Wednesday, December 23, 2015

What Hollywood Can Teach Analytics Professionals: How to Tell Stories

You might not realize it, but you probably have something in common with the creators of the TV show South Park. 

Analytics yield insights that can have powerful business impact. These insights come from statistics and data mining—processes that are inaccessible to most people. If you want your business to learn and remember, you have to tell a story.

All too often, the communication of an analytic finding reads like a police report: procedural, laden with jargon, and stripped of meaningful business context.

That’s not interesting. People won’t learn from it, and they certainly won’t change their behavior.

How then to get your point across? You need to learn how to tell stories. Data stories.

Trey Parker and Matt Stone know a thing or two about telling a story. They are the creators of South Park, a wildly successful television show which has been on the air for 19 years. Like you, their success depends on telling interesting stories.

In the video clip above, Parker and Stone are speaking to a group of students at NYU on storytelling strategies. Trey tells the students:

We can take these beats, which are basically the beats of your outline, and if the words “and then” belong between those beats, you’re f***ed. Basically. You’ve got something pretty boring.

What should happen between every beat that you’ve written down is either the word “therefore” or “but.”

Data storytellers make this mistake all the time. "We did this…then we tried that…the algorithm showed this…the correlation coefficient is that…our conclusion is...”

This kind of forensic storytelling is boring. It won’t be remembered, and the value of the insight will be lost. Save the procedural detail for an appendix somewhere. People learn from good stories, not lab reports.

As Matt says later in the clip, you need causality to have an interesting story:

But. Because. Therefore.  That gives you the causation between each beat.  And that…that’s a story.

Be sure to watch the entire clip and, if you are so inclined, take some time off for an episode or two of South Park. It just might make you a better data scientist!

The embedded video is from the NY Times ArtsBeat blog post, Hello! Matt Stone and Tray Parker Crash a Class at NYU (September 8, 2011).  Hat tip to Tony Zhou and his Video Essay on F for Fake at the marvelous blog Every Frame a Paining.

Wednesday, July 8, 2015

Create Social Documentation

Documentation is sometimes viewed as a necessary evil. But it doesn't have to be. Here's how to produce documentation that will be used.
Useful documentation gets used -- during all development phases, and by all interested parties.
Burdensome methodologies often expend precious hours producing documentation that is hard to use. Many projects leave behind fat binders of text that hardly anyone will ever open. These examples have given documentation a bad name.

The good news is that documentation can be done right. It does not have to be a drag on project time, it does not have to be a chore to read and review, and it does not have to be something we interact with alone.

Why we need documentation

Documentation is not an after-the-fact explanation of what has been built. Used properly, it is a central component of the entire lifecycle of a BI solution.

Important uses include:

  1. Prior to development: Identify and validate requirements and designs
  2. During development: Specify what to build
  3. After development: Educate business people and support personnel

Of course, there are many other areas in which documentation has value (program planning, governance, change management, etc.). These three above are sufficient to illustrate the value of social documentation.

Social Documentation

Useful documentation should be easy to read and discuss. It should also not be burdensome to produce. Three principles shape social documentation.

Social documentation is the focus of collaboration. 

Whenever possible, I recommend to my clients that we use PowerPoint for documentation. Why? Word processors are tailor made for reading, which is a solitary activity. Presentation software is tailor made for collaboration.

Social documentation is easy to navigate. 

Support "random access" rather than "sequential access." Presentation software is great for this; we can easily sort and navigate slides by their titles. This can also be achieved using document maps or outlines.

Social documentation is not prose. 

Each slide in a presentation, or section in a document, should be set up to capture essential information in a consistent format.  This format may be tabular, diagramatic, or both. Your subject matter will dictate the appropriate format.

But here is the important part:
  • No paragraphs
  • No prose
  • If using PowerPoint: No bullet lists. (They're just a back door to writing paragraphs.)

Uses for social documentation

I find the presentation format excellent for defining program priorities, defining project scope, capturing business requirements, developing top level information architectures, and a variety of other tasks. For specifications, a word processed document with multi-level headers and a document map typically fits the bill.

When documenting business metrics for a dashboard or scorecard, for example, set up a PowerPoint presentation with one slide per metric. Use a standard tabular format to document each metric. This documentation is easy to produce, review and revise, as I will discuss in a moment.

Where presentation software is not practical, word processors can be used in the same way. Divide the document into sections, activate the contents sidebar, and use a consistent tabular format.

Of course, not all documentation is captured in this manner. For example, we might use social documentation to capture a top level star schema design, then use a modeling tool to produce a detailed design.

Advantages of Social Documentation

This simple approach has numerous advantages.

Frictionless and Comprehensive

During requirements specification, social documentation allows you to capture the necessary information in frictionless and comprehensive manner. A standard tabular format, for example, ensures the same items are filled in. The presentation itself is easy to navigate via sections and slide titles.

