If you are pursuing a business analyst course, you should learn the various investigative approaches and techniques relevant to your core domains and business areas.
There was a time not so long ago when Business Analyst course would focus on training with simple cases studies and data management techniques. In the last 5 years, things have changed remarkably due to the advancement of tools and techniques to help business analysts adapt to an investigative approach to any decision-making project.
In this article, I have highlighted why you should adopt an investigative approach to business analysis and what types of techniques would serve your mission.
Here are the top methods you can use for investigation.
The simplified business analysis would involve the use of these techniques –
Qualitative: What kind of problem plagues the business?
Quantitative: How many problems are impacting the business? How much cost is involved in the crisis? How many people are affected or how many of these people do we need to solve the problem?
Diagnostic Analysis
I prefer to add another type of technique to this whole mix of investigative business analysis course.
It’s called Diagnostic Analysis.
According to a leading research firm, diagnostic analytics is an advanced analytics technique used to investigate a problem using data and content characterized by the use of data science tools and solutions, such as data mining, wrangling, data visualization, linkages and correlations.
Types of Research
Business Research
Business analysts need to be research-focused from the first hour they step into the role. This could involve exploring various teams, groups, departments and cost-centres of the organization that need some improvement from various points of operational efficiency or manpower handling. Thanks to internal documentation process and HR policies, business analysts mostly have easy access to the various information they might need to perform the business research. Internet resources also enable an analysis of background information, especially financial statements and trading policies.
Workshops
A very popular method to continue investigative business analysis involves setting up Workshops.
This set up brings multi-disciplinary groups at one place, discussing and working together on a single problem under a simulated environment where variables are fairly controlled without influencing the participants’ behaviour and style of working.
Business analysts create a highly cooperative ecosystem to ensure participants have a chance to formally get used to the functions, events and targets expected from them during and at the conclusion of each workshop.
Use case diagrams and contextual behaviour reporting are often part of business analysis resulting from workshops.
These can be performed using scenario creation, control conditions and centralization /decentralization of workflows/paths required to handle business analytics at various steps.
Prototyping / Simulation
Every business analysis technique is based on the extent or scope of the project team involved in the process.
Prototyping is a basic analysis process which involves the creation of working models, in a limited scale, demonstrating the scope of this analysis to prove the efficiency of the various components/resources.
A prototype is a cost-saving model that can be discarded if it’s a failure, or improved and upgraded if the results are as per expectation.
Unlike other techniques, the prototype is a very model-centric approach, influencing human decision making based on visible cause and effect outcomes.
If you are in a reputed business analysis course, you are more likely to work with approved Predictive Analytics business analysis techniques based on prototyping/simulation. These are especially adapted for software and automation tool developments used in the healthcare, IT and manufacturing industries.
Shadow Techniques
Now that we have understood how Observation, Simulation and Case studies for investigative business analytics work, we can leverage another technique.
It’s called Shadowing.
Shadowing is simply explained based on the kind of roles, targets and resources used up, and identified through the interview process.
Shadowing has some benefits over other techniques, especially when it comes to “often taken for granted/missed” nuances of analysis. These are used in Big Data Analytics.
Conclusion
Now that you have more or less identified the supreme techniques used in basic Business analytics, you can easily tell why AI and Machine Learning applications are so popular in this field! Obviously, it saves tons of resources, is cost-efficient, and is not riddled by risks of human bias.
The final outcome when reported in a document format, represents the case and pillars of research. It is often considered as the precursor to the futuristic investigation.