Using Data to Tell a Story

Bobblehead DollIn a conversation, it was discovered that a vital aspect of communication was missing. Data has a story to tell, but many never know the story or have never figured out how to tell the story properly.  Either way, the reports containing data fail to capture the audience’s attention, lose the audience, or fail, thus making the process of collecting, analyzing, and using the data useless!  Hence my aim here is to aid you in improving your storytelling power and, by doing so, increase the credibility and usefulness of your data to convince your audience.

We must bow to a truth; data does nothing, proves nothing, and cannot convince anyone.  All data can do is support a proposed course of action.  Hence, the data is reliant upon the story, and the story is reliant upon the data.  This principle cannot be stressed enough or more emphatically.  Let me illustrate.

Here is some data:

5184 0.83 4 5123 5 0 3 95 80 242 0
183 4 483 2.9 1 3666 1 17 1 2 0
2 0 705 15.32 2 11458 0 0 0 5054 760
35 1 493 28.8 4 10258 1 0 33 970 390
17 1 33 15.15 2 18811 3 0 40 32 5
2741 8 838 11.81 1 35843 15 298 64 239 104
0 0 1438 4.59 0 1582 0 0 0 22 1
1827 1 1011 18.5 0 40208 0 645 800 418 308
0 0 28 3.57 0 732 0 0 18 69 7

Use storytelling to present with power | Presentation GuruEven with column and row headers, this data is useless.  It is trying to tell a story, it is reporting symbols correctly, and the data is an accurate indication of work occurring; but, where is the value of the data?  What can you surmise from this information?  What trends are happening?  Are the trends good or ill?  What good will having this data do for you without an explanation about each row, each column, and a basic understanding of how each data point was collated?  How is the data read, right to left, top to bottom, left to right, bottom to top, or some other way?  You have all the data you need in this table to make several decisions, plotting multiple courses of action, but how do you know what to do?

Hence the truth; data does nothing, proves nothing, and cannot convince anyone.  All data can do is support a proposed course of action. Therefore, the data is reliant upon the story, and the story is reliant upon the data.  This principle cannot be stressed enough or more emphatically.  When in doubt, always return to this truth about data.  If the data is incoherent, sometimes the story can make up the slack and convince.  If the story is confusing, the data cannot take up the slack.  Worse, if the data and the story are incoherent, time and resources were wasted.

Storytelling Stock Photography Clip Art - Children Telling Stories , Free Transparent Clipart ...I mentioned storytelling with data, and the person I was talking to seemed perplexed.  No, the story does not begin, “Once upon a time, in a far off land, there lived….”  Nor should the story begin, “Column A is aggregate data pulled from …”  What we are discussing is finding a medium between these two extremes where the data’s story can begin, without compromising the veracity, but still keeping the audience’s attention.  Believe it or not, storytelling begins with planning, and planning starts with selecting the audience.

Planning: Selecting the Audience

The first question every writer must address is, “Who is your primary audience?”  For children’s books, the answer is simple, choose an age group of children, and voila, you have a primary audience.  For adults, the decision tree is a little more complicated.  For example, is your primary audience expert-level professionals, graduate students, baccalaureate students, high school graduates, or seasoned professionals without a degree?  Is the primary audience vendors, stakeholders, employees, engineers, a mix of all, none of the above, politicians, lawyers, judges, doctors, etc.?  Until you know the audience, you will not know how to address the audience, what language to use, the grammar, the syntax, and the vocabulary.  All of which require planning to capture the audience’s attention and tell the story successfully.Non Sequitur - Plasticity of Language

I choose to write for general audiences, using plain language principles, for my intended audience are experienced professionals, adults, and general people.  I make this choice not for ease of writing but for the enjoyment of communicating.  In this blog writing forum, it is better to be plain and speak simply than trying and peg a specific audience.  I presume you already know many principles, and my job is to flush those principles into current memory and help build on what you know.  I also suspect you know how to use a search engine to gain additional information if you so desire.Five tips for effective data storytelling

Hence, making choices about your primary audience is critical to how you address your audience.  When using data to convince the audience to take action, you will also need to plan how and when to use the data.  But, before you use the data, you must tell the audience how the data was gathered, how it was analyzed, and why these are important to know.

