Archive for Change Management

Failure Enables Success

The ASAE Technology Conference is next week and features of a tagline of “Revolution and Evolution”. These terms cover the concepts of both reward and failure. Speaking of failure! A fun part of the event is ASAE Fail Fest!

This session is a celebration of mistakes and mishaps, but most importantly recognizes that failure is a key part to innovation and improved growth. This particular session includes leadership who tell stories about how they have failed in the past but learned from their mistakes to create something even more innovative.

In the world of data-guided decisions, it is highly important to have the needed mindset, culture, and technology to accept failure as a possible outcome.

How did we get here?
Association customers over the past decade have a growing number of options and increased expectations. This means we must continuously innovate to remain competitive. However, we still often don’t take needed actions for fear of failing. Why? Because doing nothing is not generally viewed as an action with potential failure.
– People can get caught up in previous high-profile fails and allow these legacy events to impact innovation.
– Time spent planning and researching an approach is often viewed as more acceptable than actually trying the new approach.
– There can be a bias toward new and modern ideas, and away from things that might be tried and true.
– Perceived preferences of leadership can cloud judgement and make good ideas seem like non-starters.

So, how can we change this?
First and foremost, failing must be accepted and built into decision, innovation, and project processes. This is the process of trial and error. We learn from our mistakes to get to the best solution. Here are a few examples of a new value system to consider.
– Lack of trying taking risks should be viewed as missed opportunities!
– Encourage ideas to fail fast, as opposed to fear of admitting failure.
– Understand sunken cost vs future cost, meaning you should not continue something based on time and money spent in the past.
– Beware of the clichés. The idea that “the fee is the cure” implies that you should continue down a bad path based on sunken costs.
– Understand risk tolerance to ensure the cost of failures aligns with association time frames and resources.
– Communicate the cost to correct potential failures as this helps consider the benefits of opportunities.

Why are we so afraid to take the leap?
Like viewing no action as a potential fail, it is important to consider lost opportunity against the cost of failure. One example is the vital task of measuring the success of predictive analytics models.
We might have a model that estimates the propensity for individuals to attend an annual meeting along with segmentation for personalized marketing. Measuring the model requires a “holdout” group of individuals to not receive certain marketing efforts.
Since success is commonly measured by granular registration characteristics such as weeks out and registration type compared to prior years, it can be difficult for people to purposefully limit marketing. This is an important act that requires thinking in terms of broader, lost opportunities.

How does Association Analytics accommodate failure?
As a product-focused organization Association Analytics (A2) carefully balances accepting failure as part of our innovation mindset as well as mitigating it’s impact.

Examples of our own fails:

– When we first began using AWS Redshift, we were instructed by a person of perceived authority to load one record at a time using an API. This appears to be a modern approach as opposed to the seemingly legacy solution of moving around text files but loading text files in bulk is clearly the proper approach.
– It’s always ideal for analytics applications to interact with cached data optimized for performance. We’ve created data sets for high-transaction business events only to reach volume limits. We solved this by reworking the data set to leverage a hybrid approach of cached data and direct queries.
– We’ve used database drivers to accommodate performance, only to later discover limitations enforced by analytics tools. We had to rework solutions using a combination file edits and tedious client-based changes.
Mitigations that make something even better:
– Analytics solution. Analytic solutions are rapidly changing in terms on cost, features, and part of a broader ecosystem. We design our data architecture to be independent of analytic solutions to allow future portability.
– Data architecture. Data warehouse implementations can be costly and time-consuming when not based on industry-specific reference models, such as Acumen. Another solution is a “data lake” approach that makes rapidly available in rawer formats.     – Technology selection. Choosing a technology requires a balance between future features and current staff skills. We’ve selected our technologies, such as Python for various API integrations, based on future market direction and make hiring flexible and agile staff a priority.

Now, what can our leaders do to help?
As we’ve often said, people are more important than technology. Association leadership can enhance innovation by accepting fail in a variety of ways.

