Using charts to misinform and fool people

➡️ 𝕌𝕤𝕚𝕟𝕘 𝕔𝕙𝕒𝕣𝕥𝕤 𝕥𝕠 𝕞𝕚𝕤𝕝𝕖𝕒𝕕 𝕒𝕟𝕕 𝕗𝕠𝕠𝕝 𝕡𝕖𝕠𝕡𝕝𝕖 — Most of us struggle with making sense of numbers and data. Charts are the most common method of making numerical data understandable. Like all tools, they can be used for education just as well as for misinformation. Here’s a common example of how bar graphs can manipulate the viewer’s judgment.

Key words: charts, statistics, misinformation, data

🆀🆄🅾🆃🅴🆂
💬 “He uses statistics as a drunken man uses lamp-posts… for support rather than illumination.” — Andrew Lang
💬 “Facts are stubborn things, but statistics are pliable.” — Mark Twain, who also said, “There are three kinds of lies: lies, damn lies and statistics” — which he in turn attributed to Benjamin Disraeli, the British politician.
💬 “Sanity is not statistical.” — George Orwell (1984)
💬 “Miracles are statistical improbabilities. And fate is an illusion humanity uses to comfort itself in the dark. There are no absolutes in life, save death.” — Amie Kaufman

The ideal number for a meeting is …

Key words: brainstorming creativity productivity strategy meetings number


ABOUT THIS SERIES OF CARDS: “Men follow their sentiments and their self-interest, but it pleases them to imagine that they follow reason. And so they look for, and always find, some theory which, a posteriori, makes their actions appear to be logical.” — Vilfredo Pareto

Confirmation bias

Key words: bias, confirmation bias, cognition, tunnel vision, echo chamber


ABOUT THIS SERIES OF CARDS: “Men follow their sentiments and their self-interest, but it pleases them to imagine that they follow reason. And so they look for, and always find, some theory which, a posteriori, makes their actions appear to be logical.” — Vilfredo Pareto

Parkinson’s Law of Triviality

Key words: Parkinson triviality law meetings time 


ABOUT THIS SERIES OF CARDS: “Men follow their sentiments and their self-interest, but it pleases them to imagine that they follow reason. And so they look for, and always find, some theory which, a posteriori, makes their actions appear to be logical.” — Vilfredo Pareto

A Walk Through the Brave New World of Healthcare Data Analytics

With a stethoscope around the neck, a good flashlight, thermometer and genuine empathy for patients, you were all set to go as a doctor, just a few decades ago. The need for empathy remains, but the world of healthcare delivery has changed hugely since then.

Fast forward to today. Sci-tech has given us tools of remarkable capability. There is no corner of the human body, however small or remote, that cannot be imaged, measured, probed and altered in some fashion. We are armed today with devices that can even work upon the very stuff of life and creation: DNA. The words of the science fiction writer, Arthur C Clarke, come to mind: “Any sufficiently advanced technology is indistinguishable from magic.” What modern Medicine can deliver today is undoubtedly magical.

From Pieces, Into Bits — the Digital Transformation

In keeping with all other areas of human activity, the years have seen a shift in medical technology from analogue to digital. As an example, imaging studies are almost all captured in digital form. The old x-ray film is now obsolete. This change is convenient; reporting, viewing, archiving, transferring and analysing are all made much simpler with digital systems rather than physical.

The Data Tsunami

The power comes with a price. The data that pours in from any given patient is vast. Everyone dealing with healthcare delivery — users, caregivers, administrators or third-party payers — struggles with the effort of staying afloat in this deluge. Making sense of all this information is a task that can exceed the cognitive abilities of the smartest. It’s now an uphill task to stay up-to-date even in narrow specialities.

Looking at just one speciality, oncology (2005 – 2015):

  • 140 million patient encounters,
  • Generating 0.1 – 10 GB of data per patient (14 – 1400 TB overall)
  • 80% of which is unstructured.

An average hospital generates 665 TB of data, yearly. The quantity is doubling every two years.

A Triple Whammy

Three properties characterise the data deluge.

