Tag: Data Quality

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Customer Master Data debt

men tied with brown rope

Programmers and software developers understand the concept of “technical debt” – it is tied to the implied cost of future refactoring work to improve an existing piece of software. This technical debt could relate to the inherent design of the software, some aspects of its logic or methods, its integration and even the database that it relies upon.

Technical debt was originally coined by software developer, Ward Cunningham. Ward first used the metaphor to explain to non-technical stakeholders at WyCash (a portfolio management system), why developer resources are needed to be budgeted for refactoring work.

The exact reasons for why you may land with technical debt depends on many factors but it is often tied to simply the passage of time and expedient decisions that were taken, that on reflection now need to be undone.

Data, customer data, in particular, experiences the same challenges and changes with ‘technical debt’. Businesses that want to keep ahead of their competitors, need to continuously adapt and reevaluate the data that they hold, the way they hold it and the way they use and distribute it, sometimes the technical debt around their customer master data holds them back from being able to keep ahead of the pack.

Unfortunately, a great many systems that are already in use, constrain the flexibility that the business has around changing or adding the data on hand and as a result short-cuts and potentially bad decisions are taken about how to work around the deficiencies of the systems in use.

What constitutes customer master data debt exactly?

It is really only when you dive into the details of the data that you have, how you use I, where it is used and the effectiveness of it in getting certain jobs done, that you really draw some solid conclusions about whether or not you have a customer master data debt problem.

Customer data degrades over time, typically due to customers’ circumstances changing. they may change their name, they may move, they may get a new phone number, change their email address or start using new social media services. Unless you have a continuously managed relationship with that customer then the chances are that your systems are not current with the latest information that relates to your customers. Is this data debt? Probably….

If your systems are deficient in a particular set of customer attributes, like the ability to store their social media accounts, then what do you do? It has often been observed that with older types of systems that predate social media platforms, often the decision is taken to repurpose certain data fields to accommodate the storage of additional customer attributes that in all likelihood have no real relationship with the fields as defined in the system. When an upgrade comes along, those records risk being wiped out or ruined in some way. In some instances, a decision is taken to simply not store that data in a repository that is accessible to everyone. This type of decision becomes a data debt decision.

String data without a clear understanding of why you are storing it or without an understanding of the final purpose for that data is another example of a data debt decision. This is the kind of decision that ultimately also introduces compliance risk, and also unnecessarily clutters up your systems.

Then there are the critical bugaboos of data quality that seem to be pretty pervasive, namely the forced nullification or fake data posting for records that you have poor or missing data. Putting in Telephone Numbers like “(000) 000 0000” for example or capturing phrases like “UKNOWN” where data is missing but where the system requires some sort of entry.

Click on the image for a better view of the platform
Click on the image for a better view of the platform

You can probably think of a good many more. Pretectum’s approach to all of this is distinctive and flexible. When you define your customer master you decide which attributes you need to have and whether they are mandatory or optional. You also get to decide whether the data needs to be bound to certain kinds of data capture rules or data maintenance rigor. Data captured, is continuously assessed relative to the definitions that you have maintained.

Click on the image for a better view of the platform
Click on the image for a better view of the platform

Most decisions that you take today, can be ‘undone’ or modified and adapted as your business needs evolve thereby avoiding the situation where you make a decision and then struggle to recover from the negative consequences of that decision. All of this serves to reduce the risk of you introducing customer master data debt. In fact, if anything this enhances the likelihood of you being able to consider your customer master in the Pretectum platform as an asset.

Contact us today to learn more.

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Putting your customer data through its paces

Bearded Man Winning Marathon Race

When was the last time you did something really innovative with your customer data? In fact, does your customer data actually support you in cranking up your use of your data assets in response to the changing market?

In many businesses, sweating data assets like customer data happens all the time, but in some cases, it is really hard to do for a great many reasons.

Some of the reasons that impair your ability to leverage customer data assets include compliance and regulatory control. Others are siloed data, an inability to nail down a true customer data owner, the burden of reshaping the data in just the way you need it in order to follow through on an idea, or the most common one, plainly defective data or data with poor data quality.

