And while no one technique can ensure a dashboard will deliver value, there are some key steps that can materially improve the success of your business dashboards.

Start Early, Ask Questions

• How well do you know your audience? While you may know the data, the end user knows the business. Before you meet with them, do some preparation work on possible data sources you might need, and identify questions you know you’ll need answered. When you meet, start with broad questions and work down to detail.
• What do you want this dashboard to do for you in a perfect world? Use your first meeting to get to know the big-picture needs of the team who will use the dashboard as well as the details of how they’ll use it. It can also spur conversation on content that is easy for you to include but they may not think to request.
• What are the next steps you want to take? Someone on the front line of a credit union will have different dashboard requirements than a board member reading a summary. Do they need to take an action you can build, like a link to another specific report? Or just understand big-picture trends? If they want to export data to Excel for additional analysis, find out what that analysis is you may save them valuable manual time.
• What detail-level data needs to be included? While the goal of the dashboard might be to understand call center volume, they may want to be able to see that information in more granular detail. By CSR name? By using a unique identifier of some kind?
• Who will use this besides you? This is an opportunity to make sure you don’t miss additional use cases that could make the dashboard easier to understand for many users.

Confirm Hands-On Specifications

• Were there any specific visuals you had in mind? Some people can be very particular they may even have another image or dashboard in mind when making the request. Consider what they already have access to and even bring examples of other dashboards with you; sketching visuals on a napkin or iPad can be a useful way to get on the same page with others before wireframing the project.
• What filters would you like on this? Should any data be excluded before it reaches the dashboard? (A colleague once spent days working up a mortgage dashboard and included HELOCs, which weren’t of immediate interest to those who would be reading it.) This is an easy way to save time and demonstrate skill with your audience.
• How fresh does this data need to be? Find out the time frame of the data they want shown by default and how often they want it refreshed. This gives you an opportunity to make sure your dashboard provides relevant insights while saving development time if less customization is necessary. In addition, it creates an opportunity to manage expectations if you are not able to provide near-real time information.
• What are your KPIs? The best dashboards take you through the most important information first, then allow users to drill into what they need to know. Identifying specific KPIs to highlight is important for visual impact and can reveal additional questions you need answered and help focus your data sourcing tasks.

Click here to learn more about how PenFed’s Mortgage Analytics team learned to iterate and build more actionable dashboards in the process.

PenFed’s mortgage team went through multiple versions of their core dashboards, working to incorporate best practices, highlighted here. Click to enlarge.

Manage Expectations & Build Relationships

• Start smaller than you think. The above covers a lot of ground but don’t be afraid to break someone’s dream dashboard or suite of dashboards down into pieces. What is most important and could be most useful to have right away? Identify this and work to secure something you can deliver sooner rather than later, then plan and communicate how it will be added to and when.
• Set expectations for iteration. Focusing on value-added low hanging fruit can jumpstart a business unit’s relationship with business intelligence or analytics. Ensure you have clear, feasible deadlines communicated on both sides. In your kickoff meetings, emphasize that back-and-forth dialog is a requirement and that you’re there to get them what they need.
• Meet before your final reveal. Checking in along the way is essential to avoiding a disappointing dashboard unveiling. Depending on your credit union’s preexisting data quality, you’ll want to make sure that your calculations or sources align with any the unit requesting your work is already using. If they see numbers that immediately differ from their own, it erodes trust and creates delays and more work. Similarly, you can use check-ins to ensure that the dashboard’s design is suited to the audience’s needs and preferences. Always be ready to iterate and build in time to have these necessary back-and-forths, while also being cognizant of the requestors time.
• Future-proof your work. When you hand off a dashboard, keep in mind any training the users may need, including how to access the dashboard, use filters, export, and request help or changes from you as the creator. Create a reminder for yourself to check in on how the dashboard is performing for the requestor or even schedule a meeting in the future to confirm how well it’s working. These conversations can help avoid abandoned dashboards and create opportunities for the team to make a given dashboard more useful.

In this webinar, Kelly Gage of Red Canoe Credit Union ($1.1B, Longview, WA) talks more about best practices for business intelligence requests.