  1. Volume — as exemplified earlier.
  2. Velocity — the rate of accrual and change is estimated at 20 – 40% per year, meaning that the size of the data store doubles every other year.
  3. Variability — Captured data is stored in silos that can be difficult to penetrate. A large part of the problem is the lack of unified data storage structures and inter-operability. On top of all this, a substantial portion of the data resides as unstructured records, often descriptive text and narratives.

Tunnel Vision versus Big Picture

As a result, it is challenging for anyone — users, caregivers, administrators or payers— to get “the Big Picture”. Like the story of the blindfolded men encountering an elephant, each one interprets the whole through the narrow lens of what is immediately perceivable by the remaining senses.

New Wine, Old Bottles

Fortunately, the very same technology that has brought about the problem also can provide solutions. Data analytics is the hottest ticket in today’s information technology scene. Data mining, machine learning, deep learning and artificial intelligence offer us the means to make sense of this mass of bits and pieces in a way that individuals — even large teams of people — cannot.

Big data analysis has been a part of managing efficient businesses for some time now. We can extend the lessons learned from business into healthcare delivery to the great advantage of all —- users, caregivers, providers and payers.

Meanwhile, Behind the Scenes

While this flood has been building up, a paradigm shift is ongoing in the way quality healthcare delivery is assessed. For decades, the model of payment in healthcare was “fee-for-service”. Whether the outcome was good or bad, a service was appraised as being worth a specific sum of money and the amount released to the provider.

In recent decades, quality assessment has shifted from a physician-centric approach to a patient-centric one. The endpoint for satisfaction is an outcome that the patient feels is worth rewarding. Life and activities of daily living have been changed for the better (or at least, not worsened) by the transaction. The two points-of-view are, quite often, tangentially opposed.

A “pay-for-performance” model is slowly replacing fee-for-service.

This new model demands a panoramic view of service provision where the individual is compared against a population-based norm. The data keeps shape-shifting and has to be evaluated in real-time from the perspective of the 3 Vs: volume, velocity and variability. Humans can’t do this with ledgers or even spreadsheets. Big data analytics is the need of the day.

Promises to Keep

The intention to harness big data can be sincere, but the tools cannot be wished into existence. There is no magic wand. Starting from a well-organised assessment of needs, healthcare analytic systems have to be carefully designed and implemented. It’s all too common to take a “kitchen sink” approach to the exercise and end up with a product that no one likes.

The Winners

Healthcare data analytics will benefit four groups.

  1. Patients will receive the best quality of care.
  2. Professionals (caregivers) can deliver the best quality of care.
  3. Providers (hospital administrators) can assure users of getting the best quality of care.
  4. Payers (third-party agencies) can be confident in getting the best value for money.

Let’s take a walk through the garden of possibilities.


Data Sources

Where does this mass of information come from? Every aspect of healthcare delivery is today, a geyser of data.

The Patient Record

The patient record is the cornerstone of high-grade medical care. It’s where the process of data analysis begins.

The history and physical exam report is the core component. This document maps the patient’s current and past health status in great detail. Personal habits, past illnesses, family and social history, medications, and treatment plans enter the archive.

Other details are appended over time. They include:

  • lab summaries,
  • treatment plans,
  • procedure notes,
  • nursing notes,
  • medication records,
  • progress notes,
  • consultation requests.

Over time, the repository can become quite sizeable and bulky. Making meaning out of the record becomes a laborious and frustrating endeavour.

The Electronic Health Record (EHR)

The traditionally paper-based record is now captured digitally as an electronic health record (EHR).

EHRs have many advantages over paper.

  • They don’t need the vast spaces that physical records demand.
  • Multiple users can view them at the same time, from different points of the hospital.
  • They can be transmitted anywhere in the world.
    • Most of all, being digital, they lend themselves to data analytics.

The push for widespread EHR usage in recent years has led to the availability of an extensive database which, after analysis, may be repurposed as information packets directed at improving patient care.

There is data in plenty and, of concern, just as many standards for defining the record structure. Any given piece of data may be stored and coded in any number of fashions, often with the same package.

Other Hospital Data Sources

Modern healthcare delivery is a comprehensive, diverse, complex system, probably more so that any other activity in everyday use. Every element of this system pours in data which needs to be factored into the care of a patient.

