5 Business Value Drivers to Optimize Your Data Warehouse Investment

Data warehouses can yield a tremendous ROI for organizations that leverage them properly. However, many financial institutions that invest in a data warehouse are not maximizing the potential business outcomes that will drive a positive return on investment.

The amount of stored data and exceeding interest in data analytics has resulted in the growing popularity of data warehousing solutions and analytics platforms. Over the years we have seen that as data management and analysis needs have skyrocketed, the market has introduced data warehouse solutions to address the evolving data centralization and storage dilemma. Well-built data warehouses offer the ability to store vast amounts of data and deliver fast results that a traditional database could not compete against.

As credit unions move away from the traditional database to a data warehouse, whether it is built, purchased, or in the cloud, it’s essential to use the data warehouse strategically to optimize all the potential value it promises.

If your credit union has invested in or is considering purchasing a data warehouse solution, are you leveraging its full value?

Here’s a quick Q&A on value drivers to get you started:

Value Driver #1: Are you gaining faster insights and better decision making?

The goal of a data warehouse is to help answer business questions faster.

In what once took days, can now take seconds. This provides management the ability to make clearer and more accurate decisions regarding the credit union’s members, products, services, branches and so much more. A data warehouse allows the credit union to analyze their data effectively as well as trust it! It creates accuracy, dependably and democratizing data so that more than just the purely technical employees can access it— your team can use and benefit from the insights gleaned from running data queries. This avoids bottlenecks and allows management to make decisions based on pure, clean, data—not on gut instincts.

The data warehouse provides a way to mine, refine, and harvest actionable insights faster – increasing the amount of time available to realize the benefits from those insights. The best data warehouses allow you to gather and analyze various types of data from diverse sources and not only collect and convert that data, but turn it into action plans that drive business decisions for the organization.

Value Driver #2: Are your business units/departments aligned and embracing the benefits of the data warehouse?

Each line of business in your organization (e.g. sales, marketing, lending, product management), and third-party tools should have a centralized data warehouse.  Your data warehouse should not limit data access or produce silos of data. Data remains centrally stored and can be accessed through any warehouse, as long as the user has the necessary permissions.

Most credit unions operate hundreds of disparate application systems.  Individual departments in an organization often focus on their own narrow system and information needs and don’t see the corporate value of integrating data.  A data warehouse helps breakdown those silos of disparate data so your data doesn’t get out of sync.  Best-in-class data warehousing technology will enable better department alignment, a single version of truth that ensures clean and accurate data management that everyone can rally around.  All this leads to more informed managers, making data driven, objective decisions – for which you’ll see the results to your credit union’s business outcomes.

Value Driver #3:  Is the data warehouse automating data collection and scaling with your credit union?

The best data warehouse solution should provide automated end-to-end data management—from initial data collection to analysis and reporting.

Your organization’s data assets will continue to increase, therefore, a data warehouse is one of the best available tools for managing data growth by enabling archival, aggregation and analysis of data from many different data sources. Whether an in-house or cloud-based solution, data warehouses can be highly scalable solutions. Having scalability to meet business needs is an important value driver to take advantage of as it will allow your organization to automatically scale to support any increase in data, workload, and concurrent users and applications without the need for data movement or expensive upgrades down the road.

Value Driver #4:  Are you utilizing powerful visualization tools?

A data warehouse makes it easier to work with popular visualizations tools like Power BI or Tableau. This enables non-technical users to quickly build insightful visualizations and dashboards to highlight critical information in an appealing fashion.  These tools can be used for advanced analytics output as well as traditional operational reports.

Value Driver #5:  Are you easily integrating key non-core data sources within your data warehouse?

With the increasing volume of information collected through a variety of channels, credit unions need a single interface where data is collected and stored – integrating data from common non-core applications such as loan origination systems, third-party servicers, credit and debit card processors, GL systems, and much more.

