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Archive for nonprofits

For Nonprofits and Associations, the Time is Now for BI

Business Intelligence can improve nonprofit and association decision making.  Most of us are familiar with the scenario where we extract information from a variety of different systems that each serve their own purpose, but are not integrated.  In recent years, there has been a push to integrate systems or to try to put everything into one multi-purpose system, like an AMS (Association Management System) or CRM (Customer Relationship Management).  There are certainly benefits to this especially for the front-end users and customer service representatives.  However, there are challenges as well.  For example, it often will slow down a transactional system to store every email that was ever sent to a member.  It may also be cost prohibitive to have a real-time integration between all of your systems.

A Better Way

time_to_goTo evaluate if this situation is optimal, ask yourself if right now you could accurately measure engagement across all channels and programs.  The goal is to not only enable you to increase that involvement, but also to clearly demonstrate the positive impact your association or nonprofit has on your sphere of influence.  I’ve often found that this broad level of analysis can be elusive.  When your board asks for this information, you may have to spend days pulling information from all of your systems and trying to come up with some form of analysis.  But don’t forget to save those complex spreadsheets and don’t forget how they were created so that they can once again be recreated next month!  This kind of activity is what makes me cringe and think, there has to be a better way!  The exciting news is that there is a better way and it’s not as hard as you might think.

Private Sector Paved the Way

The private and commercial sector has already set the stage.  It’s like having a big brother or sister that pushes the boundaries, makes mistakes, and figures out the best way to excel.  Now associations and nonprofits can learn from their mistakes, modify their path to meet our unique needs, and off we go.  The commercial sector has proven the value of Business Intelligence (BI).  Which is, simply stated, transforming data into meaningful information that can be used to make good decisions.  However, remember that the technology is just the enabler – the “tools” to get the job done – it’s people who are the differentiators.
BI can be used to bring together disparate data sets so that historical analysis and predictive modeling can guide decision-making.  It can also be used to supplement your standard customer data with social media content, including customer’s interests, purchasing behavior, and social circles.  What if you could find those customers who spend very little money with your association, yet enjoy being a part of it, and also have a huge circle of influence?  You could reach out to them to help promote your organization.  BI can also identify the key metrics which will help determine overall effectiveness in your space.

BI is Expected

I’m sure you’ve heard about Business Intelligence by now – it’s been a buzz word for a long time and in fact is almost overused.  But the time to act is now.  If your competitors aren’t using it, they will be soon and have you stopped to think that the private sector is a competitor these days?  Especially with respect to content, education and networking.  Chances are your customers are already using BI (or analytics), even if they don’t realize it.  Each time they purchase something at a large online retailer and see things like “other customers have bought this” or “you might also like”, they are reaping the benefits of BI.  It’s something they’ve come to expect.  They also want a custom, user-centric experience from you.  In order to provide this to them, you must first understand them.  You likely already have that information, you just need to harness it.

Get Started

To get started, take a look at my previous blog, Preflight Checklist for Association Business Intelligence. This blog outlines a few preliminary steps you can take now on your path to using BI and making data-driven decisions.

Top Trends in Business Intelligence for Associations for 2014

Top Trends in Business Intelligence for Associations for 2014
Tableau software recently compiled their set of Top Ten Business Intelligence Trends for 2014. Not all of these trends will be impacting the association space. Some of these trends are more relevant in the corporate space, but could become more relevant as more time passes and technologies are less expensive and accessible. In this blog we will review the trends compiled by Tableau as well go in depth on the trends that will directly affect you and what you should do about it.
Below is the Top Ten list as published by Tableau.

