Data modelling. It’s not a foreground topic for many business owners, but with a little diligence it’s one that can lead to tangible (and profitable) growth. Not convinced?
If you believe your business is perfectly profitable without a data model or a data management plan, let me ask you another question.
Do you ever:
Get tired of flicking between multiple systems
Have mismatched data in different systems/applications
Spend time copying handwritten details into the system
Forget to send follow-up emails
Deal with clients who are frustrated by excessive paperwork
Receive fines for accidental non-compliance
If you answered yes to any of these, then it’s time to rethink your data structure. Each of these annoyances, no matter how minor in the short term, is costing your business in the long run.
A smart data model saves you money, time and stress. It keeps your clients happy, keeps compliance issues at bay, and allows you to engage in more meaningful work (rather than addressing menial problems).
What is a smart data model?
Data models define how the information within your business is structured. They come in many forms. There’s certainly not a one-size-fits-all solution to getting your data into shape. For many firms, there may not even be one solution. Multiple models may be used simultaneously to serve a particular purpose (to manage client data for example). Likewise, one model may be used to serve many purposes (document management, database management, system integration, to name a few).
As any data modeller will tell you, it’s likely that your business is using several different types of models, even without being aware of it. They might be built in to your software, or be present in the way you organise a simple spreadsheet. When you look over the (not even close to exhaustive) list of types of data models below, think about whether any of these models are currently at work in your business, either because they’ve formed organically or because they’re built in to your software or business processes.
Types of data models
These are primarily database formats, but the models can be extrapolated to apply to broader data sets, such as a firm’s entire client data.
Some of these data model types overlap. For example, a relational data model is a type of record-based logical data model.
Things to consider when designing a data model
Data models can range from simple database frameworks to complex, business-wide megastructures. For the purposes of this article, we won’t go into detail about the intricacies of logical, physical, and database data models. Instead, we’ll consider a data model as the combination of a model type (e.g. relational) and the software/systems you use to capture and store data (e.g. XPLAN), because a smart data model is one in which data, systems and processes work in harmony. Whether or not you choose to do further research, it pays (somewhat literally) to hark back to a few core considerations:
What are your needs/priorities?
What are the advantages of the model?
Does it mesh with your current systems and software?
1) What are your needs/priorities?
What can the model do for you? Are you looking to organise data into a logical format? Do you want to conceptualise data to better visualise complicated data sets? Do you want to map relationships to gain new insights?
Write a list of your needs, prioritised from most to least important, before looking into compatible data models and software systems.
2) What are the advantages of the model?
What are the advantages of this model compared to other models? What makes it different to other solutions?
Agility/Responsiveness to change
3) Does it mesh with your current systems and software?
The ability to connect your systems gives you greater breadth when mapping, sharing, syncing and analysing data. The more of your business’ data you can consolidate, the more you can learn from and leverage.
Does your existing software support your preferred model?
Can you sync data across complementary software systems?
Using your data model to drive growth
If you’re designing a data model, you’ve already got an edge on your competitors: you’ve got the opportunity to build in practical functions that save you time and money in a very tangible way. By addressing the key priorities and challenges specific to your business, your design can save you time, improve your risk profile, ensure data integrity and identify new opportunities for growth. It can help you and your team better understand and visualise core concepts. It can help you discover and act on opportunities for growth (for example, by creating intelligent marketing lists).
A smart data model can:
Set up task automation to save time
Automate workflow and processes
Capture and store data digitally (no scanning or printing)
Integrate systems (to avoid errors, improve data integrity and avoid flicking between drives)
Secure data to prevent time-consuming and costly compliance issues
Getting expert advice
There are no out-of-the-box solutions when it comes to modelling your organisation’s data. The complexities of integrating a data model (or two), your existing systems and desired software can be overwhelming. To get started, a bit of research into data models, systems and software goes a long way. But if your data model isn’t producing the results you need, or you’re having trouble designing a management plan that works for your business’s circumstances, it’s worth seeking expert advice.
Where to from here?
Umlaut’s data experts help financial services firms produce growth-driven data management plans. Begin your data journey with our Discovery Program, where we pinpoint areas for improvement and set out goals that will add real value to your business. Call Umlaut on 1300 80 95 80 to book a free consultation or learn more about data modelling.