The right data warehousing solutions allow you to easily combine data from multiple sources to create a unified, single view of the data.  The ultimate goal is to provide users with consistent access and delivery of data across the entire credit union.  Data integration benefits everything from business intelligence and member segmentation to data governance and real time information delivery. Data warehouses can help bring disparate datasets together to further increase the value of your information.

Are you ready to drive greater business value? Getting the most out of your data warehouse means making smarter, quicker business decisions.

If your credit union is embarking on a business intelligence journey, or already down the path and looking to increase ROI of your data analytics investments with a powerful data warehouse, learn more about VeriCU data warehouse platform created by the Knowlton Group.  You could be up and running in 72 hours driving value data insights right away.

 

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To Build or Buy A Data Warehouse?

Chances are, you have heard conversations around the “build vs. buy” question in the context of data warehousing.

The answer to “build or buy” may seem a little hazy now. This free guidebook created by The Knowlton Group provides clarity so you can make an informed decision for your organization.

Transforming data into a strategic asset means empowering your teams to have fast access to accurate data that they can put to action.  Data and analytics are the key accelerant of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value. 1

Organizations who want to compete in the emerging digital economy need to be strategic on how they go about analyzing and managing data. Companies know their data is a strategic asset and they want to utilize it to make smarter decisions; but the problem is it takes dedication, a cultural shift, empowered people, tight processes, and robust technology.  Those who follow through however, will be the success stories of tomorrow.

Let us uncomplicate the process.  These 5 steps will get you on a well-chartered course to turn your data into a strategic asset.

 

Step 1: Build a Data Strategy & Roadmap

Strategy without execution will fail just as execution without strategy will also fail. Moving towards a more strategic approach to capitalize on data is certainly attainable, and it starts with a Data Strategy. A Data Strategy addresses more than the data; it is a roadmap that defines PeopleProcess, and Technology. Creating your strategy begins by addressing some critical questions and filling gaps quickly.

  • What are your objectives and use cases that can turn data into an asset? Knowing your strategic business goals now (i.e. deposit growth, opening new branches, new products, digital channel alignment, etc.) and in the coming years will help your organization devise a living, breathing roadmap that aligns analytics with key business objectives.
  • How can the credit union empower employees to use the data? If you empower employees through a high-performing culture, a vision of the future, open communication and access to data and analytics assets, you can accelerate delivery, improve quality, and drive user adoption and future success with data.
  • Do you have the right processes and tools that ensure data is accessible and of high quality? Having a robust process and high-quality control disciplines that governs the overall management, usage, storage, monitoring, and protection of the credit union’s data is a critical step in the data strategy.
  • Do you have the right technology that will enable the storage, sharing and analysis of data? As data becomes an even greater asset for the credit union, the ability to store large amounts of complex data in a unified, central database, known as a data warehouse


Step 2:  Create Reliable, High-Quality Data Sets for Rapid Analysis

A vital step when transforming data into an asset is having a proper data collection system. The credit union can amass enormous volumes of data from several sources in a short period of time, but not all of that data is relevant for analysis. Start by defining the types of data that are important and which use cases will drive the greatest return. Meticulous data organization is pertinent for analysis, and it will enable you to remain in control of data quality while improving the efficiency of analysis.  Data cleansing is imperative and will help to ensure data analysis is centered around the highest quality, most current, complete, and relevant data.

If your data is clean, well-organized, and free of silos, the next step is to segment your data for a more detailed and focused analysis. Going back to step number one, define your business objectives and use cases. Consider and plan for how the data will help you achieve this goal and segment the data accordingly. You can sort data into relevant groupings to analyze trends within the various data subsets.

Step 3: Use Information as a Competitive Edge to Drive Growth


In his book, Infonomics, Doug Laney explores countless examples of how organizations can assert economic significance from data. He dives into how organizations should measure, manage, and monetize information as a real asset.   These 3 steps include:

Monetizing information starts with generating economic benefits from available assets to drive measurable business value.