  1. The end of data scientists. Data science moves from the specialist to the everyman. Familiarity with data analysis becomes part of the skill set of ordinary business users, not experts with “analyst” in their titles.
  2. Cloud business intelligence goes mainstream. Organizations that want to get up & running fast with analytics drive adoption of cloud-based business intelligence. The maturation of cloud services helps IT departments get comfortable with business intelligence in the cloud.
  3. Big data finally goes to the sky. Cloud data warehouses like Amazon Redshift and Google BigQuery transform the process of building out a data warehouse from a months-long process to a matter of days.  This enables rapid prototyping and a level of flexibility that previously was not possible.
  4. Agile business intelligence extends its lead. Self-service analytics becomes the norm at fast-moving companies. Business people begin to expect flexibility and usability from their dashboards.
  5. Predictive analytics. Once the realm of advanced and specialized systems, will move into the mainstream as businesses seek forward-looking rather than backward-looking insight from data.
  6. Embedded BI begins to emerge, in an attempt to put insight directly in the path of business activities.  Analytics start to live inside of transactional systems.  Ultimately, embedded BI will bring data to departments that have typically lagged: for example, on the shop floor and in retail environments.
  7. Storytelling becomes a priority, as people realize that a dashboard deluge without context is not helpful. Stories become a way to communicate ideas and insights using data. They also help people gain meaning from an overwhelming mass of big and disparate data.
  8. For leading-edge organizations, mobile business intelligence becomes the primary experience, not an occasional experience. Business users begin to demand access to information within the natural flow of their day, not back at their desks.
  9. Organizations begin to analyze social data in earnest, gaining insight beyond number of their likes and followers. Social data becomes a proxy for brand awareness and attitude, as well as fertile ground for competitive analysis.  Companies begin to use social data to understand how relevant they are to their customers.
  10. NoSQL is the new Hadoop. Organizations explore how to use unstructured data. NoSQL technologies become more popular as companies seek ways to assimilate this kind of data.  But in 2014, the intelligent use of unstructured data will still be the exception and not the norm.

Of these trends, only some will impact your association in 2014.  Below we have provided you information on the relevant trends to take to your executives to make sure you can stay ahead of the Business Intelligence curve.

  1. The end of data scientists. Most associations don’t have the resources for full time data scientists. Instead associations are putting the power of data-driven decisions in the hands of staff across departments. Staff will be trained on analytical skills that can be applied to their daily routine and need for information.
  2. Cloud business intelligence goes mainstream. Cloud-based solutions help associations to more quickly and often more economically begin using business intelligence. It also puts the data in the hands of everyone and anyone with internet access. Data belongs to the association business staff and the IT staff facilitates the management of this important asset.
  3. Agile business intelligence extends its lead. In the association space, DSK incorporates key aspects of agile processes to business intelligence initiatives because it dramatically increases the probability of a successful outcome. Typically, associations do require an estimate up front for budgeting purposes, but the scope and development are best performed in an agile, iterative fashion. See our blog post from last year about Agile Business Intelligence.
  4. Storytelling becomes a priority. We often believe data is a flat object, but viewed in context it has the power to tell a story about what is really happening.  We believe that through data discovery, association staff can learn to understand the story their data is telling. And once the story is understood the story, you have the power to can change the ending! Through the use of interactive data visualizations, your data can be analyzed in ways not thought of previously. 

Can you see your association following these business intelligence trends in 2014?

How to Choose the Right Visualization for your Association

Choosing the right data visualization is as important as choosing the right outfit to wear to an important meeting. Although your alma mater’s sweatshirt is perfect for the ball game, a suit and tie is more appropriate when trying to convince your board to increase your budget. Similarly, you are going to catch some flack for showing up to the game in a suit and tie! Choosing the right visualization for your audience is similar to choosing the right outfit for the function.
Did you know that the human brain is able to process images three times faster than text? From our primitive beginning, we’ve depended on our brain’s ability to detect subtle patterns and interpret meaning. So, how do you choose the right visualization? Let’s take a look at some common types of visualization and when they should be used to effectively communicate the story your data is telling.



  • Best used when exact quantities of numbers must be known.
  • Numbers are presented in rows and columns and may contain summary information, such as averages or totals.
  • This format is NOT favorable to finding trends and comparing sets of data because it is hard to analyze sets and numbers and the presentation is cumbersome with larger data sets. It is estimated that the visual working memory has a capacity of about seven items. This means that you can store up to 7 bits of information (like numbers) in your brain’s “RAM” simultaneously. If you build a table with financial information for each month of the year for different areas of your association, it becomes difficult to find outliers or even the most profitable month.
  • This kind of visualization is likely what many association staff are accustomed to (think of all those excel spreadsheets floating around your office) so you may need to use a tabular format in conjunction with one of the other types listed below to convey the information.
  • A variation of the tabular chart is a highlight table. A highlight table applies color to the cell based on its value. The use of color can make outliers stand out more.