Some typical sources include:

  1. Laboratory Information Management Systems (LIMS): The number of tests available for clinical use run in the hundreds. Starting from collection of samples from the patient to transporting them, processing them in highly sophisticated machines, reporting results and delivering reports back to patients and care providers, there are numerous points of data collection.
  2. Diagnostic Procedures: There is an equally large number of diagnostic procedures used today. Most of them are now capable of recording the entire transaction digitally. ECG, X-rays, scans, endoscopic tests, angiograms: every one of them can be piped into the data backbone of a hospital.
  3. Monitoring Equipment: The mandate for high standards of patient safety and outcome results in the need for intensely monitoring patients during their journey in a hospital. Multi-channel monitors, alarms, respiratory support devices and many more are data points.
  4. Wearable health devices are here to stay. Immense amounts of personal information are pouring in every day. We have access to perspectives of any persons’ health in a manner never imagined before.
  5. Pharmacy Management: Beginning with simple records of prescriptions, pharmacy systems offer an opportunity to keep track of the complex interactions between drugs and quality care.
  6. Scheduling Patient Flow: A hospital sees large movements of people in and out of the system: appointments have to be made, patients tracked during their journey from area to area, beds allocated to the satisfaction of the patient and the doctor. Computer-based systems coordinate these functions today. They are no longer hand done. Once again, tons of data.
  7. Radiofrequency identification (RFID) is increasingly integrated into healthcare to provide real-time management, tagging, and tracking of patients and staff
  8. Insurance Claims/ Billing: The entire process is now done online. The life of an institution hangs on the efficiency of financial management.
  9. Human Resources and Supply Chain Management—many healthcare organisations now use enterprise-level systems to manage the complexity of care in modern hospitals.

This list merely skims the surface of all that is available. Suffice it to say that modern healthcare delivery pivots around data management.

Meet the Data Scientist

We are now at a point in time where the 3 “Vs” of data which we talked about have to be tamed and converted into useful, actionable packets. The complexity of the task has led to the evolution of a distinct brand of information analyst: the data scientist.

They are highly skilled, specially trained, much-in-demand professionals who are a single-point resource for managing, analysis and interpreting Big Data. They have the capability of using tools that are in themselves complicated bits of engineering.


The Upside

I: Patients

Medical practice is, in its entirety, directed towards the welfare of patients. Let’s see how data analytics can improve what is delivered.

A: Chronic Disease Management

Patients diagnosed with chronic non-communicable diseases (NCD) consume a substantial portion of health services. A handful of specific conditions like diabetes, high blood pressure, heart disease and respiratory disorders account for a major share.

Cost-effective management of NCDs hinges on the ability of providers to pre-empt high-impact, high-cost complications which often occur in patients with these disorders.

NCDs, usually life-long afflictions, provide a wide window of opportunity for applying health care data analytics. The number of data points that need to be weighed and acted upon in each patient can overwhelm the cognitive capacity of the most well-informed, conscientious doctor.

Using smart devices, RFID-embedded machines and the universal availability of mobile telephony, patients can be closely monitored for specific target levels such as vital signs, oxygenation, blood sugar, glycosylated hemoglobin, blood pressure and many more. Detection of abnormal levels or worrisome trends permits early, evidence-based intervention which can slow down the rate of progression of many of these disorders.

Treatment can be personalised and tailor-made to fit the demands of each patient.

In a review of 49 studies of chronic disease management (Bhardwaj et al, 2018), big data analytics was beneficial in:

  • risk prediction,
  • diagnostic accuracy,
  • patient outcome improvement,
  • hospital readmission reduction,
  • treatment guidance and
  • cost reduction.

Population Health Management using predictive analyses has shifted the focus of Public Health from the traditional wait-and-watch approach to prediction and prevention.

B: Genomic Medicine

Genomic Medicine has changed the face of medical practice. Patient genotypes can provide pointers to the most effective drugs and treatment regimes, risk of complications and long-term outcomes.

The discipline is expanding at a breakneck pace. New information pours in every day. Genomic data has to be matched to the vast amounts of values observed for individual patients: a daunting task. The field is wide open for application of data analytics.

