Product managers are surely an important part of any organization. That’s because they present and manage the products so that it could be deliverable for both the customers and the stakeholders.
However, it is often asked whether a product manager should hold the knowledge of data science along with the process of monitoring and controlling product development teams.
If you’re working in the product management field, suffice it to say you’ve fallen into a career where upskilling is expected at every turn.
But of all the skills that you can practice to get ahead in the workplace, learning something as technical as data science can make you question if it’s really worth the effort.
To answer this pressing question, we offer a detailed study on whether data science is a mandate for product managers or not.
Likewise, we will also glean some benefits of hiring a data science product manager for any particular project. Let’s get straight into it.
Is Data Science Knowledge Mandatory For Product Managers?
Data science is certainly a mandatory aspect of product management. It’s by no stretch an unrelated field, and on the contrary, can make for a valuable addition to a manager’s toolkit.
Product managers must understand and drive the requirements of any particular business so that it could work as a team without a hitch. Team coordination is surely essential for any successful business.
A data scientist interacts with the engineers to come up with efficient product development. However, there is no way either of these teams can make the product acceptable to the customers.
It means that the production team can make the product; however, to market and convey the information about these products, it’s important to take help from the product managers.
Besides, professional product managers should have adequate knowledge of data science for proper management.
However, there should be no such specialization for the position of product manager. A product manager should be business-oriented and communicative so that the product could be successful among customers.
Data Science Is Not The Major Focus Of Product Managers
The major focus of product managers should be based on business needs. They should question themselves about the entities that will solve customer issues or the entities that will help in the better operation.
To be clear, their primary aim should be conveying accurate product information to stakeholders and the customers for business needs.
Moreover, they should know the delivery challenges or how they can present the product in front of the customers.
Although data science professionals can adequately fulfill a product manager’s role, it is not always mandatory for them to be the same. Their role will be wildly different from that of a data science analyst.
So Should Product Managers Not Have Data Science Knowledge?
No, not at all. Product managers knowing data science is surely an added benefit.
With data science information, they can do their job much better. Besides, it also helps them to come up with more creative ideas for management.
Product managers with data science knowledge are always welcome. However, it is not mandatory. It means that there is no such sole requirement for them to be a data scientist.
Instead, they should be focused on making the product deliverable.
What Are The Benefits Of A Product Manager With Data Science Knowledge?
Now that you know why data science is required for product management, let’s know why a product manager is important for data science.
Provides Data Science Solutions
Customers might often think that the query requires Machine Learning (ML) to get solved, while that’s certainly not the case. Even if it is so, many times, it does not require any complex solution.
Knowing the inner workings of data science can help product managers encourage their clients to reconsider these aspects. They can step in and suggest the right solutions in a way that customers understand.
Use Case Identification
There can be scenarios where the customers would not be able to know the use cases of technologies like MI and AI. In such cases, data science product managers can help as they are well known in the sector.
They also have adequate skills to collaborate with stakeholders with the best product owner certification and the data science team for use case identification.
Apart from that, customers might not have the skill and time for product management. On the other hand, if the team itself does it, there are chances of failing to juggle both the parts.
Thus, in such case scenarios, a data science product manager can step in and use their skills for efficient product management.
Explains Product Knowledge
It is not possible for both the customers as well as the data scientists to explain the product precisely to the customers.
Neither can a customer understand why they should buy that particular product, nor can the data scientists explain them.
Hence, product managers with knowledge of data science can help to make them understand in such cases.
Product Business Needs
In addition to that, managers may happen upon situations where the data science team would not be able to comprehend the business needs of any item.
Thus, in that case, product managers can make the data scientists understand the same in their language. Thus, they are certainly important for different aspects.
Post Launch Model Management
Once any data science product gets launched, it must be managed precisely. That’s because data science products are likely to deviate with the passing time.
While that can’t be maintained by customers or data scientists, product managers can step in and help with the same.
From the above read, we can conclude that it is not mandatory for product managers to specialize in data science. However, there is no issue if they want to do so.
Product managers should be focused on conveying product information to stakeholders and customers. Their way of executing the work can be different, depending on the area where they are working.
So, to answer the question, knowing in data science is an added benefit. However, it is not necessary to have it.