 Line Charts

line chart

  • Best used when trying to visualize continuous data over time.
  • Line charts use a common scale and are ideal for showing trends in data over time.
  • Example: membership or registrant counts throughout the year compared to previous years.
  • Trend lines and goal lines can also be added to compare actual counts with certain benchmarks.

Bar Charts

bar chart

  • Best used when showing comparisons between categories.
  • The bars are proportional to the values they represent and can be shown either horizontally or vertically. One axis of the chart shows the specific categories being compared, and the other axis represents discrete values.
  • Example: Bar charts can be helpful when looking at certain segments of your customers, registrants or members.
  • Goal lines can also be added to compare the actual counts with your benchmarks.
  • A variation of the bar chart is the stacked bar chart. This incorporates the use of color to visually show how certain segments add up to the total. In the example above, it’s easy to see that while 2010 Conference attendance counts are higher, the number of Paid attendees actually decreased from the previous year.
  • Another variation of the bar chart is called a bullet chart. This chart allows you to take a single measure (for example, revenue) and compare it to another measure (for example, revenue goal). It also can display percentiles.

bullet chart

Pie Charts

pie chart

  • Best used to compare parts to the whole.
  • Pie charts make it easy for an audience to understand the relative importance of values.
  • Using this format for more than 5 sections is not recommended as it can become difficult to compare the results. Too many sections make interpretation difficult because the difference between the sections can become too narrow to effectively interpret.
  • Often, even when wanting to compare parts to the whole, a bar chart can be more effective.

In addition to difference chart types, the use of filters and sorting is important to increase the association staff person’s ability to explore the data in more detail.
The goal of any visualization should be to communicate the information in the most concise and impactful way by using the appropriate visualizations for your data.  Effective visualizations enable your audience to quickly understand the story in the data and speeds the ability for association staff to reach key insights.

7 Business Intelligence Mistakes Associations Should Avoid

failure_successThe private sector and government organizations have been using Business Intelligence (BI) for over 15 years. The good news for those of us in the association space is that we can learn from their mistakes and avoid them when starting BI programs for our associations. Below is a summary of common mistakes and how they can be avoided.

1. Not Solving a Real Business Problem

It’s easy to get caught up in the hype of business intelligence. It’s cool, it’s great for your resume and you may be getting pressure to just get it done. However, too many organizations fail to focus on the real business problems and opportunities they should address. Even if IT is ready and willing to take on a BI project, the initiative will fail deliver a return on your investment if it is not directly connected to addressing the problems and opportunities the association needs to address.
First identify and prioritize the business situations that need attention. We advise our clients to begin small.  Start with an area that will yield measurable benefits (such as Finance or Membership) but initially select an aspect of the area that can be analyzed in a relatively short time-frame.  A skilled analyst can collect requirements, conduct interviews, and facilitate group sessions focused on identifying and describing the challenges and opportunities facing the association and how they tie to the association’s strategic plan. Working as a team the analyst, business users, and technical resources locate and document the available data sources as well as identify the gaps in which essential data is not being collected. Once this information is gathered, requirements are grouped into logical areas.

2. Focusing on the Dashboard

You may have seen impressive examples of flashy dashboards from BI vendors, media outlets, or personal websites. It is easier than ever before to grab data from any source and present it in a visually pleasing matter. However, to make that visualization meaningful and actionable for your association, you will need to determine what will help your specific organization. Even in the association space, what makes sense for one group can be completely meaningless for another. Spend your time and resources to find and prepare data that will provide meaningful information to allow business users to make better decisions.  You can use the flashy visualizations and dashboards as inspiration once you have the underlying data and business questions formalized.

3. Not Including Business Users when Data Modeling

Data modeling is a task performed by the technical team. However, how quickly business users embrace and adopt BI solutions often comes down to how the data is organized. The data needs to be organized in a way that makes sense to the business so that they can interact with it by having “conversations” directly with the data.   The technical complexities of a highly normalized transactional data model should be abstracted so that the business user interacts with familiar objects and attributes with friendly names. Discussions with business users should be conceptual, not technical. In addition to technical documentation, documentation should also be created to capture the concepts and components of the data model in a way that business users can understand.