– Make failure part of the process. This demonstrates that failures should be managed and are acceptable.
– Think holistically and consider the collective association. Testing predictive models can harm attendance of a few events why significantly improving many others.
– Encourage prototyping and experimenting. The availability of cloud technology platforms makes this efficient.
– Celebrate and publicize failures. If someone takes an innovative course of action that is not successful, communicate that this is needed for innovation.
– Encourage questioning of real or perceived assumptions and bias. Staff might immediately dismiss ideas based on leadership views. Challenging these impressions should be welcome.
– Don’t extrapolate past failures. Understand that not all fails are the same and learn from the past without stifling innovation.
Associations should accept that failure in some respects is an option by not viewing it as an overwhelming tragedy and, of course, try to attend ASAE Fail Fest with us!

 

Matt Lesnak, VP of Product Development & Technology
Association Analytics

Your Association Needs An Analytics Translator

If you have a data analytics team or you are in the process of forming one, the analytics translator is a role to consider hiring for. This individual plays a critical role on that team and at your organization. She or he serves as the link between the analytics team and the executive team because this individual takes the information from the data team and translates it on a broader scope, so stakeholders can see how analytics impacts the organization.

Think of the analytics translator akin to a marketing operations manager at a B2B or B2C company. A marketing operations person is a subject matter expert on marketing technology solutions and typically works very closely with the executive teams. That individual also oversees the implementation of a marketing automation system, the data, and the processes to support the organization. A person in this role also works with the demand generation team to support any campaigns they want to execute and provides the metrics and reporting. She or he has both qualitative and analytical skills and possesses superb communication and project management skills to be successful in their role.

So, what does an analytics translator do then? According to Mckinesy and Company, someone in this role “communicates data science features and capabilities to internal and external stakeholders in order to identify business needs and uncover areas in need of deeper data exploration.”

Ideally, an analytics translator possesses the technical fluency in analytics, strong project management and communications skills, and a keen interest in staying current with industry trends.

Now you might be thinking that your data analytics team already has many of these skills, but the analytics translator is truly a unique role that an organization benefits from having. Here are 3 reasons your association needs to bring an analytics translator on staff.

1. Help demonstrate how analytics solves business problems

Analytics continues to play an instrumental role at organizations because it helps staff members make data-guided decisions to help them better align with their overall organization’s goals. Sometimes one person (such as a data analyst) alone cannot convince their executive board that a data analytics platform is a worthwhile investment. In some cases, it takes someone such as an analytics translator to convey the need to purchase an analytics tool because this person has the expertise to communicate how it can truly solve your organization’s challenges in an easy-to-understand way.

Let’s say your organization already has an analytics platform, but your organization’s stakeholders still don’t understand the value of it. That’s where an analytics translator can also help. An analytics translator is in a unique position where she or he can demonstrate the power of data analytics by identifying where it solves a business need. Once this individual discovers an area of opportunity, she or he works with the analytics team who then creates data models that show where the problem is and how best to resolve it. The translator might offer suggestions on adjusting the model so that it produces actionable insights that their executive team can easily interpret. Once the model is complete, this person ensures it’s the final product before delivering it over to the executive team to review.

2. Function as a Project Manager

One of the attributes an analytics translator must posses is excellent project manager skills. In the association world, this individual can operate as an “internal” project manager. She or he serves as a go-between the business leaders and the data analytics team ensuring that an analytics project is successfully executed from start to finish. This individual also can communicate the project’s progress in a digestible way to different team members at the company. If the stakeholders want changes to the project, then they work with the analytics translator who then relays those changes to the analytics team. The analytics translator helps to bridge that gap that exists between those who are a part of the data team and the executive team, so each side is better aligned with one another.

3. Assist in implementing solutions

An analytics translator serves as an advocate for adopting new solutions at your organization. One of the challenges your organization might face is some staff members hesitation in incorporating analytics into their roles. Shifting to a data-guided mindset is intimidating if your team isn’t accustomed to thinking in that manner. Also, sometimes company politics are a roadblock when attempting to implement a new tool or project across the organization. The analytics translator has the potential to champion the need to use analytics or needs to possess the grit to “fight” that battle because there will be people who are less enthusiastic to the notion.

