The Association of Arts Management,

Marketing and Development Professionals

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Data Analytics

By Neil FitzGerald, President, PriceWhispers

In a recent client consultation, I was asked whether I thought data an-alytics had reached their zenith of

applicability in arts and entertainment, specifically in regards to the maturity of analytical tools and the questions that could be answered.

This query was posed by a progressive and for-ward-thinking arts organization and was primarily motivated by their indecision on how (or if) to move forward with additional investment in data analyt-ics. Working as part of a group with over 25 years in the data and analytics domain across multiple industries using data in sophisticated analyses, I knew the answer was a definitive “No,” but this led to an interesting conversation – first on a review of the analytics domain today across other industries, and then towards the beginnings of a framework to self-assess on data analytics readiness and oppor-tunities. Here is a template of that framework for you to use in your organization to determine where you are today on the analytical spectrum and what opportunities might be around the corner for you.

The Analytical SpectrumThe pyramid in the diagram at right highlights

the varied levels of capabilities available. As you move up, the more sophisticated the potential anal-ysis...and the potential rewards in facilitating better decision making. Unfortunately, moving up also increases the required sophistication of the tools and analysts.

Every organization, including our clients and your organization too, is already on this analysis spectrum. Using reports or excel worksheets created internally or provided by your ticketing or CRM system (e.g. to determine where to send a promo-tion email) fits in the lower levels of the pyramid. Creating custom metrics or visualizations for an executive dashboard (e.g., revenue per available seat or genre penetration rates by geographic area) that incorporates data from internal databases moves you up the pyramid. Using advanced statistical and/or algorithms to model your organization and its customers places you near the top.

Opportunity KnocksAt each level of the pyramid, there are usually a

myriad of unmet challenges that can be addressed by tools and capable analysts (e.g., customer segmenta-tion, forecasting, demand-based pricing, sales pace curves and heat maps, probability to buy, customer loyalty scores, promotion analysis, etc.). In addition (and an important element in the discussion with my progressive client noted above), there are also ongoing opportunities provided by utilizing an iter-ative process of analysis and striving for integrated analysis and continuous improvement.

Implementing a cycle of constant improvement enables organizations to use completed analyses and proven metrics as inputs or a foundation into future analysis. As an example, think about an organization that has completed a set of advanced Probability to Buy (PTB) metrics for their customer base. While powerful by itself for facilitating segmented market

promotions, imagine the benefits that this organiza-tion can realize by combining the PTB metrics with their performance forecasting and sales pace analyt-ics. They can quickly identify shows and sections that are under- or over-performing expectations and create a targeted promotion list by marrying that data with the individual customer PTB metrics — i.e., don’t make discount offers to customers who have a high PTB and have not yet purchased.

Organizational ReadinessWhile organizations are likely unanimous in their

interest to take advantage of the benefits provided by leveraging more (and better) analytics, the unfortu-nate reality is that not everyone has the bandwidth

Data Analytics Are Here to Stay — Long Live Data Analytics!

The Data Analytics Spectrum: Where You Are and Where to Go From Here

Advanced Analytics

Self-Service Analytics & Visualization

Guided Analytics & Reporting

Canned Reporting & Excel Imports

Web Dashboards Data-driven Decisions

The Analytical Spectrum

“Implementing a cycle of constant

improvement enables

organizations to use completed analyses and

proven metrics as inputs or a

foundation into future analysis.”

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Data AnalyticsContinued from page 3

or familiarity with the methods and tools to be able to step back and assess the entire data landscape (or data-health) of their organization. The chart below provides an outline of the three core areas that contribute to better data-driven decision making in every organization.

To facilitate an internal assessment of your orga-nizational readiness, an executive team can begin by reviewing the three primary elements outlined in this framework – Technology, Data and People. By candidly self-assessing in each of these key areas, a group can determine where internal gaps exist, where opportunity presents itself in the short-term and understand paths for moving forward to take advantage of the lowest hanging fruit.TECHNOLOGY

With the pace of technology advances today, this is an area that can feel overwhelming to organiza-tions very quickly. The figure below provides a guide to the primary toolsets available to arts organizations for investigating and extracting value from their data.

As you move up the technology stack depicted above, the potential benefits to your organization (along with their potential cost) increase. The more specialized tools enable more advanced types of

analyses and the consolidation of analyses across multiple data sources.

To help you assess where your organization is today and the possible paths forward, you should carefully consider two elements of your technology infrastructure – Tools Availability, i.e., what tools you have access to from the above diagram, and Infrastructure Scalability, i.e., is your organization equipped to grow its IT infrastructure to accommo-date more advanced analytics.Data

Data-driven Decision Making

The three core areas that contribute to better data-driven decision making

People Technology

The primary toolsets for investigating and extracting value from data:

Advanced Analytics

R, SPSS, SAS - statistical packages

Predictive/ modeling

Business Intelligence

SAP, IBM, Tableau, QlikView, etc.

Dashboards & interactive reports

Advanced visualizations

Web & Social Media Analytics

Google and other Web analytics

Facebook & Twitter analytics

Excel/ Spreadsheets

Exports from functional systems Pivot tables Basic charts

System Reports Single source reporting

Integrated reporting

HIGH

Invest in Analysis

• IT infrastrucure & staff in place.