As relationships between business units and their embedded analytics experts or any stand-alone analytics team develops, iteration will be required. Patience and open communication are key. Along the way, the report builders will get better at fielding questions, asking questions, and keeping projects moving. Dashboards can be powerful tools for any credit union, fed by anything from a set of key Excel documents to an advanced set of data warehouse sources. Regardless of where your credit union stands in their analytics journey, dashboards, when done right, allow the business to come together around one source of data-driven truth and see, explore, and ask more questions about data that can reveal new and improved ways to deliver value back to the member.

The post Build A Better Business Dashboard appeared first on CreditUnions.com.

Set overall dashboard size

To set the overall size of a dashboard:

• Under Size on the Dashboard pane, select the dashboard’s dimensions (such as Desktop Browser) or sizing behavior(for example, Automatic).

Group items using layout containers

A layout container is an optional way to keep views and objects together. It helps groups of items resize and change position when users interact with your dashboard so that the dashboard doesn’t include white space that you don’t want.

The image below shows how a dashboard behaves when two views are placed in a vertical layout container versus how they behave when they are not placed in a layout container. Notice how, in the dashboard that uses a layout container, the views adjust vertically as different filters are applied.

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In this rapidly changing environment, how can industry leaders determine how their institutions are faring? For starters, by understanding their credit union’s financial performance against the context of the wider financial services industry.

The interactive dashboard below does just that. It provides a baseline review of loan performance for any credit union plus an asset group. To use it:

• Select a primary institution and a peer group comparison.
• Click on a button to view product-level detail.
• Hover over the charts to see actual values.
• NOTE: Peer group values are in averages.

Once leaders have a reference point for their credit union’s performance, they can focus strategic planning where it matters the most and reduce the likelihood of making decisions based on intuition or emotion.

When it comes to comparative analysis, this is a drop in the bucket for Callahan & Associates. Learn how our market-leading comparative analytics tools can empower leaders at your institution.

The post How Does Lending At Your Credit Union Perform Against Peers? appeared first on CreditUnions.com.

That is by no means to say that business intelligence is not on the rise in a major way among credit unions far from it. Rather, I ran into a highly stratified landscape of different approaches to and readiness to deploy what we know as Big Data.

A single credit union is, in principle, meant to do the best it can for its members. As such, my first question was, how do credit unions look after and make the most of their own data the activities that form the core of business intelligence. And second, what activities and players within the credit union industry help credit unions leverage their own data and analysis within the spirit of the cooperative movement?

My colleague Chris Howard kicked off 2016 by challenging us to think about the role of disruptive collaboration in the industry in this and years to come. Business intelligence-driven advanced data analytics will offer value when it allows credit unions and, notably, CUSOs to deepen the impact of financial cooperatives in the lives of the Americans.

Read more about Chris Howard’s view of disruptive collaboration in, Disruptive Collaboration Is A Big Idea For 2016

This brings me back to my initial question. What are individual credit unions doing with business intelligence and where does the potential lie for them in future?

Big Money, Big Data

The credit union industry is home to many institutions that are taking cutting-edge approaches to business intelligence. Although these are not limited to the $1 billion-plus players, there is certainly a correlation between asset size and the ability of a credit union to devote time and resources to the life of its data. Even the NCUA is on the Big Data/business intelligence train: the regulator is now seeking credit union input on how the regulator can best upgrade its own systems to optimize exam efficiency and information gathering.

Naveen Jain at First Tech Federal Credit Union ($8.7B, Mountain View, CA), not coincidentally located in the heart of Silicon Valley, has been singular in developing a comprehensive and elegant design for First Tech’s entire business intelligence process.

How do credit unions look after and make the most of their own data – the activities that form the core of business intelligence. What activities and players within the credit union industry help credit unions leverage their own data and analysis within the spirit of the cooperative movement?

What does this look like? At the core of effective business intelligence is a credit union’s data, and the institution must determine how to make it accurate, how to store it, and how to use it in iteration.