If the resistance to adopt to new technology or start a new project exists in your organization, don’t feel as if you’re the only one experiencing that. It’s more common than you realize. That’s why it’s essential to have people such as an analytics translator to work as the driving force in implementing new solutions at your organization.

What if there’s budget constraints?

Even if an analytics translator isn’t a role you can fill at this time due to budget constraints, it’s a great position to keep in mind for the future. If hiring someone for that position isn’t possible though, then consider delegating the responsibilities to your data analytics team. It’s likely there’s someone on that team that possess some of these skills, so it’s just a matter of honing them and shifting their responsibilities around. Sometimes this is a better option because this person is already familiar with the company, processes, and data. And remember, an analytics translator doesn’t have to be a data scientist to be successful in this role.

Need help?

Contact us at info@AssociationAnalytics.com or (800) 920-9739 to explore if the Analytics Translator role is right for your association.

Resolve Power BI Column Discrepancy

During development or enhancements to a Power BI solution, you may encounter this message: “An error occurred while processing the data in the dataset. The ‘handouts_path’ column does not exist in the rowset.” You probably received this message via email if you published the dataset.
powerbi_column_discrepancy

What Column Discrepancy Means

The message means that since the dataset was published, the actual data source (SQL Server, Redshift, Excel, etc.) was changed to remove or rename the column. Now, the published data source can no longer find it.
 

How to Fix Column Discrepancy

Here are the few steps to resolve the error message:

  1. Open the PBIX file in Power BI Desktop.
  2. Locate and click the refresh icon in the toolbar, as shown below.
  3. Wait for the refresh screen to complete. This will vary in length depending on the size of the data source.
  4. Once complete, confirm the change in the fields pane to the right. Any field removed should no longer appear and any field renamed should reflect the new name.
  5. Examine existing visualizations and correct any issues resulting from the changed field.
  6. Save and publish the package choosing the replace existing option when prompted.

powerbi_column_discrepancy_refresh
Monitor your inbox to ensure the issue is resolved by the elimination of the email indicating an error in the rowset. Now you’re ready to get back to analyzing the data.

Why You Should Include Data Literacy in Onboarding

A critical part of onboarding involves introducing the culture and setting expectations. If your association strives for an analytical culture that makes data-guided decisions, you should think about how to include data literacy in your onboarding or orientation process.

Data Literacy

Data literacy is the ability to derive and communicate meaningful information from data. Data literacy is an important skill for new employees to learn to make sure they know what data is available, where they can go to get answers to their questions, and how to interpret data. These competencies are essential in a culture that values an analytical mindset.

Levels of Data Literacy

The level of data literacy required depends on the roles and responsibilities of the new employee.
If they are heavily dependent on data, like a Director of Marketing, they should be able to interpret data, analyze data using business intelligence tools, identify key data sources, and communicate the results of analysis.
To maintain and strength a data analytical mindset within your association, all employees should understand the importance of evidence-based decision making. They should also be able to interpret meaning from the organization’s dashboards, visualizations, or reports representing the association’s key metrics for success.

Incorporate Data Literacy into Onboarding

Here are a few ways you can incorporate data literacy into your onboarding process:

  • Provide new employees with an orientation to all key data systems
  • Provide a tour of dashboards and visualizations your association uses
  • Encourage usage based on staff role and responsibilities. Set expectation for usage and monitor accordingly.
  • Document analytics decisions and processes and share with new employees.

A quality onboarding experience sets the stage for new employees to be successful and productive. Studies show the importance of onboarding. Did you know that newly hired employees are 58 percent more likely to still be at the company three years later if they had completed a structured onboarding process? Make sure your new employees are data literate and ready to make data-guided decisions. They’ll be more successful and satisfied in their new jobs and that’s good for everyone.

Associations Tableau User Group Covers Best Practices in Visualizations and Advanced Analytics

The Associations Tableau User Group met in Chicago on October 13, 2016. Formed in August 2016, the Associations Tableau User Group (AssocTUG) serves as a platform for association professionals using Tableau to network and learn.  The group meets quarterly in Washington, DC and periodically in Chicago. If you missed the Chicago meeting, here’s a recap of some key takeaways.
Association Analytics® was proud to sponsor the meeting in Chicago. Association Analytics® co-founded AssocTUG and currently serves on the planning committee for AssocTUG.