Planning: Data – Gathering, Analyzing, Presenting

Consider the table above; without dollar signs, how can you tell which fields represent dollars?  Without percentages, how many fields represent a percentage?  The presentation might not be everything in data storytelling, but it is definitely a significant part of the task.  Hence, there should be a plan to present the data long before the first pieces of data are gathered or analyzed. Primarily if the data consists mainly of numbers, for numbers are merely symbols and can mean anything!

WHY STORYTELLING IS THE NEW HOT BUZZWORD! - Advanced Marketing StrategiesGathering data is all about relating how the numbers originated.  Not created, originated; creation implies the numbers were made up; origin implies the numbers existed and were discovered.  Choose your descriptive words carefully in storytelling, especially where numbers originate.  Each number is a symbol representing something; hence, each number requires an explanation of its origin story and value to the results.  Never forget, if you have 100 number columns and 200 rows, you will need at a minimum 100 explanations and origin stories.

Analyzation, what tools helped you crunch the numbers?  Any regression, statistical analysis, any bell curves, remember, each instrument used will need an origin story and purpose for use.  Each tool will have a preferred method for presentation, does the presentation clash with other numbers being represented?  Are tables too complex due to the number symbols and presentation demands?  When writing the origin story, the clarity in telling the story is discovered in the origin stories, so make sure you understand how the data is to be presented.

Planning: Presentation

Business storytellingHow will the final report be given, PowerPoint, Prezi, Adobe PDF, MS Word, Email, Conference Room deliverable, Web Chat, etc.?  The presentation of the final product dictates what goes into the story, how graphs and charts are used, the language employed, body language in presenting the data, and a host of other decisions.  Yet, too often, this planning step is neglected to the end of the process.  Then massive changes have to be made to the product on the fly, creating confusion, wasting resources, and creating stress and problems unnecessarily.  Before the story’s first words are told, decide how the final product will be presented, right alongside the primary audience, and how the product will be delivered, it will save time and resources!

Convince – Don’t ProveMediocrity Joke

You intend to convince an audience that the proposed course of action is the best course of action.  Data can never prove anything!  The story must convince a course of action, and a decision tree is appropriate; thus, the storyteller must tell the audience why!  Why is this course of action the best?  Why is another method of effort not to be considered?  Why should other courses of action not be undertaken or explored?  Why?  Why?  Why?  When in doubt, circle back to the unalterable truth discussed in the beginning, data does nothing, proves nothing, and by itself cannot convince anyone of anything.

Convincing the audience is the storyteller’s job.  The data is there to assist, provided it has been properly introduced, correctly presented, and described with aplomb.  Then, the data can be an effective tool to carry the day and aid in convincing decision-makers (people) that a course of action is correct.  Failure of the story, failure to explain the data, and your efforts are wasted and the proposed course of action not taken seriously.

Knowledge Check!Please note, these are the basics of using data to tell a story.  Experience and time are harsh taskmasters, and they will teach advanced courses in using data to tell a story.  However, understanding these basics will keep you from learning through failure while being taught the advanced skills in storytelling using data.  One final aspect of planning involves language, especially grammar and the technical aspects of writing.  If you do not know the language, find a native speaker to review the presentation before publication and delivery.  Get to know tools available to aid in proper spelling, grammar, and punctuation.  Your diligence in learning technical skills in communicating will pay dividends for good or ill.  Invest wisely!

© 2021 M. Dave Salisbury
All Rights Reserved
The images used herein were obtained in the public domain; this author holds no copyright to the images displayed.

When Fiction is Reality – The World Weeps!

