5 reasons Data Science will help your business in post-pandemic

On this blog, we discussed the 4 stages businesses will go through during and after the COVID-19 epidemic and crisis. We saw that most businesses are already through with Change Management and Adaptation as well as Crisis Management. Most companies will now start catching up and innovate to return back to normal.

It’s no surprise if you wonder how Data Science can help you in the next steps, catching up to normal life and mitigating the effects of a new pandemic.

1: Save costs by exploiting your data

Data is the new oil. Understanding where your bottlenecks, sunk costs or hidden values are can lead to big cost saving opportunities for any business. Descriptive and Diagnostic analytics show what happens in your business and why business happens the way it does. We found that customers that don’t exploit their data need to staff more people and execute tasks in sub-optimal order sometimes even at the wrong time. All these inefficiencies and bottlenecks are costs your data can tell you about – if interpreted correctly.

Techniques to use: Data Mining, Process Analytics, Data cleaning and transformation

2: Automate the processes that make sense!

There are always standard processes that can be automated at any company. A reminder email or follow up call, an order to be sent based on some criteria can all be triggered and even fulfilled by a machine. However, we see many cases where companies go too overboard with automation and it causes more trouble than it’s worth. We have seen customers automate tasks that are cheaper and less prone to error if done by humans. Identify processes to automate, and only automate if it makes sense.

Techniques to use: Process Mining and Mapping, Robotic Process Automation (RPA)

3: Understand your customers and audience better

With the rise of social media and the internet, there is a lot of buzz about every product, service and business sector. Some of our customers have complete teams constantly monitoring social media, news, forums and other online platforms. Many of them are even actively gathering customer feedback from their customers. However, questioners can be biased and a person can only check so much online. Gathering and aggregating feedback and the feelings of your target groups automatically is essential to stay on top of your market.

Techniques to use: Social media mining, Sentiment analysis, Natural Language Processing (NLP)

4: Reduce risks

Forecasting and predictive analytics can help show you what the future might hold, giving your business a chance to prepare. The power of a big data lake also lies in testing out some of your decisions and ideas, so that you don’t need to conduct live experiments for each change. A large and well-maintained data lake is going to give you the chance to mitigate risk.

Techniques to use: Forecasting, Simulation, Data Morphing and Mock data generation

5: Make Data-Driven Decisions

Many companies operate on gut feeling. There are tried and true methods from the past or decisions drawn up in the business bubble, but as Harry Beckwith, author of Selling the Invisible: A Field Guide to Modern Marketing and many others point out many times, the real world does not follow your plans. Your data, however, speaks for itself and does show how your customers actually interact with your product and service. Use this data to create new customer groups, to bring out the right product and to make data-driven decisions!

Techniques to use: Data Mining, Feature engineering, Clustering, Classification, Regression, etc.

With Data Science, you unlock the potential to become a data-driven company, cutting operational costs and optimising your business based on real data instead of gut feeling. At COMPUTD we are committed to helping you unlock your potential! If you have any questions, concerns or just want to know what the best solutions are for your organization to return to business as usual and even improve your current operation, don`t hesitate to contact us at info@computd.nl or on our Contact Form.

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