Best Practices in Visualizations

Matthew Illuzzi reviewed some best practices in visualizations. Don’t just recreate a spreadsheet in Tableau. When developing a visualization consider your audience and what will resonate with them. Focus on telling a story. If you’re feeling lost, Tableau offers a ton of great educational resources.

Analytics for the 99%

Christopher Michaelson, Data Analytics Manager at the National Futures Association, shared how he introduced Tableau and data analytics to his organization. His goal was to reach “self-service nirvana” where everyone had access to data analytics and used data to make decisions.

Getting Started

To start, NFA purchased only a few Tableau Desktop licenses. They used Tableau Reader, which is free and allows users to open packaged Tableau workbooks, to give staff access to visualizations. Chris distributed packaged workbooks on SharePoint. Chris noted that managing multiple workbooks this way can be difficult to manage. He recommended considering Tableau Server licenses when managing multiple workbooks in this way is no longer a viable option. NFA publishes data sources to the server now, but eventually wants to get a data warehouse.

Designing Visualizations

Michaelson recommended focusing on creating beautiful and simple designs. Less is more in data visualizations. He also focuses heavily on usability and looks at minimizing how many clicks it takes to get an answer. He leverages Tableau strengths. Tableau is not designed to handle tabular views. Echoing Illuzzi, Michaelson warned against trying to recreate Excel in Tableau.
Most importantly, Michaelson said that information presented in data visualizations has to be timely and relevant. Does the data visualization solve a problem or create more work? Would stakeholders adopt the data visualization voluntarily? The fastest way to spark interest is to build visualizations that people will want and need.

Matt Lesnak presenting at AssocTUGAdvanced Analytics and Tableau

Did you know that you can use Tableau for advanced analytics, like propensity modeling and predictive analytics, by connecting it to the statistical computing tool R? Association Analytics® Senior Analytics Architect Matt Lesnak provided an overview for how you can connect R to Tableau to handle advanced analysis. Lesnak shared a demonstration of how he used a model created in R to populate a data visualization in Tableau that used unstructured data from social media.

Get Involved with Associations Tableau User Group

Don’t miss the next AssocTUG meeting on November 16, 2016, 1:30-4:30 p.m. at the National Council of Architectural Registration Boards (1801 K St NW, Suite 700K, Washington, DC 20006). Register and learn more.
Join the AssocTUG online community to stay up-to-date on the latest group activities and connect with other Tableau users in the association community.

How to Succeed with Data Analytics

If you’ve ever participated in a data analytics implementation, you may be familiar with the indescribable excitement around the project. Who wouldn’t be eager for a solution that makes it easier and more efficient to understand and serve your customers?
But what happens after excitement of your initial implementation fades, the consultants have gone home, and your dashboards have lost their shiny, new appeal? How can you ensure a return on your investment?
Recently, Galina Kozachenko (Association for Financial Professionals) and Debbie King (Association Analytics) discussed the afterglow of data analytics as part of the weekly Association Chat series hosted by Kiki L’Italien. You can replay the recording here. Here are my top 5 takeaways for how to succeed with data analytics:

1. Align Analytics with Association Strategy

What gets measured, gets done. “Analytics and strategy need to live side by side,” said Galina. It’s important that for every strategy, you have a hypothesis that’s tested by measuring and tracking defined metrics.

2. Manage Your Scope

Don’t start too big. “We have seen the greatest success when an association starts out by analyzing one area at a time,” said Debbie King. Prioritize your business areas and ensure successful implementation of one area before moving on to others.

3. Establish and Enforce Data Governance

Data governance is elusive, but attainable if you treat data as an enterprise asset that is the responsibility of everyone. Galina recommended evaluating your data early in any analytics engagement to better understand what elements will need to be kept clean in the future. Read more about data governance.

4. Identify a Data Champion

One of the most important factors in successful adoption of a data strategy is having one (or more) data champions. These internal staff members are able — through influence, education, or example — to advance the cause of data throughout the organization.