Engages with the business

Social documentation invites collaboration. Give people a big fat binder and their eyes will cross. Show them 5 or 6 slides that capture the business metrics they care about, and they will give you feedback.

I always have my laptop with me, so if I happen to be in a room with a SME, I can pull it out, flip to the correct slide, and ask a question.

Incidentally, collaboration with the business is one of the cornerstones of the agile manifesto.

Reviewed together, rather than in isolation

Ever sent out a fat document for review? If you have, you know the results are not good. Most people will not review it by the deadline. When reminded, they will say, "it looks good." A precious few will provide detailed feedback.

Social documentation transforms this process. A review is conducted by bringing people into a room and reviewing the deck. Any agreed upon changes are made directly to the presentation slides.

The documentation is now ready for the next tasks: guiding development and then serving as the basis for education.

Learn More

Read more about documenting BI program activities in these posts:
For more details on what to document, check out my book Star Schema: The Complete Reference. Detailed descriptions and examples can be found in Chapter 18, "How To Design And Document A Dimensional Model.”

I also discuss documentation of information requirements and business metrics in the course “Business Information and Modern BI.”  Check the sidebar for current offerings.

Thursday, March 26, 2015

Join Chris in Europe: 18-22 May 2015

I will be leading a week of in-depth sessions in Berlin this May. The rigorous agenda includes full courses on Performance Management, Analytics, and Dimensional Modeling.

Join me for any or all of the following sessions:

Hope to see you there! For more details and to register, visit TDWI Europe:

Join me for the whole week, and you will have covered each of the Three Pillars of Modern BI!

Friday, March 20, 2015

BI and the Path to Business Value

Managing BI services requires a consistent information architecture, even if different teams are responsible for data marts, performance management, and analytics.

Business Value From BI

Business Intelligence is the use of information to improve business performance.[1] To improve business performance, we must do three things:

  • Track business performance
  • Analyze business performance
  • Impact business performance

Each step on the path to business value is supported by two kinds of BI services, as shown in the illustration.

  • Tracking performance requires understanding what is currently happening (Performance Management) and what has happened in the past (OLAP).
  • Analyzing performance requires the ability to get to detail (OLAP), develop insight into cause and effect (Business Analytics).
  • Impacting performance requires targeting a business metric (Performance Management) and taking a prescribed course of action (Business Analytics.)

Each of these steps leverages a pair of BI services, and each service shares a common interest in business information.[2] Managing BI services therefore requires a consistent information architecture. This is true even when separate teams manage each area.

Tracking Performance

Understanding performance often starts with summarized data on dashboards and scorecards (Performance Management). The need investigate potential problems requires detailed data and history (OLAP and Reporting.)

As Wayne Eckerson demonstrated in Performance Dashboards, both these areas provide stronger business value when they are integrated. For example, a dashboard is more useful when someone can click a metric and bring up supporting detail in an OLAP cube.

To successfully link Performance Management and OLAP, the two domains must share common definitions for business metrics (facts) and associated reference data (dimensions). Metrics must be calculate in the same way, linked to reference data and different levels of detail, and synchronized (if managed separately).

Analyzing Performance

Analyzing performance is the process of breaking down what has occurred in an attempt to understand it better. Slicing and dicing an OLAP cube is a form of analysis, providing insight through detail. Analytic models provide a deeper level of analysis, providing insight into cause and effect, and extending this to the future through prediction.

OLAP is largely focused on exploring various aggregations of business metrics, while analytics is largely focused on the underlying detail that surrounds them. Our OLAP solutions provide historic detail to Business Analytics in the form of data from the data warehouse.[3]

The exchange flows the opposite direction as well. Business analytics develop insights that suggest other things that should be tracked by OLAP services. For example, a particular set of behaviors may define a high value customer. This assessment is developed using Business Analytics, and applied to the customers in the OLAP data mart. For a fun example from the world of sports, check out the book Moneyballby Michael Lewis.[4]

Improving Performance

All of this is somewhat academic if people in the business do not use all this information to make decisions. Business impact occurs at the intersection of Performance Management (which tells us what is important and how we are doing) and Analytics (which suggests the best course of action.)

Every analytic model targets a business metric or key performance indicator (KPI) from the world of performance management. That same KPI, in turn, can be used to measure return on investment of the analytic model.

For example, a direct sales manager of enterprise software wants to reduce cost of sales. An analytic model is developed that assesses the likelihood of a prospect to buy enterprise software.

The manager begins using the prospect assessment model to prioritize the work of the sales team. Less likely prospects are reassigned to a telesales force. Over the next two quarters, cost of sales starts falling. The same KPI that the analytic model targeted is used to measure its return on investment.

Information as an Asset

It is common to manage each of the pillars of Modern BI as a separate program. The path to business value, however, requires that these programs share a consistent view of business information. BI programs that are not centralized must carefully coordinate around a common information architecture.

