Data is central to every digital transformation, but many organizations fail to account for the maintenance it needs as part of their plans to update their enterprise.
Not all data is in a state that is fit to be used for productive purposes – in fact, only 3% of organizations have data that meets basic quality standards and can be used reliably by the new technologies they are implementing.
Managing your data properly as you continue to work with it is critical to ensuring that it stays useful and doesn’t topple your digital transformation before they can start to pay off.
Why You Need Data
Data is to a digital company as blood as to the human body: you might not think about it much, but it’s still there in the background, keeping everything going.
The most promising aspects of digitization require extensive amounts of good quality data in order to function at their best.
Machine learning, for instance, is a much-vaunted new technology that brings all sorts of new possibilities to the business world.
Systems and software that are equipped with machine learning capabilities can perform certain tasks (such as product development or customer service) without following a rigid set of programmed instructions. Instead, they learn how to accomplish the goals they’ve been given using a set of historical data to develop an understanding of how that process usually goes and which actions lead to which outcomes.
By absorbing these examples, they are able to learn from the past experiences of others and piece together an optimal solution to the problem in front of them.
Digital technologies like these depend on having access to data that can act as a kind of stored memory for them.
In short, data is knowledge, and knowledge is power; businesses that have undergone a digital transformation will never be able to flourish properly without it.
Why Having a Data Strategy Is Key
Understanding that you need data to run your digital operations properly is a good start, but not just any kind of data will do.
In order to get the best results, you’ll need complete and coherent data points that you can easily compare against each other.
To do this, you’ll have to think about both of the two main types of data: existing and new.
New data is the information that will be coming in after you’ve made your digital transition. In addition to adding to your records for future reference, it will provide feedback on how your company is doing in its newly digitized state. It will be the first place you will see any shifts resulting from changes you have made, allowing you to optimize your operations in a much smaller window of time than would otherwise be possible. By setting strict standards for what incoming data should look like before it actually enters your systems, you should be able to ensure that you start out with a good quality dataset.
Existing data, on the other hand, is a very different prospect. It is equally valuable as new data – if not more so – because it provides a frame of reference for what your company once was and how you were performing at that time. It also gives you the contact information of your existing client base, many of whom are likely to buy from you again at some point. However, this data also tends to be more difficult to deal with than new data because it was often collected before proper standards were put into place. For example, you might have some records with the customer’s last name listed first and others with it listed last, and even some with no customer name listed at all.
A computerized system would have trouble figuring out how to handle all of those instances and still deliver reliable, consistent analytics, which is why you can’t cross your fingers and hope that that happens.
You need to actively intervene and get your data in order before you can hope for good performance from those systems.
The five core components of a data strategy:
Having a data management strategy in place that determines what your data should look like and ensures that all data conforms to those specifications allows you to feel confident that you have set your digital transformation up for success.
Your Data Duties Are Never Done
Even if you get your data in order for the moment, though, you should never assume that your work with it is done.
Data isn’t something you can enter into a system once and then never touch again – it’s a representation of something, and in most instances in business, that something is a human being leading an ever-changing life of their own.
As their life goes on, the data that pertains to them will need to be updated too.
To look at a more specific example, people change jobs an average of 12 times in their lives, sometimes as often as every 2.8 years in the early parts of their career.
If you have records that have gone untouched for longer than that time, chances are good that at least some of them are out-of-date.
The contacts you were relying on for their purchasing power may no longer have that power anymore, or if you’re lucky, they might have even more than they used to.
Either way, your old obsolete data will not notify you of the change; it has decayed over time and is no longer relevant to your current needs.
Data decay is a problem that only gets worse over time.
The more corrupted, out-of-date or incomplete customer profiles you have, the more errors you can expect that to introduce into your algorithms and analytics. That’s why it’s crucial that you keep up with those changes.
Contact data quality management ensures that your data is being regularly reviewed so that it meets all of these standards and remains useful to you at all times.
Making sure this process gets done is just one more part of your data responsibilities as an organization.
Your Data Diligence Will Pay Off
So let’s say you get all of your data quality issues in order – what specific benefits can you expect to see as a result of having done this?
The four below are just the beginning. Good data can help you:
- Shape your digital strategy – There’s more than one way to go digital, and quality data can help you figure out what that journey looks like for you. Companies that use the information their data gives them to guide their way forward as an organization grow 8 times faster than global GDP, proving that evidence-based strategies are far more successful than your average digital growth plan.
- Maximize your revenue – Revenue from digital sources is projected to account for about half of all B2B revenue by 2020, and that’s not even counting the offline sales you might be able to capture by using technological tools like digital marketing. Getting good data on your side lets you access that market and find your place within it based on real-time feedback about your actions. Without it, you’ll have much more trouble finding your footing in this brave new world that runs at a much faster pace than the old one.
- Measure and improve your customer experience – One of the big improvements that most businesses want to see come out of a digital transformation is an enhanced customer experience – 86% of people are willing to pay more for a good one, so it’s worth your investment. If your data quality is high, you can reliably track what’s going on with your customers and offer them things like personalized marketing and AI chatbots that can help them sort out any problems they might have even when human staff members are not available to assist them.
- Improve your ability to acquire new customers – Good data not only helps you to understand what your prospective customers are looking for from your products, but because it gives you insight into customer behaviour, it can also help you to reach hesitant leads at key points in their decision-making process. Since 67% of marketing leaders feel that acquiring new customers largely comes down to your ability to lead prospective buyers through the customer journey across all possible touchpoints, you can expect to see an uptick in your market share.
Let Your Data Light Your Way to Successful Digital Operations
While no digital transformation ever goes perfectly smoothly, good data management could make yours much more likely to yield positive results.
Knowing that you can rely on the quality data you have to accurately represent your company's past and present for your new systems can give you some much-needed confidence in their eventual abilities.
With that key consideration handled, you can look forward to many promising changes in your organization as you adapt to the demands of this new paradigm.
There's no limit to the number of things your data can tell you under the right circumstances, and we'll have more to say about that in future posts.
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