 

II: Professionals (Care Providers)

Although the doctor continues to be at the centre of healthcare delivery, modern medical practice is a collaborative effort involving many highly trained and certified providers: nursing professionals, pharmacists, physical therapists, social; workers to name a few.

Data analytics bears great promise for enhancing the skills of care providers.

A: Pre-empting acute/ critical events

As discussed earlier, predictive algorithms can point out and highlight patients with chronic disease who are at risk for crisis situations. Interventions can be made before a patient’s condition snowballs into an acute crisis requiring emergency department visits. Data analytics can identify such high-risk individuals early. Ongoing progress can be monitored, and customised care plans put in place.

B: Learning Health Systems

The information base of healthcare delivery is expanding and changing so rapidly that conventional learning tools like textbooks are obsolete almost from the time of publication. Medical information has to be far more dynamic and real-time.

Data analytics offers tools for designing and implementing “learning health systems”. Every patient visit is an opportunity to both learn and generate new knowledge. Knowledge bases can be looked up to provide the most current evidence. Recommendations can be matched to a patient’s specific data set. New patient information can be added to a global database and analysed on the fly.

Personalised Medicine is the mantra of the day.

C: Research

Data mining tools can pick up patterns that are not easily seen by humans. As data accrues, the analytic engine can keep sniffing out many gems of information and new knowledge. Some examples:

  • Risk assessment
  • Early detection
  • Epidemic detection
  • Potential cures
  • Quality of life improvement
  • Prevention strategies

The COVID 19 pandemic has shown us numerous instances of data analytics picking out potential treatment modalities.

 

III: Providers (administrators)

Hospital administrators are under constant pressure while performing the difficult balancing act between quality and cost. Despite its undeniable benefits to other business domains, healthcare has been slow, even reluctant, to adopt practices that are of proven value in business. The post-Covid years are sure to see notable changes in healthcare delivery methods. The role of data analytics will be crucial to survival and staying afloat in what promises to be a highly competitive arena.

Here are some critical areas where data analytics can find an application.

A: Key Performance Indicators (KPI)

Every process offered in healthcare has an outcome. Both process and outcome can be objectively assessed, tracked over time frames and outcomes compared against established norms or over changes in time within a given provider’s domain. This is a KPI.

Any number of KPIs are in use. Some common examples include the length of stay (LOS), 30-day readmission rates and healthcare-associated infection (HAI) rates.

The variables (process(es), factors) underlying each outcome can be complicated. Making associations between intervention and outcome can’t be done manually. Multi-factorial analysis of massive data requires data analytic tools.

KPIs can be keyed into performance dashboards (see below). Feedback to caregivers, when done in a sensitive, non-punitive manner, can be powerful tools for quality improvement.

KPIs can be used to set up “best practices” manuals that could be highly specific for a given institution.

Even with clear goals in mind and a manageable list of KPIs, the process gets very foggy when large volumes of data are involved. Enter, data analytics.

30-day readmission rates

30-day readmission rates are an important KPI of quality of care. Hasty discharges before adequate stabilisation of patients often result in readmissions within a few weeks.

These events lower patient satisfaction. Outcomes are often adverse. Hospital costs climb steeply. Payers often impose penalties on providers for this complication.

Data analytics give valuable insights into the mechanisms that could have been responsible for this event. Corrective measures and policy changes could be implemented.

B: Patient Traffic Flow Management

There is a constant movement of patients and personnel, both into and within a hospital. For long periods, this flow has been managed by personnel who acquire skills on the job, without any formal training in operations management. Considering the intricacies of patient movement in a modern hospital, data analytics can be handy for smooth service delivery.

Waiting time is a leading cause of patient dissatisfaction. Quite often, appointment times are delayed by long periods. Patients who need elective admission often simmer in lobbies till rooms are ready for occupation. The average waiting time in an emergency room is about 4 – 6 hours.

Radiofrequency identification (RFID) is a useful option for tagging and tracking patients and staff. Patient’s can be pinpointed with accuracy. The data is valuable for shaping patient flow in the care process. Once again, data analytics offers solutions for optimising and managing hot spots related to patient movement.

C: Billing and Finance

However competent the caregivers, efficient financial management is vital for organisations to stay afloat.