5. Be Prepared to Manage Change

Data analytics is an exercise in change management and that change won’t happen overnight. “It’s not a one week journey,” said Galina, “but once the traction picks up, it will be like a self-propelling train.”
To help ensure adoption, you need the support and buy-in of leadership and staff. Communication throughout the project is key. Be prepared to continuously demonstrate value through “quick wins” and sharing success stories. Your data champion or analysts also will need to commit to spending time training, providing analysis, and working with both the early adopters and the risk-averse.
Debbie recommends publicizing and promoting internal data analytics work in much the same way you would promote an external benefit to members. Pick an area and provide a weekly summary to leadership about the meaning of “story in the data”. Encourage the analytical mindset by having a “Question of the week”. Look for and show examples of surprises in the data that defy intuition. Increase visibility and stimulate interest by placing a monitor in the kitchen or lobby that shows high level visualizations that rotate each day.

failure-quoteGiving Up is the Only Sure Way to Fail

Ultimately, though, success isn’t even possible if you don’t try. “The only time you can really call an analytics initiative a failure is if you give up,” said Debbie. “It’s an iterative process and the most important thing is to get started where you are.”

3 Signs That You’re Ready for Data Analytics

I recently went onsite to a client’s headquarters to facilitate a Strategy & Discovery session – the first step in a data analytics journey. With this client and many others, I’ve noticed some common issues with their current state that prompted them to invest in data analytics. Here are three symptoms of an association that could benefit from data analytics. Anything sound familiar?

  1. Struggling to get data out of transactional systems. Once your AMS has been in use for four or more years, you’ll want to analyze all that great data being generated. Applications such as AMS, event management systems, and financial management systems are transactional systems designed to efficiently create, change, and store data. It’s not easy to get data out, though. Conversely, a centralized data warehouse uses a dimensional data model to store data in way that makes it easy to retrieve for analysis. 
  2. Time-consuming, incorrect reports. When management needs to make a decision, they rely on reports. These report are often manually created using Excel or Word and come from many different sources (e.g., your AMS, your financial software, event management, etc.). Reports prone to human errors, manipulation and can be time consuming to produce.
  3. No “single version of the truth.” When there are multiple versions of queries or reports, it becomes difficult for staff to know what to believe when trying to make decisions. Using a combination of a granular data model and data visualization navigation, you can create executive dashboards with drill-down capabilities for deeper analysis. This means that everyone from your executive team to your business staff has access to the same information and can get more details when needed. Not only can a data warehouse store information from disparate sources, it also serves as a single version of the truth.

Clients we work with may have these or other symptoms, but they all share one thing in common. They are ready to make a culture shift to seeking and yearning for data to guide decisions.

New Features in Tableau Server 9.2

Just in time for the holidays, unwrap the latest Tableau version available, 9.2, and install it for your association.  Staying current with Tableau Server is always a good idea:

  • avoid version conflicts by always matching the version of Desktop available from Tableau.
  • get the latest performance enhancements and bug fixes that are not always noted in new feature releases.
  • if you require support, you’ll always be asked to upgrade to the latest version.

The latest release also contains many new compelling features, including:

  1. Web Authoring – A powerful feature that enables licensed Tableau Server users to edit and create visualizations on the fly without a license for Desktop.  New features added here:
    • the ability to go directly to the sheet of a dashboard and manage data blends.
    • additional access to the data fields including the ability to update the data type.
    • access to formulas, including the ability to create a new one.
    • updated toolbar makes finding the mostly commonly used features easier and improves usability across screen sizes (see image below).
  2. Permissions – it’s now possible to set permissions at the project level. Previously they were inherited from Workbook and Data Source defaults. Administrators can also lock a project so authors cannot make any updates.
  3. Performance – Who doesn’t want their visualizations and dashboards to render faster?  Published workbooks take advantage of browser capabilities to display shape marks more quickly. Workbook legends are a little smarter to only redraw when visible changes are made. In addition, Tableau can cache more queries using its external query cache compression leading to leveraging a system’s RAM better.