There’s a lot at stake if you don’t exercise your customer data regularly. Data erodes over time, even if it doesn’t fundamentally change. People change their contact data, they pass away, relocate, marry or simply change their preferences and behaviour.

It doesn’t take much for all that great data that you possibly had at the time of capture, to become irrelevant. The fastest path to irrelevance is most definitely, your own business’ inability to deal with evolutionary change in the data and the underlying characteristics of the people and organizations that it represents.

Change has everything to do with speed and currency. When the speed of change around your organization is faster than the speed of change within, you see organizational obsolescence. That obsolescence begins with the data but can quickly permeate into the actual DNA of the business.

Voice over IP technologies, for example, revolutionized long-distance phone calls. New technology destroyed the idea that you needed to pay for the distance of the voice circuit and the time of day that you called. In fact, the idea today, that you should pay for minutes is an anathema for the next generation of workers.

What does this mean for your business?

This is just one example of how you need to rethink the status quo and reconsider what matters and what is relevant. For any business that stores customer data, it is essential to keep that data current and relevant to the evolving world in which we live. The only way to do this is to leverage technologies that are combined with business processes that support a new way of working.

To achieve this you need to warm up your customer data assets, just as you would stretch your muscles ahead of any strenuous exercise. You need to assess what you have, define the rules that relate to the purpose or intent you have in mind for the data, and then verify that what you have, will fit the purpose you have in mind. If you fail to do the warm-up, in the form of a data definition and assessment, then you risk diving headlong into an initiative that will suffer the friction typically associated with projects built on data with poor data quality.

The Pretectum approach to addressing these essential steps is to provide you with a way to define what you need as a minimum. Define what constitutes acceptable or gating criteria and then stage and assess the data assets that you have at hand to determine fit.

Data that doesn’t meet your expectations can be peeled off from the good data and dealt with separately. The best data that you have can be leveraged to finish the race and in fact, used multiple times for follow on activities.

Pretectum feeds into not only your operational needs on a day-to-day basis but also your long-term goals of getting as close and as intimate with your customers as they will allow.

In the end, the result is a win-win for you and the customer. The customer feels valued and can be rewarded and your business can grow and thrive confidently in the knowledge that the data that you have at hand is relevant, appropriate, and approved.

Find out more about how Pretectum’s Customer MDM can help your business can put its customer data through its paces so that you can run any race and be confident that you will finish it successfully.

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Does all your customer data belong to you?

black and white wooden sign behind white concrete

Customer data is broad-spectrum in nature, it covers a lot of information about the people that your company serves. At the most fundamental level, your customer data is a critical data asset that you need to understand your customers and guide how you can best serve them.

There are many kinds of data that you will have about the customer, from names to email addresses. phone numbers, job titles, date of birth and other personally identifiable information (PII) through to sales orders, quotations, service and support ticket records, policies, warranties, certificates etc. You may even know where they work, what kind of devices they use and more about their families!

The possibilities are almost seemingly limitless, depending on the purpose and intent you have for that data.

Just like their physiology, customer data comes in a variety of shapes and sizes. You may have their data stored in more than one system of record or repository and simply making sense of the customer data that you have, may seem daunting especially if you have doubts about the consistency, accuracy and general quality of your customer data.

This is why we talk at Pretectum, about focus, a focus on what matters and having the right customer data perspective. We have observed that many organizations fail to establish some fundamental building blocks for building and using customer data effectively.

We believe that you are likely to have four main missions around your customer data

  • Customer data definition
  • Preventing bad data creation
  • Assessing the quality of customer data
  • Reporting and distributing customer data

Customer data definition
Basic personal customer data frames aspects of your fundamental understanding of each relationship you have with every customer. Out of the box configuration, standard data fields in an ERP, CRM or CDP should be considered minimum basic data. Names, addresses, email addresses, phone numbers and relationships are all examples of basic customer data.

Demographic data, such as gender, family connections, income, social media data or firmographic data can also be basic customer data but not necessarily so.

Preventing bad data creation
We believe there is only one way to prevent the creation of bad customer data and that is through the introduction of rigour into the customer data creation process.