Key Performance Indicators (KPI) can be handy for finance managers. A variety of metrics are available from organisations like the {Healthcare Financial Management Association (HFMA)

Data analytics can provide up-to-the-minute assessments of the financial health of a hospital.

D: Human Error

Adverse events during healthcare delivery are commonly due to human error. Failure to note abnormal values, improper medication administration or misidentification of patients are all too common.

Data analytic systems can spot these events and issue warnings.

 

IV: Payers

Third-party payers usually make healthcare payments in modern practices. Be they governmental organisations or private insurers; they are always battling costs and seeking to get the most value for money.

Data analytics are vital tools for payers.

A: Comparative Analysis

Data analytics permit payers to survey the market for costs and effectiveness of specific disorders and interventions. They can be done both within an institution and between hospitals. Device and procedure costs can be compared.

Pricing data can be mapped against quality outcomes to identify the best quality, lowest cost providers. This data can be used to leverage prices with hospitals carried by the payers.

Once again, data analytics can provide detailed, up-to-date figures.

B: Fraud Prevention

Suspected fraudulent claims can be investigated with data analytics. Comparisons can be made for similar claims at other hospitals of known quality and integrity. Hard data can support rejections.


Dashboards and Displays

It’s not enough to capture and process data. Actionable information has to be displayed to users in a fashion that is easy to grasp. Anyone who has played video games will know that current-day computer graphics is more than up to the task.

The Old Way

The typical healthcare report is a static document delivered in a one-size-fits-all model. Revisions and updates are slow and time-consuming, often out-of-date at the time of printing.

The complexity of data available demands much more dynamic output.

Dynamic Displays

Look at the NYSE

Although nowhere as demanding, the rapidly moving and changing screens that we see on the floor of the NYSE and other financial centres, gives us an idea of how data can be displayed for the benefit of users.

Interactive, multi-coloured dashboards are available, showing data in easily-grasped formats. The data is updated in real-time or at least in short, frequent intervals.

Users can view critical metrics, trends, benchmarks and such.

Bells and Whistles

Complex data, when presented as easily-understood charts and tables, allow users to make confident decisions.


The Brave New World of Healthcare Data Analytics

Everywhere we turn, we keep seeing, reading or hearing about the rapidly expanding role of big data analysis and artificial intelligence. Computer power and software complexity have reached a point where hitherto fortressed domains are being breached. Recent reports of programmes generating sophisticated pieces of journalism that are hard to distinguish from human writing have induced a sense of fear in all professions. Robotisation revolutionised manufacturing. The automation wave is advancing relentlessly into white collared jobs and the service sector.

Healthcare has stayed defiantly refractory to the changes happening around it. This state can’t last for long. Major disruptions are in sight. Healthcare data analytics hold the promise for being a dominant force in bringing about a much-needed change in the area of healthcare delivery.


Making meetings matter: do it like Bezos

“It’s a truth universally acknowledged” that employees resent meetings and try their best to avoid attending them. Surveys show that as much as fifty percent of people in an organisation believe that they are a waste of time. Executives can spend up to 20 hours a week on them. They interfere with productivity; time spent could have been put to better use. But, no enterprise, big or small, runs without periodic meetings.

We Don’t Like Meetings and We Don’t Want Them Gone

Still, when asked if meetings should be abolished altogether, the same number of people reply that it would not be a good move. They feel that meetings are essential for maintaining a democratic spirit. Ideas should be aired, discussed and modified by groups of people; otherwise, the management style will be seen as autocratic.

Two factors are at work.

1. Parkinson’s Law of Triviality — Meetings have agendas. Items on an agenda vary in importance from critical to trivial. Professor Northcote Parkinson, him of the much quoted, eponymous law, also described a constant characteristic of meetings: The Law of Triviality.

There is an inverse relationship between the importance of an item and time spent on discussing it. Plans for a large investment on a major expansion will get passed over in a few minutes whereas a half hour or more will be spent on arguing about a new coffee dispenser in the lounge. It’s easier to talk about something that you are familiar with than something beyond your knowledge limits. (This law is also called “ the bike-shed effect ” based on a popular anecdote.)

2. More People, Less Effective the Meeting: There is also an inverse relationship between the number of people attending and effectiveness of a meeting.