The complete release notes and new features are here.  Schedule your install today.  If your IT vendor doesn’t directly support Tableau system updates, please contact us to discuss our Adoption Acceleration program which includes regular updates and maintenance.
tableau_server_9_2

Advancing Trust in the Charitable Sector

I recently had the opportunity to attend a fascinating international conference on building donor trust, jointly presented by the BBB Wise Giving Alliance and the International Committee of Fundraising Organizations (ICFO).
Art Taylor, President and CEO of the BBB Wise Giving Alliance, explained that the four pillars of trust include ensuring good governance, providing quality financial information, being truthful in public communication, and continuously striving to achieve results.  He stressed the impact of trust as breaches force those organizations who stand for doing things the right way have to work even harder to maintain trust.trust
People often do not conduct research prior to making charitable donations.  Each of the four organizations recently accused of fraud had detailed information available on the BBB Wise Giving Alliance website indicating that they did not meet all standards.  This is why the BBB Wise Giving Alliance seal is vital in advancing trust.
The conference included four very interesting panel sessions addressing the most challenging trust issues.
Cultural Differences that Influence Trust in Charities & Fundraising Strategies
Cultural differences exist that affect how characteristics of charitable organizations which are used as a basis for trust are perceived:

  • Public executive salary data: publishing salary data is a priority in some countries, while privacy of such data is a priority in other countries.
  • Board member compensation: board members may be expected to volunteer their time.
  • Financial statement publication: detailed consistent financial statements are considered the norm in some countries and an added burden in others.
  • Tax exemption status: the threshold involving the level of contribution to the public good and how that is defined varies.

The interpretation of data and supported conclusions can be very different when there is not a common understanding of data.  We find this same situation frequently in our work with association analytics.
Gaining Donor Trust of New Generations
The panel focused on the popular topic of millennial donation behavior, while many of the conclusions surrounded the importance of taking a broader view of customer engagement along with user segmentation.
A common characteristic of millennial donors is that they value shared experiences with friends.  To accommodate this, it is important to provide social communication tools.  A specific example is a successful campaign where a charity did not request donations directly from previous donors, but instead requested that they ask their friends to donate.
The concept of engagement is relative to individual expectation.  Millennials treat assets other than financial donations as equal, such as time and social actions.  This is reflected in time and donation patterns that are common with millennials – they take longer period of time to donate and have a larger quantity of relatively small donations.  Organizations must build trust over time and consider broader forms of engagement.  Once millennials are engaged, giving feels very natural.
Treating all donors the same is not a good idea for many reasons.  Not only is it not as effective, but one panelist described an example of a charity directing donors to a popular online platform resulting in high transaction costs for large donors who normally use other channels.
One of the most popular panelists was Josh Hoffman-Senn, the co-founder of Causemo, a startup company that provides technology to support causes through apps and websites by presenting donation opportunities within the natural flow of the user experience.  For example, a game app can offer players the option of donating to a list of charities with the BBB Wise Giving Allowance seal in order to advance to the next level of the game.
In summary, organizations need to adjust expectations concerning the size and timing of donations; place a greater value on all forms of engagement; and make a concerted effort to segment donors based on these and similar characteristics.
Communicating Charity Value and Inspiring Trust
A common theme of the panel members was the importance of articulating the impact of donations as part of all donor communication.  The panel also included the presentation of public opinion surveys that unfortunately indicate a lack of trust in charities along with high demands for accountability.
Expectations of charities by donors and the public include:

  • Serving an important need
  • Providing effective and lasting impact
  • Efficient use of funds
  • Ensuring transparency
  • Meaningful participation and feedback

Prescriptive actions that are needed in the near-term include:

  • Measuring program effectiveness
  • Timely and accurate communication to donors
  • Ensuring value to donors
  • Common standards for enforcement
  • Clear regulation and enforcement

