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Day: March 9, 2020

What Are Business Analysis Techniques?

Posted on by Imarticus Learning

Last Updated on 2 years ago by Imarticus Learning

With the growth of AI and Data Science, the field of Business analysis has gained significant value in the past decade. More and more businesses today rely on the acumen of the business analyst to obtain data-driven solutions for their business problems. Let’s delve into how the complex process of analysing business needs and providing solutions to the same is carried out by business analysts.

Business Analysis Techniques

Some of the most popular and relevant business analysis techniques are as follows:

SWOT Analysis

The term SWOT is the acronym for Strength, Weakness, Opportunity, Threat. SWOT analysis forms the most rudimentary business analysis techniques to get a holistic view of the most important aspects concerning the business. This analysis techniques categorise the Strength & Weakness as internal factors of the business, the strong suit of the business could be its brand image and the weak points of the business could be its high price point given the alternatives in the market.

This analysis technique considers opportunity and threats as external factors to the business. The threat could be in the form of increased competition, an example of an opportunity could be expanding into an untapped market. SWOT analysis techniques is a one that is widely used and the application can be done at any stage of the project.

MOST Analysis

MOST stands for Mission, Objective, Strategy, Tactics. These four elements form the core of the MOST business analysis technique. It provides a clear picture when it comes to understanding the purpose and approach of the business. Let’s break each element individually to gain more insight into this valuable business analysis technique.

Mission

Every organisation is started to fulfil a purpose, to solve a problem, to accomplish a goal, that goal and purpose is the mission statement of the company. The primary step to business analysis is to be familiar with the mission of the company, everything else is secondary.

Objectives

What is the objective? How is it different from a mission? Well, the mission takes a broader approach to the problem whereas objectives are the set of goals that the organisation intends to achieve within a certain time period. The objective breaks down the broader mission into more defined goals and a measurement approach.

Strategy

Strategy again takes a broader angle; it can be defined as the approach and plan the organisation will use to obtain its business objectives within the set time frame. Strategy answers the ‘how’ of the business.

Tactic

Tactics are more refined methods to carry out a broad strategy to achieve the goals of the organisation. Tactics are more about short term operational plans to obtain the objectives.

Business Process Modelling

Business Process Modelling considers the process improvement techniques which will help the organisation to achieve the objectives in a more efficient and effective manner. It helps in analysing the gap that exists between the existing business process and the more efficient business process which could be opted instead. The pros and cons of both the business process are taken into factored in before reaching a decision. Some of the major steps involved in the Business Process Modelling technique include strategic planning, business model analysis, process designing, and complex technical analysis. The technique of process improvement is widely used in the IT industry.

PESTLE Analysis

The organisations do not operate in isolation, there are multiple stakeholders in a business ranging from customers to employees and suppliers. All stakeholders are influenced by the functioning of the business and have the power to influence its operations. In the contemporary scenario, sustainability if of utmost concern, it’s not only about profit maximisation for the business but to achieve it in a more sustainable way. PESTLE is the acronym for the crucial factors that influence the business, these include Political, Economic, Social, Technological, Legal, Environmental factors. PESTLE technique analyses these factors and identifies how each of these elements will influence the performance of the business.

Also Read: Business Analysis Trends in 2020

What Does an AI Researcher Do?

Posted on by Imarticus Learning

Last Updated on 5 years ago by Imarticus Learning

Developments in the AI Industry

The fourth phase of the industrial revolution is all about automation and artificial intelligence which is powered by data science to a great extent. The need to reduce the chances of human error and automate repetitive mundane tasks has been paramount. We are moving to a stage where human inputs are needed only in critical situations and machines are handed over the responsibility to carry out day to day operations.

Even the AI is evolving on a continuous basis, making the machines able to carry out fairly complex tasks as compared to their traditional use in repetitive functions. Autonomous driving vehicles are the talk of the town; this indicated the degree to which the AI has penetrated human lives and the way of living. The

AI with machine learning algorithms made its presence felt across various industries including healthcare, education, e-commerce, finance, etc. From robot advisors to customized product recommendations it has directly or indirectly influenced the lives of masses and will aggressively continue to do so in the coming future.

The role of an AI Researcher

The role of a researcher in any field is more focused on gathering information and discovering new aspects of the field, it’s more concentrated towards exploring and discovering the unknowns of a subject matter. According to computer science, AI research has been established as the study of intelligent agents, intelligent agents here are described as machines or devices that comprehend its surroundings and act accordingly after analyzing all the variables that increase its chances of achieving set goals successfully.

