Data Foundations for Wealth Management 101
As a wealth management firm, your data strategy is no longer an adjunct to your business strategy. Rather it is now core to it.
Your data strategy impacts how effectively you can pursue your business strategy. It enhances or impairs the speed with which your team can make decisions and take actions. It allows you to build scale. And perhaps most importantly, your data strategy has a direct relationship with customer engagement.
Firms with strong data strategies:
- Enjoy better business intelligence and better decision making across the Lines of Business
- Are empowered to constantly streamline processes
- Can identify trends and shifts in the business earlier – frequently resulting in a market advantage
- Innovate more easily and profoundly
- Reduce waste and redundancy
- Move with more confidence
It’s still early in the data journey
Manufacturing insights, and decisions that erupt from those insights, are the core work of wealth management firms. Regardless of whether that happens by technology alone, human alone or some combination, fuelling those insights with the right data and intelligence is critical to business success.
Our ability to amass and leverage data, while once impaired by cost and technical complexity is now cost-effective and relatively easy. Frequently the greatest barriers are old approaches and legacy technology. The ‘cloud’ has changed the game on both cost and aggregation strategies, and the WealthTech landscape has brought powerful decision engines to the edge of the service and operating environment – all of which are powered solely by data. If you do not have a thoughtful data strategy for your organization, you are certainly under-leveraging your most valuable asset.
As technologies continue to progress and innovators find ways to bring new data patterns to bear on real world problems, the criticality of a forward-looking data strategy will only increase.
At Xtiva we are, at our core, a data company. We help you put your data to use in optimizing your business performance. Data Foundations 101 is about your organization getting stronger through your data strategy.
The Garbage Problem
We’ve all heard it: “Garbage In, Garbage Out”. It was true 20 years ago. It’s still true today, except the stakes are higher. When your business increasingly runs on data, dirty data, missing data, wrong data and misunderstood data all add up and can compromise your business performance, because those systems that rely on data to enable your business decisions become less reliable. It’s “Data Debt” and it’s a hidden but massive cost in many financial service firms and it’s growing. Data Debt means slower, less efficient and less reliable decision-making and execution.
A forward-looking data strategy
Any aspiration for the business to maintain optimal regulatory compliance, operate efficiently, service well, scale through any means AND deliver the best quality advice MUST have a forward-looking strategy to manage the depth, breath and quality of enterprise data. The guiding principal of the data strategy must be the treatment of the data as one of the most valuable assets of the organization.
This data strategy must incorporate:
- A future state view of the enterprise, including the regulatory landscape and the jobs-to-be-done;
- Definitions for where all valuable data is known to be and suspected to be across and outside the organization. This should be as unfettered a view as possible and it must be ongoing versus static;
- The means by which that data can be successfully domesticated, including education of users about the data and its usability;
- A standard of data quality, both at data acquisition or creation and beyond, as well as the controls to ensure this occurs and that remedies can be applied where necessary;
- Protocols and incentives for the use of the data. It is among the most valuable of enterprise assets, therefore its use should be encouraged not stifled;
- Clear and transparent perspectives on the appropriate use of data owned by customers;
- Organizational governance and management of the data as a critical asset;
- Definition of the tools, technology and systems to accomplish the data strategy.
A Data Strategy Quick Start Checklist
It is critical that organizations develop a full data strategy. By embracing the steps below in our ‘Quick Start Checklist’, organizations can establish a good foundation, make material progress quickly with minimal downside risk.
1) Establish leadership for your Data Assets.
Assign someone to play point on this incredibly valuable asset. Your data strategy warrants as much focus and priority as Human Resources, Technology or other major organizational investments.
Hint: Don’t make this a token role, and don’t make it about policing data usage. Make it about building and finding value in the data assets across the organization or Line of Business. Creativity should be a favored skill.
2) Find all the data.
All data. Don’t limit this to internally generated data or custodial data. This is where many organizations fall down in maximizing their data assets. They think too small. Creativity and vision are really important. Think broadly – more than might seem reasonable at first.
Hint: Focus on answering two questions: 1) What are we really trying to do? and 2) What piece(s) of information would give us an advantage in accomplishing that? Challenging these questions repeatedly will help you get past the day-to-day thinking and to the core of the compelling problems that data can help you solve.
3) Collect and organize.
Associate as much metadata as possible to the data – any metadata is useful metadata. Remove any optionality on collection of data. Remove friction and barriers to collection.
Hint: Always err on the side of ‘making it easy’ for data to be collected. Don’t impair a more critical business (or customer) function with data collection process. Automate as much as possible. Never make a customer-focused job harder as a result of data collection demands. Where possible, carrots should favor sticks.
4) Prioritize data quality.
A fast path to poor execution and low user-engagement is the use of dirty data. Investment in tools and processes to establish and maintain data quality is important and should be embraced as soon as possible and certainly before accelerating the use of the data. Don’t worry about getting those tools perfect. Get them in place quickly and then optimize.
Hint: Often the key to efficiently managing data quality is ensuring a clear understanding of the parameters of the data as it is created at the original source.
5) Get momentum around value early.
Focus initially on small, meaningful wins from use of the data in the short term. The bigger wins can follow as the strategy gets built out.
Hint: Dirty or poorly understood data will derail the engagement of the end users – the very people who are needed to help leverage the value of the data. Prevent those risks from derailing the effort.
6) Know your data topography.
Establish and maintain a topographical map of all data flows in the business in high detail. This map should describe all data flows in to and out of each system. Identify and map every core process as well as all secondary and tertiary processes (we call these system ‘side hustles’).
Hint: Maintaining these details on an ongoing basis is much more efficient than decomposing and reverse-engineering later.
How can Xtiva help?
Our professionals know data. Better yet, they know where data hides and how to use it. We can help you gain control of and grow this critical asset to help you drive your organizational performance. Our team will partner with yours to help you develop your data strategy and concurrently accelerate your progress with the items in our Quick Start Checklist.