Common Practices in Business Analytics

Common Practices in Business Analytics

Successfully navigating all that comes with running a business is a multifaceted task. So many elements come into play that needs constant management, consideration, and action. Having a solid team around can certainly help, but as the leader, it is essential to understand fundamental business principles to drive things forward. The following post focuses on the importance of business analytics and some commonly associated practices.

What is Business Analytics?

Business analytics is a method of approaching and deciphering statistical data pertaining to a company or corporation. It focuses on a problem-solving technique base and infer resolution through data components, statistics and an exploration of the quantitative side of things. It is a very skill-focussed specific approach that requires a certain level of educative background and business savvy.

Why is Business Analytics Important?

It is a solid, time-tested way to decipher and target problems across a wide number of areas. Businesses need a constant analysis schedule in order to improve, maintain integrity and perform in line with KPIs and set functions. Whether this is outsourced or in-house, analytics is just a standard business practice that should be implemented universally. Proper practices can highlight potential or existing problems within the framework of the company, collect data on how to rectify the issue at hand and provide a strategy to move forward with. Without this agenda, problems lie undetected and fester away in the background ultimately detracting from the overall company efficacy.

How to Implement Successful Business Analytics

To properly incorporate successful analytical practices into any corporation, the process must be approached professionally. This task may be outsourced to external experts, but owing to the ongoing requirements and fulfilments, it may be easier to employ a role within the company. An in-house staff member with the role of business analytics can stay up to date with trends, focus on solely one business, and be scheduled as and when required.

If you are looking to expand your personal knowledge base and absorb this type of practice you’re your leadership skill portfolios, a course such as a MSC business analytics from Aston University is a smart move. Courses such as these set out all necessary skillsets and developments that adhere to growth, problem solving, and resolution focussed approaches all necessary for determining the success of a business. There is always value in acquiring key skills while holding a leadership position.

The Practice Methods

The following points for consideration are common practice methods amongst business analytics professionals. This is a multi-step process that allows for exploration at each step of the way. Each loop ties into the next and creates a full circle approach to modifying and engaging with issues in real time circumstances.

The Methodology

Generally speaking, there are three main types of analytics that are widely practiced in this field. These are:


This model moves with a focus on past practices within the company’s existing data. By observing historical interactions, transactions, misgivings and successes, a model is generated for any future occurrences that may be similar in nature. Where something worked successfully,it is brought forward. Where something crashed and burned,it is forgotten about entirely and scrapped.


This method observes current market trends, data and projections in order to line up practices with what is relevant and try to foresee future actions and engagement. Through predictive analytics the success rate is not as high as other methods as despite data being predictable and coherent, there are always external factors that can influence influx and unexpected change.


This is a real-time method that concentrates on actual business outputs that are in current circulation. This data is gathered from what is happening in the moment based on KPI regulations and outputs alongside other factors.

Identifying and Highlighting Problem Areas

This first key stage is the part of the process that allows for any current issues to come to light from assessing where the business currently stands. This encompasses factors such as profit drops, budget overspends, staff productivity, customer engagement, marketing strategy success rates and effectiveness of leadership. With a descriptive analytics model this would take a plunge into current business trends and look at issues as they are playing out across the board.

With a predictive model, considerations would be placed on what could happen as a result of a strategy and how to curb the negative potentials into something more positive. With a prescriptive method, data from past practices is put forward into current practices and observed in line with what went wrong and what could be improved upon. If something went wrong in the past and is still going wrong currently, it is time to make a change with data to support it.

Finding Related Data

After problems have been established and brought to life, the next step is to provide data relating to solutions and actions. This can be through customer observations such as tracking engagement habits, reviews, and interactions on customer service platforms. It can also be from incorporating past data trends and applying them to current circumstances. Any data that provides insight and leads onto a solution is useful data and should not be dismissed.

Brainstorming Potential Solutions

This data focussed approach can lead to solutions to fix current issues. Think of it like a scientific experiment. There is a hypothesis, a research method, a testing phase, and a solution agreement. This stage is there in order to put ideas on the table as to how to move forward. All problems have more than one answer, and this is about finding the one that is the best fit. Statistical reviews can provide a deeper insight into what might work and what would be less effective.

Selecting and Implementing Solution-Focused Practices

Lastly, once all previous steps have been completed, it is time to implement the findings. Putting into practice what has been learnt and assessed should be the easy bit. The work has already been done, the solutions have been found it is just about pressing the big green button and watching the cogs start turning. If the chosen method yields ineffective, there is always the option to regroup and select a different method set out at the brainstorming stage of the process. That is what this stage is for – though the expert will more times than not understand the best solution to put into practice and thus avoiding the need to go back and start again.

Common Problems Faced by Business Analysts

Though it may all sound straightforward, there are some common roadblocks that analysts face in this line of work. These include:

Inefficient Quality of Data

The quality of data is determined by factors such as client representation, timing and market trends, and demographic circumstances. If the collected set is from a niche group of people who, for example, provided faulty or fake information, the data is therefore redundant. If, at the time of sampling, the current economic focus was drastically different to current times, the data will not be a true reflection and that should be reflected in its usage.

Inefficient Quantity of Data

Sometimes there is also a lack of quantity. This means not enough data with regards to the required demographic has been collected in the past or the present and therefore, the results cannot be properly determined or planned for.

External Circumstances

External circumstances are things like employee deaths, workplace accidents, economic crashes, and natural disasters. Essentially, anything outside of the four walls of the company that can negatively (or positively) impact the workplace trends cannot always be accounted for in the data and analytics. As these things are so unpredictable and random there is little to no point planning for them with regards to this remit. Therefore, though relevant, it should be left out of current trends and planned for elsewhere.

Lack of Space to Store Necessary Data

Data storage needs to be confidential and protected. There are always external storage options if you outsource to the right model, but a lack of in-house storage can be a major roadblock in this line of work. If there is nowhere for the data to go, this needs to be resolved rapidly.

A Skill Deficit in Selected Analysis Professional

Sometimes, it is tempting to go with an internal candidate to sort through these business needs. This can yield positive results, but it can also be counterproductive. Despite internal candidates having prior knowledge and insight into the inner workings of the company, they may not have the necessary skillsets required for thoughtful analysis of current trends. That means results could be varied and incomplete, whereas a professional with expertise in this area would encompass a whole strategy more rapidly without missing out on basic elements and making costly simple mistakes.

By now it should be obvious that business analytics is a useful resource for any company looking to move forward in its practices. There is much to be gained from proper insightful knowledge into the inner workings and external impact a company has, and this is best executed through a professional channel.

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