The optimal number is 5. As the number increases, meetings become more and more unproductive. At 20, chaos reigns; from here on — 20 or a 100 — the number in the room doesn’t make a difference. It’s imperative that only those who can contribute effectively to the discussion be invited to take part. This is one element that is seldom carefully addressed.

The challenge, therefore, is to structure meetings to make them matter.

First, and For Ever, No “PowerPoints”

Jeff hates PowerPoint (or any other flavor) of presentation app. He believes that “ Powerpoint-style presentations somehow give permission to gloss over ideas, flatten out any sense of relative importance, and ignore the interconnectedness of ideas.

That’s an earth-shaking diktat for all of us who automatically reach out for these tools when making a presentation.

Well Structured Narrative

The man says, in a much-quoted memo that he sent out: “Well structured, narrative text is what we’re after rather than just text. If someone builds a list of bullet points in Word, that would be just as bad as Powerpoint. The reason writing a good 4 page memo is harder than “writing” a 20 page Powerpoint is because the narrative structure of a good memo forces better thought and better understanding of what’s more important than what, and how, things are related.”

The fundamental argument is not so much about the medium itself — Powerpoint or written document — as the need to think critically and clearly.

Here’s how it’s done

Step 1: Writing the Narrative

The person or group responsible for the meeting, spends a good amount of time producing a 4-6 page, tightly reasoned, carefully worded, written narrative. (More on how to do this in another post).

Step 2: All Those Needed for the Meeting Gather at an Appointed Time.

Step 3: Read the Narrative for 30 Minutes.

The document is NOT distributed ahead of time.

Everyone present now gets a copy of the document and spends 30 minutes in silent reading. They note down their observations, comments, opposition and so on, now.

Wouldn’t it be more efficient if the document were to be given in advance? No, says Bezos; “Just like high school kids, executives will bluff their way through the meeting, as if they’ve read the memo, … you’ve got to actually carve out the time for the memo to get read — and that’s what the first half hour of the meeting is for.”

Step 4: Discussion Begins Now.

The document is used as the anchor for all that follows. It’s easy to keep all members tightly focused on the task at hand with everyone being on the same level of knowledge about the agenda. The event acquires both magnitude and direction.


Meetings have been given a bad rap. Some of the reasons are valid. In order to extract maximum effectiveness, Jeff Bezos of Amazon uses an unique structure for all meetings in his organization. In summary, here’s how he does it.

  • Prepare a carefully-written, 4-6 page narrative about the topic for discussion.
  • Invite the smallest possible number of people for the meeting. Limit invitees to those who can make meaningful contributions.
  • Circulate the document at the start of the meeting and give everyone present half an a hour to carefully read and annotate the paper.
  • Tether discussion to the contents of this document.
  • Designate one person to be responsible for summing up the discussion and to provide an action-taken report.

The sole purpose of meetings is to create change, hopefully for the better. Like any tool, meetings are neither good nor bad in themselves. It’s how we use them that matters.

“The meeting of two personalities is like the contact of two chemical substances: if there is any reaction, both are transformed.” ― Carl Gustav Jung


Dr Arjun Rajagopalan

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How to write a business narrative which will impress Bezos

“There is nothing to writing. All you do is sit down at a typewriter and bleed.” ― Ernest Hemingway

But then, we are not talking about writing like Hemingway or Nabokov or Alice Munro. You have come up with a project. You are sure it’s a winner. You work at a company like Amazon and to take it forward you have to first write about it in a 4-6 page narrative. This document will serve as the pivot for all discussions about the project, something that your colleagues and bosses can read with ease and grasp the ideas you are putting forth.

What are We Looking At?

First things first, we must be in tune with Jeff Bezos’ recommendation. “Writing a good 4-page memo is harder than “writing” a 20-page Powerpoint … the narrative structure of a good memo forces better thought and better understanding of what’s more important than what, and how, things are related.” Powerpoint presentations are banned at Amazon. Meetings, when needed, have to be structured around a pre-prepared, carefully thought out, flowing narrative.

Who, Me?

The prospect of writing a business narrative is daunting to most of us. We baulk at the act because we have never received training for it. Writing with clarity and flow is hard work. Even Hemingway viewed it with trepidation.

