The explosion in digital media - web, social and now mobile - represents a departure from how things were like in the last century. This proliferation of digital media is both a threat and an opportunity for many businesses. Business Analytics can be leveraged to process data, sentiment, buzz, contacts, context and other aspects of business interest in real time, for business performance and impact. The course picks and uses use-cases from a variety of industries and geographies, to showcase the potential and impact that business analytics done properly (or not) can have on business performance.
Exploratory Vs Confirmatory Dichotomy
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來自 Indian School of Business 的課程
Business Analytics and Digital Media
112 個評分
從本節課中
Introduction to Business Analytics
An overview of the what and the why
Learning outcomes by the end of week 1 should normatively be that (a) Students grasp what is business analytics from the perspective of a business manager, (b) identify areas of interest, overlap, co-ordination and conflict with other business functions and processes in the firm, (c) and, develop an appreciation for the value of data, of analyses and of the components of analytics.
與講師見面
Sudhir VoletiAssistant Professor and ISB Research Fellow
Marketing
[MUSIC]
Hello everybody, welcome back.
Let me, well, before proceeding any further,
this particular section is going to deal with some more preliminaries.
And in particular, what are they going to be?
Well, we're going explore two important dichotomies which are relevant to what we
are going to do, namely problem formulation and thereby a design for
analytics.
The first dichotomy is that, would be market intelligence,
business intelligence versus market research.
And the second, within the market research embed is basically going be
the exploratory versus confirmatory dichotomy.
And finally, based on these two dichotomies, a series of multiple choice
questions will follow to explore the relationship between the two.
So, let me get to the first dichotomy.
Market intelligence, was as market research, also called sometimes business
intelligence and business research in some sense, right, market research.
What is market intelligence?
Well, market intelligence in some sense is an ongoing activity
which is not tied to a specific project, okay?
It's basically something that you collect over time anyway.
Market research on the other hand,
is a research project that is a commissioned research project.
It is a specific project, and it has specific questions.
Now intelligence, because it is in some sense an ongoing activity,
is just about keeping eyes and ears open, okay?
There is no real output that is expected directly.
I mean, it's something that we hope to discover with time.
Whereas here, you're much more deliberate in data gathering because
there are specific questions in play.
What is business intelligence do very well?
Basically gathers bits and pieces of data from out there and
try to sift them, often using expert judgement.
The expert judgement nowadays especially needn't always be human,
there are patterns to be, in some sense, discerned.
Business research is time-bounded and it is planned, it has to be
to specific projects, specific questions, deliberate data gathering.
The competencies required to pull off business intelligence,
basically database management skills, organizational leadership skills.
And I say that because the org leadership
has to stick with something that may not yield an immediate output.
The core competencies on the market research side
is basically problem formulation.
What follows is hopefully logical and straightforward but
in some sense discernible.
MKTR there, is marketing research.
Now let me move to the second dichotomy.
We've seen business intelligence or market intelligence versus market research.
The second dichotomy is exploratory versus confirmatory research, so
this is within market research.
Two basic types.
Exploratory research, the goal is discovery.
Confirmatory research, the goal is resolution.
Is it A or is it B resolved, tell me?
In exploratory research, the questions are open-ended.
What's new, what are we missing, what is competition up to, etc?
So these are open-ended questions, and we don't know what the answers will be.
We hope to discover something interesting.
In confirmatory, because the goal is resolution,
the questions are much more specific.
Is it A or is it B?
Should we launch or should we not?
What should the price be, and so on?
Now exploratory research is conducted to broaden your horizon, your vision and
your scope.
Whereas confirmatory research is conducted to narrow the field of options.
Exploratory research coincides with what we call information needs early in
the project cycle.
And the decision cycle that is confirmatory comes typically into play
much later.
The non-application of exploratory techniques incurs opportunity costs.
Discoveries fail to happen, alternatives go unrecognized, insight is not achieved.
Now these are not things that will show up on your PNL statement.
It's just one reason why exploratory research is in some sense
easy to overlook.
Confirmatory research on the other hand, if done poorly,
can actually incur direct costs that will show up on your PNL statement.
So in some sense, a lot of managerial time and
attention, including academic time and attention, is focused on confirmatory.
However, it is my belief,
that in the future, the goal is to be found the exploratory side.
It's in basically asking the right questions and finding,
discovering things that others have not yet done.
What will follow now are a serious of four multiple choice questions
based on these two dichotomies, market intelligence, market research,
exploratory research, confirmatory research.
Get back, getting back here.
What about this distinction between intelligence and research, and
where is it going?
It is clear to me that the boundaries between the two are blurring.
The chances are the two will converge in the near future.
In certain sectors, they might have done so already.
The main driver of this trend?
Technology, which is collecting data all the time, analyzing data all the time.
Within technology there are,
and if you go back to what we've done at the very beginning,
the supply side of the profit equation and the demand side of the profit equation.
Even here, the main driver of this trend, technology, does so
by acting both on the demand side and the supply side.
Let's quickly see how.
On the supply side, technology basically acts by lowering the cost of data,
its collection, its analysis and so on.
Here is an example. This is the decline in storage cost per
gigabyte, dollar per gigabyte, and you can see it all the way from 92 to 2012.
In 92 a gigabyte of storage costed about $570, today it costs $0.02.
This is for processing power, and you can basically see the prices of
personal computers just crash exponentially.
So it's become cheaper on so supply side, basically, saying the cost of doing these
things, storage and processing, has become cheaper over time.
On the demand side what has happened is that we're actually seeing
technology diffusion and adoption at a rate that are unprecedented in history.
The telephone took 75 years to reach 50 million people, Angry Birds did so
in 35 days.
The mobile phone, the Internet, and the PC, in some sense, so
this one as technology adoption, and you can see the number of years it took for
them to reach where they are.
You can see that the cellphone in particular has basically exponential rise.
Just shooting right up.
And the cellphone enables a lot of data collection, a lot of data capture.
So there's data flooding in everywhere.
Put the two together and what you have is basically an amalgamation,
a merger of marketing intelligence and marketing research into one function.
I don't know, you could call it I guess, marketing research and intelligence or
something like that.
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