Managing information is to apply asset management principles and practices to information.

Measuring Information is to practice  gauging and improving information’s economic characteristics.

As Doug puts it, “most organizations have a better inventory of their office furniture than their information assets!”  Clearly, the future of data is all about moving from volume, velocity and variety to monetize, manage and measure.  2

 

Step 4: Hire The Right Talent

Data is your organization’s second most valuable asset. The first is your people. Ensuring you have hired data savvy talent that understands how to mobilize data across the entire business ecosystem to serve customers and create valuable data products is the cornerstone of transforming data. As many data analysts and CIO roles evolve to focus less on system uptime and more on using data to drive the credit union forward, having the right data-savvy talent is key.

Data expertise must remain at the heart of a data-centric approach. Investment in core data skills is required to get maximum value out of data and technology, and to ensure that the right processes are in place to translate insight into financial gains.

 

Step 5: Build A Data-Oriented Culture


If your company’s culture does not inspire excitement about leveraging data in new ways to propel the credit union forward, then you will have a hard time achieving your business goals. Building a team who is dedicated to the organization’s success and focusing on new and innovative ways to use the data strategically will make all the difference.  To build a data-centric organization, ensure you are cultivating an organizational culture around data. Treat data as an asset and give employees tools and empowerment to make the transformation.  A few other ways to inspire a data-driven culture include:

Ensure data analysis is a key part of the leadership decision-making. Your management and leadership team will set an example that will trickle down throughout each tier of management and among employees, leading to lasting transformation.

Remove silos and make the data readily available throughout the credit union. Provide every employee access to the data, so they can perform their duties more effectively. Also be sure to educate your teams on the importance of data security, privacy and governance with proper protocols that all must follow.

View data as a key focal point of every decision and strategy. Encourage employees to routinely analyze data and then develop questions and observations from it—making it a rewarding part of their role.

Promote data literacy across the organization.  When employees have the ability to read, understand, and communicate through the use of data they are more engaged in the process and vision.

Share data successes. Celebrating the individuals and teams behind successful outcomes is essential to promoting a healthy data culture.

If you can encourage and drive this cultural shift, invest in the right people, processes and technology, there is every chance that your data will be treated as the asset it truly is—and you and your organization will be well-positioned to reap the rewards that investing and nurturing your data can bring.

What about your organization? Do you have systems in place to effectively and consistently transform data into an asset that can dramatically benefit your organization and members? If not, The Knowlton Group would like to help. Learn More, www.theknowltongroup.com

Resources:
1. https://www.gartner.com/smarterwithgartner/why-data-and-analytics-are-key-to-digital-transformation/

2. Infonomics, https://www.gartner.com/en/publications/infonomics

There’s no escaping the increasing reliance on advanced data analytics. Your credit union’s data is a critical asset you have that can anticipate member needs and allow you to execute personalized interactions.

How do you make a data analytics strategy work for you even more in the coming year?What do you need to include in your 2020 initiatives?

How do you plan a strategy that delivers insights that can be turned into tangible business outcomes – insights that help you increase your credit union’s performance and drive greater efficiencies?

Most failed data analytics strategies can be traced back to the fundamental error of focusing solely on the technology and not the credit union’s vision, mission and strategic goals.  As you plan for your 2020 Data Analytics Program, consider these key action plans to ensure a successful data analytics strategy and outcome:

1. Identify organizational strategic priorities and align the technology solution accordingly.
2. Establish a data warehouse to centralize data integrated from several applications.
3. Identify and plan for tangible and measurable use cases.

Business Objectives, Strategy and Technology Alignment:


Too often, executive teams have an unclear strategic direction with regards to their data analytics investments and how they align with their corporate objectives. In these cases, I recommend that the team take a step back and work on clarifying the overall strategic direction and outlook. Without this direction as a guide, the credit union’s technology decisions end up driving the overall strategic direction instead of the strategy driving the technology.