Yes, You

Most narratives, business or fiction, have a typical structure. Once we get familiar with this simple scaffolding, the process of writing becomes natural and effortless. Let’s look at a 4-step method of producing a business narrative that even Jeff will smile at.

Step 1: Where are We Now?

As Julie Andrews sang, “Let’s start at the very beginning.” What was it that provided the original impetus or spark for putting forward this proposal? Write about it in simple words. The starting point could be one or more of many things. Maybe it was:

  • Pain points: Write about whatever produced discomfort in your present situation: things that make you uncomfortable, wary, anxious, frightened or angry.
  • Dangers ahead: There may be lurking threats to the organisation which you feel need prompt and proper handling.
  • Opportunities: Maybe it’s about things that present a lucrative prospect and could be harnessed for the good of the company. Describe it.
  • Innovations: In a rapidly changing business world, it may be that you feel the present set up does not encourage new ideas. To survive, you sense that innovation has to be nurtured.
  • Competition: Today’s world is brutally competitive. You know that other groups are sniffing at your heels. We have to start moving faster and farther than them

The number of starting points are limitless but you will have a single, specific item. Identify it and write in detail about it.

Step2: Where are We Headed?

If you don’t know where you are going, one thing is certain: you won’t get there. Describe your goal and ambition. There are many frameworks for outlining this section. A popular one is the “SMART” mnemonic:

S = specific – be clear about what you want.

M = measurable – assess results by objective means.

A = assignable – allocate specific people for specific tasks.

R = realistic – stay within your ways and means — don’t over reach.

T = time bound – be hard nosed about deadlines.

Step3: The road map

We live in the age of Google maps. You wouldn’t stir out anywhere new without first getting a road map. Your narrative must talk of three things.

  • The various steps that need to be taken to get to the goal.
  • The time limit and deadlines for each step.
  • Obstacles that are likely to pop up en route and your plans for working around or over them. Anticipate road blocks.

Step 4: What will it Look Like when You are There?

“Are we there yet?” — the constant refrain of children on a road trip applies to your narrative as well. Don’t just go with gut feelings. Refer back to the stated goals and make sure that you have reached every one of them. Take a hard look.

  • Use objective methods of assessment.
  • List the benefits and joys of having reached your destination.
  • Pitch it against the list that started your journey.

Not Just for Business Narratives — be an Ace Speaker

Storytelling is a sure-fire way to capture attention. Anytime you need to make a presentation, convert it into a story and you will hold your audience during your talk. The framework that we just saw can be used to rephrase an idea into a narrative. With a little imagination, a boring sermon can be transformed into a tale of how the idea was born, its goals, the path to implementation and the view from the top. Like the ad says: “Just do it.”

Clever Tip

You don’t have to use the steps in the order listed. You can play around with it for dramatic effect. For instance, you could open with a vision of what the end looks like, shift to the reason for starting the journey, talk about the road and end with what your goals were. Play around with the four steps and see which order suits the spirit of the narrative

Come Back to Papa Hemingway

You don’t need a vast vocabulary or a smart turn of phrase to write well. Hemingway said this when putting down Faulkner: “Does he really think big emotions come from big words? He thinks I don’t know the ten-dollar words. I know them all right. But there are older and simpler and better words, and those are the ones I use.”

Write from the heart. Focus on:

  • Simple language.
  • Short sentences.
  • Brief paragraphs — each one containing one idea, each paragraph flowing logically into the next.
  • Anticipating objections and addressing them ahead of time.
  • Redrafting your manuscript many times. Be a ruthless critic of your writing, logic and flow. Every word must have a reason to be there.

Writing well is the best way of thinking well. Which is why anything written is given far more value than spoken words. Penned sentences linger as a legacy of a human being, sometimes well beyond the life of the person who wrote them. To disseminate great ideas, you need to write captivating stories. 

“After nourishment, shelter and companionship, stories are the thing we need most in the world.” ― Philip Pullman


Dr Arjun Rajagopalan

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Personal journals: a cheaper and more effective alternative to psychotherapy

Albert Einstein, Mark Twain, Marie Curie, Nelson Mandela, Thomas Edison, Virginia Woolf, “Che” Guevara, Anne Frank, Leonardo da Vinci: a list of famous people with a diverse range of interests. What did they all have in common? They maintained personal journals through their lifetimes.