The role of an AI researcher incorporates multiple things; it requires people to work on problems related to machine learning technology. In a brief sense, you have to identify a problem in your domain, get relevant information regarding the problem through research reports and other sources, understand the maths and prepare the algorithm that gives you a sense of the real problem in coding terms. After this, you’ll need to experiment and test the algorithms on various data sets, adjust with the results obtained from the experiment and finally write your research report based on your findings of the problem.

People working as AI researcher have a thorough understanding of the fundamentals of this technology and they apply this understanding to develop algorithms to solve a problem, these algorithms are then tested on multiple data sets before coming to a general conclusion. The day to day task for an AI researcher includes algorithm building, natural language processing, building data sorting, and organizing mechanisms. AI researchers also have an in-depth understanding of multiple computer programming languages that helps them to do their task with relative ease.

A large number of AI specialists work in areas of applied AI where they program computer smart systems. These systems are used with progressive gadgets that help to perform tasks like voice recognition, facial recognition, and other complex assessments. The AI research scientists are responsible for designing, undertaking and analyzing relevant data and information.

Conclusion

The work of an AI researcher broadly includes engaging in behaviors to solve real-life challenges. While identifying the problem it is also important to identify the bias attached to it and to exploit the bias in the AIs to learn some important aspects of it.

The learning and insights are further applied to real-world data samples to make an observation and then modify accordingly as per the evolving nature. The three important aspects of it are to design an intelligent system to solve real-life problems, to understand the fundamental properties and know the limits of the system and to imitate the natural intelligence found in humans and animals into man-made machines.

How Does Digital Transformation Help Fix Skill Gap?

Posted on by Imarticus Learning

Last Updated on 6 years ago by Imarticus Learning

“If your business is not on the internet, then your business will be out of business”

                                                                                                                         -Bill Gates

The past decade has been all about digitization, no matter what industry you are in you need the digital presence to address the audience of the new era. With growing internet penetration and affordability of smartphones, the digital world has seen a huge surge.

From cutting down your marketing expenditure to reaching customers all across the globe, the digital world has a lot to offer. From banking to retail commerce every industry has been influenced by the digital buzz and customers have been blessed with improved services and higher convenience. Now, this whole transformation requires the workforce to have the required skills for staying competitive in the game.

Let’s dive deeper into the digital skill gap that persists in the contemporary.

Understanding the digital skill gap

What exactly is the digital skill gap? To have a comprehensive understanding of the whole situation it is important to get the context here. All this exponential growth in the digital space is powered by tons and tons of data that has been collectively given the name of the Big Data. Whether it is a personalized recommendation in e-commerce space or contextual banking in finance, everything is backed by a massive amount of data. Naturally, with the surge in the digital space, data has taken a front row and the jobs in the data science and tech industry have been exponentially growing.

The demand for labor in the data industry has not been matched by the labor supply, the skills required to do the job is still lagging behind in the workforce. This has created a scenario of the digital skill gap. The future is all about AI and advanced technology, this requires the workforce to upgrade their skills to contribute to the digital transformation. If a business has to succeed in the era of this digital buzz, they need to plan a robust digital transformation strategy.

Bridging the skill gap

Now that we have an understanding of the digital skill gap challenge, let’s see how we should plan to bridge this digital skill gap that is hampering the growth of various organizations. The most prominent challenge is finding professionals who understand both the technical and business aspect of the organization.  It is crucial for organizations to link the training of their employees with the long term digital strategy of the organization. On the employee’s part, they should be aware of their strength and weaknesses in the digital arena and should up-skill themselves accordingly.

Learning the art of managing data is a must-have skill in the contemporary scenario. Employers should train the employees to be able to extract and analyze data because every industry is running on data in the digital sphere. One of the most important aspects of bridging the skill gap in the digital world is planning ahead for future requirements based on factual evidence and data.

Given the dynamic nature of the digital world, there is a constant need for businesses to train and hire new people with relevant skillset. Instead of hiring new talent or spending a huge amount of money on training programs Businesses can rely on contractual workers and freelancers who are equipped with the relevant skillset to perform the task. Given the paucity of skilled professionals in the digital arena, corporations can lure in the right talent through a good remuneration package and incentive.

Conclusion: 

The digital world has totally changed the game for businesses and workers. Corporations are facing the challenge of the digital skill gap and are missing out on the opportunity that the digital world has to offer. A robust digital workforce planning is a must-have to survive in the digital space, looking out of the usual pool to find relevant talent is a good option for the dynamic digital space.

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