4. Lack of Communication

Too often business intelligence projects start off strong. Requirements are gathered, discussions with business users are held and then IT goes off into their private corner to design and build a solution. They may be working hard and making progress, but the business is left in the dark. Regular communication with the core team, including in-person meetings, frequent demos and status reports are vital. When IT and the business users communicate regularly about the progress, adjustments can be made which improve the outcome.  BI is a business initiative and technology is the enabler.  It is not a technical project that should be foisted on the business.  Our experience has proven to us that collaboration and communication is the most essential ingredient in a successful BI program.

5. Not Providing Education and Documentation

Although many BI visual interfaces are built to be intuitive and use features users are already familiar with, training is absolutely necessary. At a minimum, the staff need to know what data is available and how it is organized. They also need to know how the data and the analysis applies to their day-to-day work. Staff members also must be provided with technical training on how to use the tool. Just like any software or technology, ongoing training is needed to provide continuity in the association as people move to new positions or are new to the association.
Documentation should also be provided. First, documentation about the published dashboards should be created. This includes topics like the name, location, business description and the business owner. Documentation about the data is also important. This includes the business name for each attribute and measure, business description, and the calculations used to create the measures. Develop documentation as you go. If you leave it until the end of the project, it has a way of falling to the wayside as deadlines near.

6. Not Providing Support after Development

Everyone is clamoring for more self-service. This term means different things to different people, but in the BI world this often means that the business users can go get the information they need without asking technical staff for help. This could involve the ability to drill-down for more details and/or change the filters or even create new visualizations. However, self-service does not mean that once the datamart is built and the BI tool is installed, IT is finished. IT must continue to be involved to ensure that the offerings continue to meet the needs of the business. Often, more data can be brought in and more analysis can be performed after the initial offering is a success. The needs of the association will evolve and the BI solution must also evolve.

7. Not Measuring Results

After the investment of time and energy to create a BI environment, sometimes organizations neglect to track the results. What you want to determine is if the initial business questions have been answered and if the business situation is improving. For example, if your initial business question was “How can I increase my membership retention?”, then evaluate if the BI solution added value by determining the improvement in the retention rate after BI enabled you to identify and connect with “at-risk” members. It is essential to track successes by quantifying and documenting when BI has resulted in an improvement in a key result or key performance indicator (KPI). This should be shared on a regular basis during staff meetings. Success stories justify the original investment and support future phases.


If you’ve made these mistakes before or see them happening now in your association, you are in good company. Some of these mistakes have been made by the best run and smartest companies in the world. The great news for associations and  nonprofits is that because we know what these common mistakes are, we can take deliberate measures to avoid them.
“A smart man makes a mistake, learns from it, and never makes that mistake again. But a wise man finds a smart man and learns from him how to avoid the mistake altogether.” –Roy H. Williams

How to Create a Data Inventory for Associations and Nonprofits

Locating Your Data

Do you know where all your data is? Associations, like all businesses, have so many working parts that it can be difficult and time consuming to keep information both centralized and easily assessable. However, in the age of data analytics, it has become even more critical to know the location and importance of your data in order to use it to fulfill your mission.
After many years of working with clients, DSK Solutions has found that the first step to a successful BI strategy is to scope the project: outline what you already know and document your business questions.

Steps to Take

Begin by identifying your data sources:

  1. Data source name
  2. Location and server name
  3. Database/data mart/warehouse name
  4. Application name
  5. Format
  6. Size
  7. Update frequency
  8. Primary tables/cubes/lists
  9. Approximate number of rows/columns for primary tables
  10. Internal/external keys for primary tables, dimensions for primary cubes
  11. Names of external systems that provide data to data source:  Frequency of external system input and method of integration
  12. Names of external systems that this data source provides data to:  Frequency of system output to external systems and method of integration

Then, identify the more qualitative features and value:

  1. Purpose
  2. Importance
  3. Data sensitivity, security/compliance requirements
  4. Known data quality issues/current cleansing process (e.g., duplicates, missing information, etc.)
  5. Data owner or name of person/dept. responsible for data source
  6. Reports/exports produced from this data, departments using these outputs

Finally, connect your data with your important business questions:

  1. What role can data play in achieving your mission?
  2. How can you map your data to your strategic plan?
  3. What metrics reflect your most important data?
  4. How can you best collect and integrate your data to get a 360 degree view of your members and prospects?

We’ve helped many associations and nonprofits create a data inventory like the one depicted visually below.  One of the first steps in the process of analyzing data starts by creating a data inventory.
Data Inventory

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