Further Reading

  1. For more on this definition of business intelligence, see Business Intelligence in the Modern Era (9/8/2014)
  2. The three service areas are explained in The Three Pillars of Modern BI (2/9/2015).
  3. Sometimes analytic modelers bypass the data warehouse, but there are steps you can take to make this important repository more useful. For tips on how to make your data warehouse more useful to analytic modelers, see Optimizing Warehouse Data for Business Analytics (9/25/13). Note that even with a well designed data warehouse, analytic models often augment this enterprise data with additional data sources.
  4. The Oakland A's used analytics to re-evaluate the basic metrics used to assess the value of a baseball player. See Business Analytics and Dimensional Data (7/17/13).
** Interested in learning more about modern BI programs?  **

Check out my new course, Business Information and Modern BI: Evolving Beyond the Dimensional Data Mart.  Offered at TDWI conferences and onsite.  See the sidebar for upcoming dates.

Wednesday, March 11, 2015

Modern BI with Chris Adamson: Chicago, May 7

Join me at TDWI Chicago 2015 for my latest course, Business Information and Modern BI: Evolving Beyond the Dimensional Data Mart.

In this full-day class, I will show you how a modern BI program can help you track, analyze and improve business performance.

With a strong focus on information, we will look at how new technologies and best practices have reshaped the way BI delivers business value.

We will cover all three pillars of Modern BI, and also discuss organizational options, agile development and technology policies.

I'll also be leading classes on Predictive Analytics (5/5/15) and Data Visualization (5/6/15).

Discount Code for Registration

If you are planning to attend, use this link to register, and enter Priority Code 111 for a 10% discount.

Hope to see you there!

Monday, February 9, 2015

The Three Pillars of Modern BI

Data marts are no longer sufficient to meet the demands of a modern BI program. This post lays out a framework for delivering BI value in the modern era.

The technologies and processes that help us deliver BI services have advanced by leaps and bounds over the last two decades. A modern BI program provides three perspectives on business performance, roughly corresponding to the past, present, and future.

OLAP and Reporting

OLAP and reporting services (or simply "OLAP") provide the "official record" of what has happened in the past--the canonical log of business activity.

This pillar of the modern BI program helps the business understand "where we've been." The typical information products provided in this service area include:

  • Reports provide pre-built, parameterized access to business information
  • Analysis provides the ability to explore the official record of business activity by slicing, dicing, drilling, and so forth (OLAP)
  • Ad hoc query capabilities allow people to ask their own questions about the official record, even if a pre-defined report or analysis does not exist.

For people in the business, these kinds of information products come to define this pillar of the BI program. There is also a fourth important information product of which the business may have less direct awareness:

  • The integrated record of business activities, aka "Data Marts." This record combines, standardizes and organizes information for business consumption.

Essential in delivering the first three kinds of information products, this component was the primary focus in the early years of BI, when we called the practice "data warehousing." Since then, the discipline has changed and expanded. But it is still essential that the BI program provide the ability to understand the past.

Performance management

Performance management services provide real-time status on key performance indicators, as well as performance versus goals.

KPI's and goals are carefully matched to the viewer's role and linked to business objectives. Goals communicate expectations, while KPI's communicate achievement of expectations.

If OLAP is about "where we have been," then performance management is about "where we are now." Typical information products in this BI service area include:

  • Dashboards provide real-time or near-real-time status of KPI's
  • Scorecards which communicate progress vs. goals

Information on dashboards and scorecards is carefully tailored for the user or functional area. Metrics are chosen for relevance and actionability, linked to business strategy, and balanced to reflect a holistic picture of performance.

While this service area can stand on its own, performance management solutions are more powerful when people can dig into the KPI's on their dashboards. This capability is enabled by integrating performance management services with OLAP services.

Business analytics

Analytic services probe deeply into data, providing insight into cause and effect, making predictions about what will happen in the future, and prescribing a course of action.

While analytic services draw on data from the past, their objective is to influence the future. Typical information products in this service area include:

  • Analytic models that make sense of activities or predict future events
  • Simulations that allow the manipulation of variables to study their potential impact on results
  • Visualizations that communicate analytic insights
  • Analytic metrics that assess current state and or future outcomes which are fed to OLAP, performance management, and OLTP applications

Like the other pillars of modern BI, analytic services can exist alone but are more powerful in the presence of the other pillars. Prescriptive metrics, for example, are best presented directly on operational dashboards; useful analytic metrics can be recorded and tracked over time in data marts.

Delivering Modern BI

In each area of the business, these capabilities should be balanced and tied together. Centralized management of all three pillars is not required, but they should be coordinated and integrated. A shared roadmap should lay out their planned evolution.

Your objective is business impact, and my next post shows how these services deliver it.

Learn More

For more on managing the Modern BI program, check out Chris's latest course: Business Information and Modern BI. Check the sidebar for upcoming dates.