• Need to purchase tools or analytics expertise.

Grow Analytics

• Available analytics tools & scalable IT infrastructure means you’re ready to scale your anal-ysis with or without third-party support.

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SCAL

ABIL

ITY—

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—>

In the Clouds

• Can gain scalability & analytic capabil-ity via outsourcing to third-party ex-perts in the Cloud.

• Need internal infrastructure expansion or cloud infrastructure.

IT Catch-Up

• IT infrastrucure investment must be upgraded to match requirements of analytic tools.

• Outsourcing option for IT infrastructure.

LOW <———TOOL AVAILABILITY——> HIGH

The quadrant map above enables you to identify where your organization sits today in regards to analytics technology and supporting infrastructure. Based on your organization’s quadrant, the diagram suggests what your analytics next steps are. DATA

Even with all the analytic tools in the world and an infinitely scalable IT infrastructure, the results of any data analysis will be lacking and unimpressive without consistent and consolidated data. You can think of the analytic technology discussed above as the sports car of data analytics, and the actual data as the fuel. If the fuel is contaminated or of poor quality, the sports car’s performance will stutter or stall. Here are a few initial questions to consider regarding the state of your data:

3 Do you have a centralized source of data? Think of a single database where you can ask ques-tions about ticket sales, donations, marketing initiatives, budgets, customer demographics, geographic information, psychographic data, weather information, web activity, social media activity, etc.

TECHNOLOGY

The Association of Arts Management,

Marketing and Development Professionals

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“A well-crafted data analytics project should be expected to

provide a return of 10-25 times

the original investment…”

3 Do you have a separate data analytics group, i.e., outside of specific functional areas or software systems?

3 Do you have access to generalized analytic or business intelligence tools, i.e., tools not attached to a given system such as Google Analytics or ticketing system reports?Based on our experience, the majority of or-

ganizations in arts and entertainment will answer the above questions with a resounding “No.” This is simply a reflection of the state of maturity for analysis in arts and neither a good or bad thing. These are considered best practices however, and are commonly implemented across other industries. The good news for arts and entertainment organi-zations is that there are templates for best practices to create a robust data environment. By leveraging these, the arts domain can avoid repeating mistakes from other industries. The other piece of good news is that many of the systems that you already use do provide solid datasets for their specific domain (e.g., ticket systems, web and social media activity) and analytic value can be derived from each of these datasets as you work through a consolidation effort and aspire to advanced analytics across the datasets. PEOPLE

Extending our previous sports car analogy, as the data fuels the technology sports car, it’s definitively and always the people in an organization that drive the car to make improved data-driven decisions. Without a capable driver, the performance of a sports car will be unpredictable at best and in many cases, very dangerous.

To help you assess where your organization is today and the possible paths forward regarding your Human Resources (HR), carefully consider two ele-ments – Resource Availability, i.e., do analysts have available bandwidth/time, and Resource Capability, i.e., do you have analysts on staff with the skills to conduct the varied types of analytics.

The quadrant map below enables you to identify where your organization sits today in regards to analytics skills and availability. Based on your or-ganization’s quadrant, this visual suggests potential next steps for accelerating your focus on analytics in the short-term. This quadrant can be applied both holistically on your data analytics environment and also on a specific analytic challenge, i.e., an internal analyst or hired consultant may not have capability across all advanced analytic problems and methods.SUMMARY

As my originally referenced client came to agree, the analytics domain in arts and entertain-ment (and other in-dustries) is still ripe with opportunity. The key to success is to critically self-assess, identify gaps, acquire the required resources and skills, technology and data to fill the organizational gaps, target an analytic objective with a big-bang return in investment and execute towards your objective(s). A well-crafted data analytics project should be expected to provide a return of 10-25 times the original investment, so following the keys to success can be both pro-fessionally and organizationally rewarding. An Analytics Scorecard is a great way to measure this return on analytics investment and your project success. These dashboards can often be created using the same analytic tools being used for your analysis and business intelligence, but that’s a topic for exploration on another day. Neil FitzGerald is the Founder and President of Price-Whispers. Prior to founding the company in 2010, he worked in the Business Intelligence (BI), Reporting and Analytics space for 15+ years and founded an award-winning, global IT and BI outsourcing company with offices in the United States, Canada and China. Neil actively works across industry verticals in the application and development of innovative pricing, reporting and analytic strategies to help optimize revenue and increase opera-tional excellence. Neil is a published author in the analytics and reporting domain having sold over 50,000 copies around the world in multiple languag-es. He can be reached at nfitzgerald@pricewhispers.com

HIGHSkills Gaps to Fill

• Train staff.

• Complement team with data analytics expertise with focus on initial sup-port & subsequent knowledge transfer.

Analyze This! Ready to Go!

• Analyze, Assess, Take Action, Review, Repeat.

• Focus on moving up the data analyt-ics pyramid and exploring new data challenges.

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AVAI

LABI

LITY

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Opportunity Knocks

• Expand team inter-nally, or

• Expand team with external data ana-lytics expertise.

• Identify initial project.

Prioritization Opportunity

• Free your analysts’ time for high-value analysis work.

• Outsource or elim-inate lower-value activities.

LOW <——RESOURCE CAPABILITY—> HIGH

HUMAN RESOURCES