Credit unions like First Tech make use of sophisticated systems that bring together their data on everything from core banking and credit cards to branch performance and call centers. From there, they manage and warehouse data, making it available for deployment by different business teams, from marketing to accounting. The operational complexity of this requires state-of-the-art technology and people who are experts in everything from SQL, data analysis, and database administration to data visualization and automated marketing.

But What About Everyone Else?

A lot of these systems are slick, which got me thinking about what this sophisticated technology with all its demands on financial and human resources means to smaller credit unions? What value does Big Data, or any data, bring to them and their members?

Over the past decade, there has been a slow rise of BI across the entire industry, beginning with making better use of data shared with providers. Some of this has been frustratingly piecemeal for example, a credit union could look at a report on credit card use trends at the end of a month and draw analytical conclusions or compare two reports covering different pieces of a member’s use of their credit union resources. But how could an institution bring them together? How do credit unions use multiple data sets together to inform decision-making in a way that benefits members?

Want more business intelligence and Big Data? Check out, A Strategy To Build Business Intelligence Across A Credit Union and Analytics And Marketing In The Era Of Big Data.

At Charlotte Metro ($374.2M, Charlotte, NC), Paul Leavell has been forwarding the idea that the first step toward effective business intelligence is to understand that even little data can be incredibly impactful without sacrificing the requisite thoroughness and accuracy that is core to the concept of Big Data.

He and colleague David Cooper put together the Cooper-Leavell Matrix, which has allowed them to guide creative and tactical marketing through the segmentation of data into three size buckets. Positive ROI and member response came out of their approach, which acknowledges that not every credit union can readily capture and analyze Big Data. As such, they find ways to make use of data they can handle with the resources and requirements they have.

The Cooper-Leavell Matrix is a way to categorize data in terms
of its accessibility and utility.

Scalability is at the heart of Charlotte Metro’s matrix approach. In the process of making strides in its facility with small data and working to push its use of middle data, it made improvements to its data warehousing and reporting processes. It also was able to parse out information such as who made charges at a baby store and might be a good marketing target for an auto loan (a new minivan, perhaps?) or mortgage.

Where Do CUSOs Fit In?

We’ve seen among small- and mid-sized credit unions that dedication to incremental improvements to their data warehousing and analysis efforts deliver cumulative results. This is often achieved through partnerships with CUSOs.

What more potential is awaiting credit unions as data and analysis become a part of the knowledge sharing and cooperative business model?

Next week in Minneapolis, the Analytics and Financial Innovation (AXFI) Conference will bring CUSO and credit union leaders together to talk about how the movement must make analytics and innovation core to business strategy and must do so now.

The AXFI Conference is an example of vendors and credit unions focusing on analytics beyond simply focusing on the sales cycle. This type of partnership is true to the cooperative spirit and also essential to meeting the challenges posed by the rapid pace of analytical innovation across the financial services space.

CUSOs have been key strategic partners for credit unions in the rise of effective business intelligence. Many organizations are working at great speed to deliver the next-generation systems that credit unions need or will soon need to match the pace of innovation set by competitors. OnApproach, one of the primary sponsors of the conference, offers a range of solutions that fit with different credit union needs. It also partners with other data analytics CUSOs, including Denali Alaskan Federal Credit Union’s Deep Future Analytics as well as the Knowlton Group.

The collaborative model is the best – and perhaps only – way credit unions can compete in the critical realm of business intelligence and the Big Data is requires. Read more about this advantage in, Of CUSOs And Big Data

This kind of cooperative innovation enables credit unions of more varied sizes access to higher-level analytical tools than they would be able to develop in-house. Such services, of course, are aligned with the purpose of CUSOs, but I am struck by the teaming up of minds and systems in which these groups are enthusiastically engaging.

Although the pace and the look of business intelligence at credit unions varies considerably, the benefits are consistent and the need for continued focus on all things data is paramount. As the industry advances, the opportunities presented by nimble, data-driven pricing or predictive modeling are immense.

What more potential is awaiting credit unions as data and analysis become a part of the knowledge sharing and cooperative business model?

Although credit unions can talk about data incessantly, the real focus remains upon the member. Data and the analysis of it aids in the understanding of what members are doing and what they want from their credit unions. And it is data that enables credit unions to deliver that in ever more personalized ways.

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