Whether your personnel are using batch loading methods, technology-based interfaces or manual entry methods, the best way to ensure that you are maintaining the best view of the customer is one where the journey to data creation is a curated one.

This means creating and maintaining controls and restrictions around the customer data that can be created and the ways in which that same data is edited and maintained.

Assessing the quality of your customer data
We believe there are an infinite number of ways to assess customer data quality but business process owners know what really matters and should have the tools and methods available to support their data quality assessment.

These data quality assessment methods should be rooted in the curation process, whereby the rules, measures and controls that you maintain for data creation should be the same rules, measures and controls that you use for data quality assessment

Not only does this maintain a unified view and understanding of the data that you have, and the maintenance thereof, but it also means that you can consider extensions to the portfolio of customer master data according to the evolving needs of your business with some degree of confidence that you are not creating a potential compounding problem of poor data quality in your customer master data.

Reporting and distributing customer data
Once you’ve created your customer data definition, defined all the rules around that data and determined who can and should have access to the data and the potential maintenance thereof; you need to consider how you will make it available for use by the wider community of business users in your business.

Everyone from product management through sales, marketing, service and support will have an interest in customer data because it tells a story about past success and prospective opportunities.

For best effect, when considering the syndication of customer data, you need to determine the purpose and intent that you have around the customer data that you have. In this light, you need to consider the customer data goal.

The customer data goal
In itself, customer data offers only the most minimal value to an organization. Harnessing customer data to improve the customer experience or develop new products or features is a very common first goal.

Accelerating revenue growth, profit maximization, and renewal maintenance can be additional motivators. These goals have nothing to do with the data itself but they have everything to do with what you need to have in place and the level of confidence that you need to have around the quality of the customer data that you have.

Competition landscape
It is not unusual to draw parallels between your business and your nearest competitors, to look to the customers that they have, the way that they interact with them and the level of commitment and recurrent business that they harvest from their existing customers and potentially how that influences prospects.

Many organizations leverage customer data in a secure and scalable way and have a disciplined approach to making customer data accessible to the wider organization. Thinking about your competitors, do you believe that they have better data and a better handle on the customer data curation process?

This may be difficult information to glean from your competitors, but the good news is that Pretectum’s C-MDM takes a lot of the guesswork out of the process for you, by suggesting the rules, controls and measures that you should have in place for your customer data.

Further, intelligence under the hood, helps you to curate perfect sets of customer data according to the needs, purposes and intentions that your business has for customer master data management.

Even more significantly, Pretectum Customer MDM looks to the characteristics of your business and compares that with similar entities in your industry segment to suggest, hone and refine the data governance process for your customer data according to the needs that your business has while taking advantage of the concept of crowdsourced insight and policy.

Data Essentials
The advantage of the Pretectum CMDM approach is that data that you have today, that you think is trivial and superfluous and perhaps not even that useful, may prove to be particularly valuable for some very specific use cases that you currently don’t use it for today.

This means, that although you may have some very specific needs that you want to address today, you can have a lens on your customer data that provides only the bare essentials or critically necessary data for that particular purpose but you continue to maintain and curate other data that you may wish to use at some point in the future, thereby leveraging a different lens on the customer master.

The era of privacy regulation
Data protection regulations like the US Privacy Act of 1974, COPPA, the Gramm-Leach-Bliley Act (GLBA), Californian Consumer Privacy Act (CCPA) and Europe’s GDPR along with industry-specific data security requirements like HIPAA and PCI are increasingly commonplace in our data-centric economy.

The Pretectum platform holds any data that you choose to store, in an encrypted and secure way according to the laws of your country and in a way that meets the intent and objectives of regulation.

Pretectum goes a step further though, in addition to ensuring that your customer data is secure, Pretectum also supports you in being able to inform your customers about the data that you have and allows you to afford them the opportunity to curate the data that you have. This consent-based approach means that your customers can tell you how they would like you to use their data and what you may do with their data. In addition, they can maintain their vital statistics in a way that supports your data being continuously up to date.

Update your vision for customer data today and consider a new perspective on the customer with Pretectum CMDM.