Many of these prescriptive actions should be a natural part of any analytics strategy for associations or charitable organizations.
Donor Trust in Charity Data Security & Privacy
The same valuable data to guide decisions is also very vulnerable to misuse.  The panel stressed that most data breaches are internal and do not involve malicious intent as people often unknowingly misuse data.  This demonstrates the importance of data governance and staff education.  The discussion also addressed the differences between data privacy, which is very much policy-driven, and information security, which includes ensuring that customer data is not improperly changed.
A panelist with the Federal Trade Commission discussed legal issues and noted the key challenge of there is no single law governing privacy and data security in the United States and privacy laws are based on the residency of individuals.
Customers should ultimately be in control of their own data based on clearly communicating choices.  Bill Karazsia of the National Student Clearinghouse nicely summarized how charitable organizations should view trust and data privacy: the question they should ask themselves is “What should we do with customer data, not what can we do with customer data.”
Data analytics plays a strong role in data security and privacy:

  • Identifying sudden data changes that might indicate data governance issues such as customer service calls, customer opt-out changes, and website clickstream involving preference pages.
  • Ongoing staff training to ensure use is aligned with privacy policies.
  • Defined data cleaning and quality process to ensure changes to customer data are accurate.
  • Ensuring a common understanding of detailed customer data.

Like other initiatives, building trust requires ongoing consideration of technology and culture.  Art Taylor elegantly noted that if we understand the values, we understand many of the most important things about an organization.  He stressed that values must live and breathe throughout the enterprise, as values drive culture and culture drives what you do.
A big challenge for charities is balancing clearly beneficial investments that improve business performance with the perception of having high overhead that is commonly used as a measure of trust.  Organizations should place the same emphasis on transparency, communication, and value as direct programs to advance donor trust as such investments provide sustainable benefits throughout the organization to ensure a lasting impact of donations.

Association Analytics Adoption Advice

My Name is Change - name tag
Change is hard, and change can even be scary, but most of the time change is for the better.  This applies to business processes, your personal life, associations, and even large organizations such as Target Corporation.  The 2015 Tableau Conference website has great sessions posted, including one called “A Journey toward Self-Service BI for the Business at Target.”  Tableau was extremely well received at Target as evidenced by the 500 licenses they have in use.  In the presentation they shared some valuable tips worth highlighting because they apply equally to associations.
Tableau by itself is not a strategy
Like any new tool introduced, you can’t expect the tool itself to stand on its own and be the strategy.  More effort will be involved in addition to implementing the software, such as building skills and interest in Tableau and analytics.  Building interest will entail a culture shift as you encourage people to explore the data in ways they never previously thought possible.  As we have mentioned before, leadership support is crucial for success and that point was reiterated in this presentation several times.  Think about how impressive and productive it will be when you participate in a meeting with senior leadership and not only answer the known questions, but also easily answer new questions posed on the fly – ones that the leaders didn’t even know they had!
Don’t use Tableau the same way you use Excel
It is always comical to listen to presenters share a story about how the business staff learned the hard way that the success of using Tableau doesn’t come from recreating massive tables of numbers in chart format.  Tableau is not particularly suited for nor is it a strength to create a large table of numbers like you might in Excel.  Applying a visualization is where the success lies, because the brain can interpret an image much faster than it can analyze rows of numbers.  Plus, images portray patterns that you may miss if you just view a traditional table full of numbers.
Operational Effectiveness
This term means there is transparency and clarity into the business and it is easy to see if the business is efficient and meeting strategic objectives.  In associations, this means everyone is working from the same data and definitions for how many active and lapsed members there are, the total attendance for an event including cancellations and last minute onsite registrations, and annual budget numbers compared to actual expenses.  The information can be made available immediately to everyone.  Yes, it is likely to entail a culture shift (aka change) within the association, but it will save everyone time and enable better decision-making because the story in the data will be clear.
There is no doubt a data analytics strategy at your association which includes Tableau will require some change, but with these tips and plenty of training (Target suggests a minimum of 5 hours per person) you’ll notice widespread adoption with happier employees making better data-guided decisions.  If you don’t know where to start, pick a process which has a complicated and almost obscure set of spreadsheets for communicating numbers and turn them into data visualizations with Tableau.  Then you’ll see how fast staff will be converted to raving fans of analytics and Tableau.