Who’s Got the Time to Write Daily?

First, a popular myth has to be dispelled. Journal writing need not be an unremitting, daily effort. The association of journaling with conventional diaries, segmented by days, is, most likely, the reason for this misconception. Daily journaling quickly becomes a chore that is easy to give up.

Instead, only record what you want to remember. Make it an exercise in capturing and archiving thoughts, emotions and ideas coming from within you. Write about interesting people, conversations, meetings, books, lectures, places — anything that captures your attention. Over time, the collection will become a resource that will act as a secure helmsman to steer you through the turbulence of life.

It’s best to keep it as a private record although, we are so much richer for many of them having been published. Anne Frank’s The Diary of a Young Girl is the most well known example of the power of a journal. There are many more.

Why Should You Keep a Journal?

Journaling should be a collection of ideas rather than a chronological log of quotidian events. Putting your thoughts down on paper (or as digital bits if you prefer) unburdens your memory, a notoriously fallible storehouse. Journal writing is a powerful productivity and self-improvement tool.

There are numerous benefits to keeping a journal.

  • Problem solving: Writing is a tool for thinking clearly. The effort of transforming what’s in our heads as disjointed notions into words clarifies ideas and concepts. Spending fifteen to thirty minutes in this effort allows you to see the problem in distinct, easily grasped pieces. Organising them and making sense out of the puzzle becomes an easier task.
  • Decision diary: Get into the habit of making entries for the more significant decisions you make in your life. Put down brief statements about the following items:

— The nature of the situation that needs a resolution.

— A list of the possible routes of action.

— The pros and cons of each of them.

— Your choice and why you did so.

— What tradeoffs did you have to make?

— What do you expect from this selection?

As the diary grows, review your entries now and then. You will get a good insight into your decision-making process.

  • Stress reduction: Studies have shown that regular writing reduces stress. Anxiety and depression can be alleviated to remarkable degrees by expressive writing and pouring out deep emotions.
  • Physical ailments: The benefits are not limited to behavioural problems. Many common disorders manifesting with pain and limitation of daily activities can respond to a simple recording of symptoms and feelings. Recognising pain and discomfort as something distinct and reportable goes a long way to augment healing processes within yourself.
  • Gratitude journal: Regardless of how bad things look, there are still so many others which are going right for you. You don’t have to be a Pollyanna;there is much to be grateful for. Write them down in your journal. The effects on your overall wellbeing can be substantial.
  • Self-discipline: Regularity in writing is an act of self-discipline and will power. It builds up resilience in all other aspects of your daily life.

Despite its popularity, there’s ample evidence that undergoing therapy with a trained analyst may be no more beneficial than talking to someone, even a friendly bartender. A well-nurtured personal journal is all you need. The list of winners at the head of this article, and many more, is proof.

How Do I Go About It?

The straight answer: Use whichever method or tool works for you.

It’s best to keep the process as simple and handy as you can: from just a notebook (a Moleskin, if you wish) to drawing, sketching, mind-mapping, visual thinking, photos, voice recording or any of the dozens of digital tools that are available for the purpose.

Apps like Evernote or Bear are fantastic for the ways and means by which you can organise and manipulate your entries. There are apps like Journal One which are specifically designed for the purpose.

The trick is consistency. Stick with whatever gives you the most value for the effort.

How Often Should I Review My Journal?

Once again, there is no hard and fast rule. Whenever you do look back, chose a time when you are calm, rested and still. Although there is a huge temptation to look when times are turbulent, you may not get the most out of your writing at these moments. Nevertheless, let your intuition direct you.

You must let your journal be a guiding lamp in your progress through life. No one can know and understand you better than yourself. It’s not unusual to be taken by surprise at the profound nature of your observations.

Stephen King Says

“Writing isn’t about making money, getting famous, getting dates, getting laid, or making friends. In the end, it’s about enriching … your own life, as well. It’s about getting up, getting well, and getting over. Getting happy, okay? Getting happy.” ― Stephen King, On Writing: A Memoir of the Craft


Dr Arjun Rajagopalan

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