Your data strategy and strategic priorities should include:

  • A strategy defining your how analytics will help drive the credit union’s strategic priorities
  • A tactical roadmap describing how you will accomplish the analytics goals outlined
  • Plans, tactics, and processes to develop analytics skills and create a data-driven culture that embraces the daily use of data analytics

Clearly understand and outline the long-term strategic goals of the credit union (i.e. growth, branching, new products and services, etc.) to identify and select data analytics solutions that fit your requirements both today and, more importantly, where you want to be in the future. Otherwise, you run the risk of a costly blind spot: investing in software that doesn’t fit the credit union’s vision, and the cost of converting later can be significant.

Implement a Data Warehouse:

The foundation for a successful analytics program is data. But, without accurate and quality data, it’s nearly impossible to make informed business decisions. As data becomes an even greater asset for the credit union, the ability to store large amounts of complex data in a unified, central database, known as a data warehouse, is critical.  This single source of truth is the repository for all the data that has been collected and integrated from multiple sources across the organization. Everyone in the credit union is using the same data derived from the same source, which leads to quick, easy access to accurate data and better decision-making.

Measure and Monitor Success:

Tracking and measuring the ROI of an analytics program allows the credit union to re-prioritize goals and take corrective action steps along the way. By measuring the action taken from the data’s prescriptive recommendations, the credit union can focus efforts on the most promising and revenue-driving opportunities, resulting in an immediate boost to earnings and member service and resources. Once key data segments are identified, efforts should be focused on the campaigns that delivered the greatest ROI and devise a set of recurring best practices for future campaigns.

Some tangible and measurable data analytics use cases The Knowlton Group clients have experienced include:

 Effective Marketing and Segmentation:

Deeper, data-driven member insights are critical to tackling challenges like improving member conversion rates, personalizing campaigns to increase revenue, predicting and avoiding member churn, and lowering member acquisition costs. Deploying member segmentation such as geographic, demographic, behavioral and other categories will help your organization target the right products and services and help reduce member churn. Using data analytics, you can successfully segment your members data, and invest more resources into those members who are most likely to respond to your product offerings.  You can then further refine your messaging and product/service offering to retain their loyalty.

 Enhance Member Experience:

Analytics also has the potential to identify the needs of new and existing members, so the credit union can effectively match the best products for them. For example, the credit union can use call center contact information, new member questionnaires and other behavioral attributes to predict what type of products would be the best fit for a new and existing member.  By matching members with the right products and services, the member is less likely to have complaints or start looking for better services elsewhere.

Elevate Efficiency:

Advanced data analytics provides credit unions with intelligence to make better, faster and smarter decisions. This knowledge leads to reducing duplicative systems, manual reconciliation tasks and redundant information technology costs.

 Improve Analysis of Transaction Data:

Your members’ transaction data is a goldmine of information and opportunity.  Deploying transaction categorization and classifications allows for the combining of ACH, Debit Card, and Credit Card transactions into a single view.  You get clean and standardized merchant information to gain the most value out of the data.  And you can identify where your members are spending their money and to which competitors’ payments are being made.  By categorizing member data into tiers, you have the greatest opportunity for deep analysis of transaction behavior.

Refine Member Engagement

Utilizing a member engagement analytics model, the credit union can assign an engagement score to each member based on all member activity.  It will enable you to separate members into defined segments based on their engagement and can create recommended action to take for each segment so you can continuously improve member engagement scores.

 The Right Guidance Leads to Success

Looking for help with developing your data strategy and plan for analytics?  The Knowlton Group is staffed by resources with both extensive technical analytics skills and decades of a line-of-business strategic leadership knowledge.  We work with many credit unions– helping them understand the full impact of data analytics to their business model, define a compelling data analytics strategy and ultimately provide results. From strategy, to conceptualization to full implementation, we are ready to make your credit union a data-driven organization. Contact us today.