The modern business analyst has a lot in common with the master chef of a fine culinary establishment: both must precisely assess, prepare and ultimately deliver their respective content in a manner that not only appeases the customer, but proceeds to flat-out WOW them into committing to continued and eager patronage.
The analyst deals in data, while the chef combines choice ingredients, but the methodology and desired outcome are the same for each. Understanding one position helps us understand the other because the processes are so similar.
The quality of a business analyst’s approach can make or break a data-based organization’s day to day operations and overall strategy, just as the quality of the data chosen can make or break the analyst’s implementation itself.
It’s a delicate series of steps that go from individual to collective levels, but just as the most skilled culinary architects deliver dishes with razor-sharp precision to the tantalization of tastebuds time and again, the battle-hardened business analyst sifts through and presents data in a skilled manner that makes executive decision-making a breeze.
Lets take a look at how this process comes to fruition.
Preparing Your Ingredients: Making Sure Your Research and Data Selection Are Fit for the Table
To properly reach the actual analysis of the data at hand, a business analyst must first make sure the data itself (as well as the corresponding research behind the data) is of a quality relevant and accessible enough to ensure productive and engaging results.
Just as an experienced chef would never serve a customer low-quality (or, let us groan collectively, EXPIRED) ingredients, a successful business analyst ensures that the data to be examined doesn’t lack proper context and isn’t pulled from insufficient research studies.
“Although data analysis can be a powerful aid to gaining useful knowledge, it cannot rescue a badly conceived marketing research study,” write the authors of Marketing Research. “Data analysis rarely can compensate for a bad question, an inadequate sampling procedure, or sloppy fieldwork.”
In other words, shop carefully for your data, know the quality of its source, and buy smart (think farm fresh, not frozen).
In this article, we are drawing heavily from the insights and tactics gleaned from Marketing Research and its four authors
The Three-Step Recipe For Perfect Preparation
In order to make getting started a little simpler for today’s business analyst, you can follow a simple three-step process to ensure quality initial data preparation:
- Data editing – finding and eliminating incongruences, omissions and errors in the data at hand
- Coding – specifying exactly how data is to be analyzed and and entered into a study
- Statistical adjustments (if necessary) – enhancing the data statistics to optimize their quality for the actual analysis.
Once the fat has been trimmed and the data is sufficiently prepped for use, our business analyst may now turn on the stove and dive deep into the analysis itself.
Conducting Your Analysis With The Right Sizzle
Properly prepared data still lacks true relevance until it goes through the full analytics process, but the good news is, when approached in the right manner, data analysis becomes a simple manner of (once again) segmenting your tasks into a series of steps.
Like a chef putting a rack of lamb in the the oven and throwing vegetables on the grill, a business analyst would first categorize the different areas in which the data belongs. This is commonly known as tabulation.
Tabulation provides the business analyst two main functions:
- Frequency distribution – reporting how many responses each element of the research process received
- Descriptive statistics – measuring the mean and percentage of the data (these will be used again later when our analyst chooses from a variety of statistical techniques to complete the analysis)
Once properly categorized, the data is ready for it’s final sear: selecting the appropriate analysis technique.
Knowing The Tools In Your Kitchen: Choosing The Proper Method To Complete The Analysis
Selecting the proper technique to statistically analyze your data can seem like a daunting task at first – there are many to choose from. However, each possible choice simply depends on whether the data falls under on of two categories of analyzation: univariate or multivariate. A chef may categorize a meal as needing either hot or cold preparation, and, likewise, a business analyst will base an analysis choice on whether the data requires a univariate or multivariate technique.
The authors detail univariate techniques as “appropriate when there is a single measurement of each of the n sample objects,” while multivariate techniques “are appropriate for analyzing data when there are two or more measurements of each observation (and the variables are to be analyzed simultaneously).”
Simplified: think single or multi-factor tests. (In our culinary metaphor, each element of your plate either requires one cook-through, or separate levels of multi-staged cooking depending on the item.)
Once the differentiation has been made between univariate and multivariate, a specific technique may be chosen and the analysis performed. Commonly used techniques for each category include:
- t – tests
- z – tests
- Multiple Regression
- ANOVA & ANCOVA (one variable) and MANOVA & MANIOCA (multiple variables)
- Conjoint Analysis (see our previously published article for an in-depth examination of this widely-used method)
Presenting Your Findings With Poise and Pristine Plating
The data has been thoroughly analyzed and the food has been cooked to order, but much effort in either situation will have been wasted if the final product isn’t presented to the receiving party in a manner that satisfies the needs at hand and encourages future business. This is where the importance of presentation comes into play.
“The presentation (of the data findings), whether oral, written, or both, can be critical to the ultimate ability of the research to influence decisions,” says Marketing Research. “The audience should not be muttering, ‘What on earth is this person talking about?'”
Luckily, presenting your data analysis in a matter that avoids these pitfalls and ensures the right decisions are made is the simple matter of following a basic recipe (Let’s face it, everything becomes easier following a recipe):
- Communicate the data to a specific audience
- Structure the presentation
- Create audience interest
- Be specific and visual
- Address validity and reliability issues
Like an exquisite dish plated to look as good as it tastes, data presented in a clear, engaging way ensures that the goals of the analysis are met and no information is lost on the audience.
Why Get It Right? Business Analytics In A Real World Setting
We’ve taken our fearless business analyst (and lets not forget our chef) through the entire the data analysis process, but how does it actually work when applied in a real world setting? Is data analytics as vital to decision making and the longevity of a company as experts would have us believe?
The answer is a resounding YES.
“Data comes into our company in waves,” says SurveyGizmo CEO Christian Vanek. “There is a veritable sea of information we have to sift through and analyze on a daily basis, for both our day to day operations and our customers. Without the right people analyzing the right data in the right manner, SurveyGizmo would cease to function as an industry leader in the big data sphere. Business analysts are invaluable – that’s the bottom line.”
With proper business analytics, forward thinking companies ensure that business remains ceaselessly above that bottom line at all times.
If you would like to look further into business and data analytics methods, we recommend you read the text quoted in this article:
Marketing Research – 11th Edition – David A. Aaker, V. Kumar, Robert P. Leone, George S. Day
If you are interested in winning Marketing Research-centered books and/or learning more about how SurveyGizmo utilizes Business Analytics and beyond, please visit our Market Research Book Giveaway page: