When your start-up experiences its first big growth spurt, it can feel like you’re working harder than ever to keep up. But the key to scaling up, argues Sang Won Hwang, is to work smarter and use data science.
It’s become one of the most in-demand functions in business and has already been hailed by Harvard as the “sexiest job of the 21st century”. But while large companies continue to ramp up big data efforts, the role of data scientists in helping start-ups become scale-ups is still not being grasped by many fledgling businesses.
At Enshored, we work with companies ranging from start-ups to tech giants, and they are all grappling with the same challenge: managing volume and workforce planning. This is where the analytical expertise of data scientists can be the difference between success and failure.
Supporting human teams
One of our clients, for example, is a social media networking service that manages millions of videos every day. The volume of content streaming in can be very unpredictable and it’s difficult to know how many content moderators you will need at any given time. That’s why we use data science to do predictive modelling through machine learning in order to manage peaks and identify harmful content.
The use of data science not only provides much deeper insights and allows us to see the context the business operates in. It also enables us to scale from ten people to a thousand with very little cost. It perfectly encapsulates the ‘work smarter, not harder’ motto.
This is just one of many areas where data science can help businesses tackle problems at scale. And with the big data market predicted to reach $103Billion by 2027, its influence in the workplace is only going to continue to grow.
Helping drive productivity in remote teams
In a post-pandemic world, we’re likely to see more and more staff working from home. Because of this, data science is being used to help better understand and monitor productivity. With enough data and machine learning, companies can predict productivity levels and anticipate when staff will go through a dip and prepare accordingly. Data science can tell employers when a member of staff’s productivity is going down through dashboards that measure work output and recommend that they intervene with training, pastoral care or other support.
This also works particularly well with companies that are outsourcing and don’t have visibility of their team. In these circumstances, a company can lose a lot of interpersonal knowledge. Without coffee conversations or water cooler discussions, lots of insight into workers’ wellbeing is lost. That’s where data science can help and keep you in touch with issues at the coalface.
And once companies embrace all the disciplines of data science; data mining, statistics, machine learning, data analytics and programming; they will find multiple uses that can help them grow.
Personalised customer engagement
Delivering compelling customer experiences is key to growth and generates considerable brand loyalty. Businesses that can deliver tailored experiences and products to serve their customers’ needs will quickly gain market share and build trust.
To achieve this, you need to build relevant and insightful data streams and make sure your data captures the question and the problem that you’re trying to solve. Once you have the data, artificial intelligence and machine learning can help you generate rich customer insights to provide a truly tailored offer.
Putting data science at the heart of your business model
The old adage that knowledge is power has never been more important in the business world. When you consider that 95% of businesses cite the need to manage unstructured data as a problem for their business, data science can no longer be seen as something that’s nice to have. It’s an indispensable tool that empowers leaders to make better, more informed decisions.
That’s why we advise clients that they shouldn’t be considering introducing data science as an add on when you start growing. It should be at the heart of your business model from the beginning. Businesses need to be thinking about how they get better data intelligence and improve their data architecture from the outset. Thinking solely about generating revenue and sales just won’t cut it any more. From the beginning of your business journey, entrepreneurs now need to be asking what critical information you need to drive productivity, quality and growth?
Because the world of business is no longer about the survival of the fittest. It’s about survival of the smartest.