Myths About Data Analytics in Manufacturing Companies
Data Digital Transformation

5 Myths About Data Analytics That Manufacturing Companies Must Not Believe

As Industry 4.0 gains momentum, it is imperative for manufacturers to adopt modern technologies for enhanced connectivity and better data-driven decision-making. This also means more efficiency in manufacturing, production, and revenue generation. 

But adapting to the changing ecosystem with the help of data analytics can be overwhelming for manufacturing companies, in the absence of any strategic planning. Due to preconceived inhibitions and lack of information, misinformation is abundant, which could slow down your upgrade to newer solutions.

Busting 5 Myths About Data Analytics for Manufacturing Companies

To demystify the implementation of data analytics to make informed decisions, we are busting five common myths about data analytics that manufacturing companies should be aware of.

Myth 1: All Machine Generated Data is Good Data

There are plenty of similar myths rooting from this extreme trust in machines, like – algorithms can never go wrong, machine-made decisions are not biased, more data is always good, etc. 

Actionable data analytics entails removing noise from the required signal. It is important to remember that all machine-generated data is not good data, and a lot depends on the cleansing of data and implementation strategy. The data should be timely and representative – irrespective of its volume. 

Even machine-made decisions can sometimes reinforce the prejudices already present in the system. Algorithms are also not fail-safe and can have certain glitches despite their rigorous initial testing. This is why human intervention for data cleansing and better interpretation is crucial to informed decision-making.

Myth 2: Data Analytics Means Hiring Data Scientists and an IT Team

Until a few years ago, companies needed a team of top data scientists to build data analytics solutions. With the onset of further technical improvements, now you can simply begin with three simple considerations. 

    1. Set your data analytics expectations based on the existing data quality and workforce.
    2. Expertise matters, but even the citizen data scientists (as coined by Gartner) with data analytics understanding and easy-to-use tools can implement the machine learning technology without being formally trained data scientists. 
  1. Provide high-quality, clean data to your team for fueling their efforts.

Having said that, it is also important that everyone on the team is data literate and understands the relevance and importance of data-driven decision-making. Companies can even encourage their existing staff to earn data certification for better knowledge.

Myth 3: Soon We Will Need Massive Budgets

Before implementing any solution, the first question is “how much will it cost?” Based on the return expectations, the final choice is made. The purpose of implementing a solution like data analytics is to get tangible benefits, i.e., directly see its impact on the revenue and profits. So, if manufacturing companies are convinced that data analytics is very expensive, they will not go ahead with the investment at all.

In reality, not all aspects of data analytics require major investment beforehand. Companies can handpick the solutions that they need, as per their expense limit. In the long run, data analytics can help a company generate user-centric data that facilitates data-driven decision-making, thus maximizing the ROI. Even the cost of collecting data, data storage, and using data analytics software has come down in recent years.

Additionally, manufacturing companies can make smarter business decisions with the help of data analytics, cutting down on several avoidable expenses. By embracing modern, cloud-based data analytics solutions, companies can save more in comparison to the expenditure on traditional infrastructure.

Myth 4: Data Analytics Can Improve Every Aspect of the Business

With adequate budget and tools, data analytics can solve your business problems – this is one of the biggest myths around the subject. There are certain aspects of a manufacturing business where data analytics can be very effective whereas, in some domains, it can be lacking. To analyze the production, market demands, customer preference, and financial data, data analytics can be extremely helpful.

Should you cancel a struggling product? Is a new law going to impact your business? Data analytics can only help you find the trends around these topics but will never give you a consolidated answer. A focused approach to solving different business complications, alongside appropriate interpretation of data is the best way to utilize data analytics, only in those aspects where it is truly beneficial.

Myth 5: Only Digital Companies Truly Benefit from Data Analytics

There is no such thing as only online companies. Today, every company is a tech company. There is an element of truth here that large tech companies can make the best out of data analytics like we have seen Google and Facebook do. But data analytics can be the key component of all processes in a manufacturing company as well. Through the metrics of data analytics, companies can improve their products and understand what works and what doesn’t. Data analytics can be equally beneficial for small manufacturing companies with smaller volumes of data, as the quality of data matters, not the quantity.

Another widespread data analytics myth, apart from the above-mentioned, is that AI-powered data analytics can cause job losses by eliminating the requirement for a human workforce. The truth is that employees should stop looking at AI as their competition and perceive it to be a support system for better functioning. 

With the help of augmented intelligence, time-intensive and repetitive tasks can be streamlined very easily. And once the machine has filtered out the required data, it is all upon the human interpretation to draw an action plan. Cloud-based solutions are also highly secure and safeguarded, in contrast to the common myth.

Data is the Way

Data-driven manufacturing is the future of this industry that can unify both external and internal data. As this data evolves with time, manufacturing companies can use data analytics tools to improve their efficiency and productivity. Once a manufacturing company is convinced that data is the way forward, they can scale up their business with reliable digital growth catalysts like Heptagon.

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