Exclamation MarkI find a piece of fiction masquerading as science from today’s email, and I cannot help but ask myself, when did fiction become a reality?  How did Orwell’s 1984 escape the pages and become a reality?  Why did Animal House exit the big screen and become a way of life?  Mark Twain is one of the most often quoted authors, and I particularly like his comments on statistics which is pertinent to today’s discussion on fiction.

“There are lies, damned lies, and statistics.”

Consider something with me; even if you initially disagree, please humor me.  Statistics prove nothing; the best a statistical analysis can ever do is represent a bias towards a specific course of action.  That is it!  Mark Twain’s quote describes the persuasive power of numbers, particularly the use of statistics to bolster weak arguments. Mark Twain’s point is used to doubt statistics to prove an opponent’s point.  Inherent in every statistical analysis are the researcher’s biases, the desire of the researcher to attempt to verify something via numbers that are generally unable to be proved otherwise.Anton Ego

Except research proves nothing; even peer-reviewed research, the gold standard in research, can only point a person towards a potential solution and encourage a person towards a course of action.  The numbers prove nothing, ever!  Many people have become convinced that statistical data is comparable to “Holy Writ,” which is erroneous and dangerous.  Let me prove it to you, please.

Project Implicit

Project implicit was designed by Harvard University, is hosted on Harvard’s servers, and is all about individual bias.  Implicit bias in statistics is described as bias that occurs automatically and unintentionally, that nevertheless affects judgments, decisions, and behaviors.  Bog-standard bias is considered attitudes, behaviors, and actions that are prejudiced in favor or opposition to a person, group, or thing.  But, here is the clincher, bias is judged by others as a projection of themselves when they encounter other people, places, or things.

Broccoli PNGFor example, President Bush I, did not like broccoli.  A prejudice, possibly from childhood, he does not like this vegetable and handled the situation poorly at a state dinner in Japan.  Not liking broccoli is a bog-standard bias.  Other people, especially those enjoying broccoli, will view this event and shake their heads, possibly even ridiculing the president for his disinterest in broccoli.  Others who agree that broccoli is nasty will not have a problem with the presidential bias against broccoli as they exercise the same intolerance.  Thus, a bias is a behavior, an attitude, and supporting actions against something, someone, or someplace, even if that bias is understood or not.

Implicit bias takes normal bias one step further, according to psychiatrists and psychologists.  The extra step includes the inability to explain why a person does not like broccoli.  If there is no hidden reasoning from childhood, traumatic experiences, or irrational fears, then bog-standard bias is considered implicit bias, as judged by the person observing the behaviors.  Are the differences apparent; the reason I ask this is because of the problem in naming biases, the individual doing the observing and judging.Implicit Bias Test

In a branch of science called “Chaos Theory,” there is a hypothesis “that people affect their environments to their own desires.”  The premise was accidentally discovered when humans observed particles under close study and observed under remote means, and the particles acted differently.  The human influence upon particles was a giant leap forward in science, and nowhere is the power of researchers more fully understood than in human sciences (psychology, psychiatry, etc.).  The human brain is wired to connect socially, which is part of the problem when humans are studied under observation.  The innate desire to connect means that people will choose differently when under direct observation, when under remote observation, and when under no observation.

Hence bias is a judgment of another as witnessed through a lens of another person’s understanding, opinions, biases, and experiences.  Researcher bias is a fact inescapable and remains a topic of discussion in every research paper as a contributing factor to the results.  Why; because the researcher’s influenced the results, influenced the data, and influenced the process to achieve their own desires for an outcome. QED: Thoughts become things.Thoughts Become Things | the quotes

Returning to Project Implicit, ask yourself, why would you allow someone else to judge you?  Do you know them?  Do they know you?  Do you fully appreciate that the other person and yourself will influence the results?

