. Understand the where, how, and why of all your assets.
Whether your organisation spans the whole of New Zealand (or even further) or just a small part, you can’t fully understand your customer base, target new areas, or route your fleet effectively with dodgy data and inadequate spatial coverage.
Clean data that's consistent and complete signifies correct addresses and customer information, which means location intelligence and coverage as a whole will be greatly improved.
Your organisation will benefit from a clearer view of where your assets are, be they customers, equipment, infrastructure, or service locations. You can better understand how you can improve on service as it stands now - can you reduce service delivery times and the number of staff and vehicles needed by optimising routes? And you can gain insight into why certain areas aren't performing as well as others or what's caused an influx or decrease in customer acquisition in particular suburbs, cities, or towns.
In this day and age, the impact bad data can have on an organisation’s time, cost, assets, and reputation is significant. Fortunately though, modern technology means that resolving the issues caused by dirty data is easy, user friendly, and has the ability to work exactly to a business’ specifications. And with those risks absolved and the promise of complete, consistent, and accurate data from hereon in, the benefits are absolutely massive.