Toastmasters Project 7: Impending Future of Business Intelligence (BI)

Greetings, fellow toastmasters, friends and guests,

Definition of BI (Slide 1)

You may have heard about Business Intelligence (BI). But what does that really mean? In simple terms, it refers to delivering relevant and reliable information to the right people at the right time with the goal of making informed decisions.

To do this, it requires methods and programs to collect unstructured data and convert them into information and present it in ways that tell us business insights or what we call as data storytelling.

Picture this.

  • You walk into a grocery store and wanted to look for chicken, bread and carrots.
  • You don’t need to find an employee and ask them where to look
  • Grocery stores are organized into aisles and signs to make the stores relatively simple to navigate
  • Now imagine the items as your business data and you need to collect information on production hours and sales goals.
  • Most people will look for three experts and ask them where they can find the information and compile the data for you
  • BI is all about collecting messy data and tuning them into tidy and accessible data store
    • That way, you can leverage on your own data and find what you need
    • Today, organizations no longer need complex excel spreadsheets but rather they rely on BI tools to extract data any time they want

Past:

  • BI first started out when people are able to pull reports to analyze the current company performance
  • This was done largely in paper form, which someone dedicated to look at the numbers and they were able to have an integrated view of what is happening and how they can plan for the future

 Current

  • Such tasks have been digitized, we have contracts and receipts now. These make things easier as we can easily generate reports and all we need to do is to gather business insights.
  • In other words, BI is becoming more pervasive now, meaning, we are democratizing BI for the masses, allowing more functions to adopt the tool
  • Case study: Airbnb
    • Use of BI:
      1. Get fast answers to critical business questions by using Natural Language Processing
        • Deployed a natural language processing technology to review the text on the message threads or review boards to lift some sentiment out of it as well. That way, their technology allows them to understand what is driving the feedback or sentiments
        • Data never sleeps, look at trends in their sales pipeline and see which areas can be targeted for impact
      2. Gain insights into customers
        • BI software allows companies to discover patterns within customer behaviors, offering greater visibility into what customers want, when they want it and how they want it
        • Acquired Luxury Retreats, a Montreal-based vacation rental service to include their wealthy clientele that are looking for longer vacation rentals in places that are considered more traditional vacation destinations

Future

  • BI will converge into other areas:
    • Artificial intelligence (AI)
    • Machine learning
  • Predicting seizures and strokes
  • Singapore-based startup Healint launched an app called JustShakeIt that enables a user to send an emergency alert to emergency contacts and/or caregivers simply by shaking the phone with one hand.
  • The program uses a machine learning algorithm to distinguish between actual emergency shakes and everyday jostling. In addition to the JustShakeIt app, Healint is working on a model that analyzes patients’ cell phone accelerometer data to help identify warning signs for chronic neurological conditions.
  • How will BI transform industries?
    • Airline industry
    • Driverless vehicles (Pay as you drive)
      • 10million self driving cars by 2020
      • We cannot ensure make these machines make ethical decisions but we can make them avoid the wrong decisions

Downside of BI
Ladies and gentlemen, as we move towards a collaborative and consensus driven environment, we must also know that technology is a double edged sword.

  • Data storytelling can go against us
    • HR using data to predict when employees are getting married or when they can get chronic diseases
  • Jobs are automated
    • We, humans should stay relevant by investing in our EI and develop skills to listen, interact and motivate others.
    • For instance, a robot can provide a medical diagnosis, but a person can help to understand a patient’s situation (financial, quality of life) before suggesting the best optimal treatment for the patient.

According to McKinsey, by 2020, we will have about 20b machines connected to internet. They include airplanes, turbines, not just our computers. We will continuously gather data. It is then up to us to innovate, use the data wisely to solve society’s problems such as healthcare and environment.

Some of the trends might be on track, some will require a little bit more ambition and effort. But hey, if I get any of these right, remember from who you heard them from.

Thank you and have a good one.

 

 

 

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