Project implicit claims to measure, using mathematical formula the bias of another person, using time and word lists.  Using this formula (v1-v2=BIAS), Project Implicit proclaims they can help you recognize implicit bias on a range of topics from racism to gender roles and from veggies to pets, all because the mathematics claim they are conducting science.  Except, the implicit association is rigged to produce the desired results, as discussed above; hence, where is the veracity?The problems with implicit bias training | The Spectator | Truth Conquers All

GIGO

Garbage in equals garbage out (GIGO) is an axiom that initially began in computer programming and signified that when you dump a bunch of garbage into a system, the results are garbage.  The same is true for every single human endeavor; when you begin with garbage, the best you get for a result is more garbage.  Returning to implicit associations as an indicator of implicit biases, ask yourself, who selected the terms associated with the topic under study, the researcher or the researchee?

Of course, the researcher selected the terms, chose the topic, and tested how fast you can associate a word with the topic under study.  Then comparing the two results declares you have a bias.  Except, do you have a bias; I do not think so!  But, that’s my bias, for I choose to believe that you know how to choose and act in social environments to your potential and desired outcomes.[الإنحياز الضمني] مكتبات التصنيف الجاهزة في العقل البشري | محمد بن نخيلان الشمري

An Example

I was ordered to take an implicit association test to measure my emotional intelligence in a previous position.  The test used word associations on the topic of gender roles and leadership.  Believe it or not, I failed that association test; I do not place genders into any roles as traditional or limited to one gender or the other.  The best leaders are good followers; leaders are not born, they are made; gender, like race, never plays a role in the leadership potential of the person in charge.  Yet, when I failed the association test, my organization was informed I was obstinate, difficult, and opinionated; not that I deny these accusations, I simply refuse to fit into a pre-determined box.  Plus, I would see more people escape the box that has been built for them to “fit” into!https://c1.staticflickr.com/9/8368/8537356422_23bf051215_b.jpg

Later that same week, I snuck into the association exam a second and third time, mainly because the researchers kept sending active links that did not discriminate against logins that had previously taken their test.  Yes, I intentionally poked holes into these researcher’s pet project, and I will explain in a minute why.  On my second attempt, I chose what the results considered a “traditional male” with a bias against women.  In the third attempt, I decided to be a woman with a grudge against men and their traditional roles.  I wanted to show how irrelevant these word association tests are and how the results should never be taken seriously.

My plan backfired; my employer was not happy.  The researchers had to scrap their entire data set and go back to the drawing board to fix the research plan, and then after regaining approval, collect human testing data a second time.  Lots of prestige was lost for my employer.  I did not care then; I care less even now; even though I eventually left that position with people angry with me, I do not regret my actions.  Thankfully, I was not the only person offended by the word associations and the results which “snuck back” to play!Mediocrity Joke

Why is this important?

The answer to why these topics are important is found in the principles outlined:

  1. Statistics prove nothing!
  2. Statistics can only support a course of action!
  3. Research can only support a decision!
  4. Research cannot prove anything!
  5. Faux science abounds, and until researchers and academia acknowledge this problem, it will only grow.
  6. Never believe what you read, see, or hear!
  7. Faux science is being used to classify, separate, denigrate, and deride!
  8. Faux science is the excuse for stealing your liberty, freedoms, and legal rights under the US Constitution!
  9. Faux science crops up in courtrooms which is a cause for bad case law, which develops into detestable legislation!
  10. Faux science looks, sounds, and appears legitimate until you dig deeper. If you do not dig, you will be misled!

Bobblehead DollI cannot stress enough the need for every person to stop accepting the box others claim you must live in to “get along and get ahead.”  You are an individual with inalienable rights, a brilliant mind, and unlimited potential.  You are needed on the front lines of the battlefields of today.  You must play an active role, or you will not be able to leave the American Heritage and this great Republic to your children and community.

But, like the “Reading Rainbow” used to proclaim, “Don’t take my word for it!”  Meaning explore, doubt, ask questions, and keep asking questions until you are satisfied the answers are truthful, without dissemination.  Liars will tell you a thousand truths to get you to believe a single lie.  But, do not take my word for it; prove it to yourself; then teach it to another person so that you can learn more perfectly.Reading Rainbow

© 2021 M. Dave Salisbury
All Rights Reserved
The images used herein were obtained in the public domain; this author holds no copyright to the images displayed.