Barrier to Data analytics

Barriers To Effective Business Data Analysis

There has been a meteoric rise in investments in business data analytics initiatives across industries in the recent years. When embarking on such initiatives for your company, it is important to plan for any potential roadblocks that can hamper its smooth implementation and running. To successfully see through it till completion, it is best to understand what these hurdles could be and prepare to combat them in advance. Here, we will walk you through the most commonly found barriers businesses face when implementing data analytics initiatives for the first time within the organisation.

Get the entire organisation on board

Once you have identified a parameter that your company really values which can be improved by implementing data analytics or directly impacts the bottom line, you need to ensure that the company shares the same vision for the business. For a data analytics initiative to be truly successful, data from multiple sources and departments might be required. This might pose a problem for the smooth running of such a project because the different teams might be hesitant to share their data as they may fear that data comparison will fuel competition or blame games.

As a part of the executive board, you can help in such scenarios by being clear about the purpose and the use of data analytics. Once the project is successfully completed, such roadblocks will cease to exist as the various teams and departments of your organisation recognises the value analytics can bring in to the company.

Differentiate between facts, opinions and biases

The purpose of effective analysis is to obtain factual answers to questions or hypotheses that are conclusive. You know a data set is “successful” when anybody who views it can come to the same conclusion as you. An opinion, on the other hand, is subjective. It change depending on the perspectives of the people viewing them and might or might not get unanimous approval. When making the leap from facts to opinions, there is always the possibility that the opinion is erroneous.

Cognitive biases are a normal occurence that can adversely affect the integrity of a data analysis. A common human tendency is the interpretation of information in a way that agrees to their preconceived notions or discrediting of information that does not confirm with their views. Ensure that the analysts who assess the data are specifically trained to be aware of these biases and how to overcome them. It imperative that analysts delineate their assumptions and specify the degree and source of the uncertainty involved in the conclusions.

Embrace the tool

As they say, Old habits die hard, but letting go of old inefficient ways is the first step towards getting started with data analytics in your company. Auditors might find it difficult to inculcate the new data analytics tools and get pulled back to their old ways of Excel sheets and audit plans that don’t use tools. There is always a learning curve for tools and people may show reluctance to learn a new tool that would take away time from their daily tasks, especially when productivity can be questioned. As a person in a leadership position, you need to make sure that all the department heads understand that some amount of their team’s time will have to be set aside to bring them up to speed with the technology and train them with regards to the functionality. There’s no doubt that changing an established but slow plan that has worked for your company in the past is a daunting task, but you have to be willing to do it to ensure data analytics is included as a standard in the company’s day-to-day operations.

Allocate time to learn the tool

It is important to invest in training your company on the chosen data analytics tool. It will require a significant effort and time but will be well worth it when it finally pays off in the long run. Your staff should be brought up to speed not just with the software aspect of the tool, but also how to integrate the tool into their daily operations and functions. Encourage the teams to read up and learn more about the tools and its capabilities.

If in doubt, you can also reach out to organisations that that provide consulting services to get your company going with data analytics. You can receive in-house training and then have a trainer spend time in your office to get you started, help you acquire the necessary data, and use the tool to provide valuable insights.

Take one step at a time

As discussed earlier, remember to encourage your staff to pick up the data analytics tool step by step. Most eager first-timers tend to try and master the tool all in one sitting which can be overwhelming and its repercussion may only backfire. Instead, have them focus on the objectives and business issues the business is attempting to solve with the new tool. By starting with small objectives that align with the business goals that have been identified, it’ll become easier for the teams to familiarise themselves with the tool as they perform their day-to-day tasks. They could begin with easy functionality they already know such as profiling data, summarisation of data, look for duplicate entries, validate data integrity, perform gap analysis, etc.

Remember to focus on the data and the problem it is trying to solve—don’t focus on the tool.

Although your organisation may face many hurdles in the initial stages of integrating a data analytics tool into the fabric of the business, once you’ve followed these suggestions for getting started and have gained momentum, the challenges won’t seem as overwhelming eventually. In the long run, the benefits of data analytics outweigh the cons and are worth the time and resources invested into its learning.