Why Organisation Needs (Citizen) Data Scientists in Every Department

Just a few years back the demand for data scientists was primarily in the finance and tech sectors. Today it’s a different story. From retail to manufacturing, every industry is becoming data-driven and is leveraging data for business success. This shift propels the rise in the demand for data scientists. However, the shortage of data scientists is a chasm that organisations are finding hard to navigate. The LinkedIn Workforce Report shows that there is a shortage of 151,171 people with data science skills overall in the United States alone. This shortage is only going to increase as big data and AI proliferates deeper into the enterprise. As the volume of data increases and the shortage of data scientists continues what can you as an organisation do to leverage data?

Most complicated questions have simple answers. This one does too. If you want a strong team of data scientists but cannot find them, you create them. People in any organisation also have to realise that no matter what their job role is today, tomorrow they will have to become data-driven to facilitate better decision making. But how can organisations become data-driven in the absence of the data scientist? The answer surreptitiously lies in the citizen data scientist. Here’s a look at a few departments in your organisation that can leverage data science.

Human Resources (HR)

Data science can alleviate some of the major challenges faced by HR managers. They have to manage a large number of resumes to fill a single corporate position. They have to manage the demand and supply ratio. HR managers also have to navigate the tenuous relationship between recruitment managers and hiring managers. Improper communication and inaccurate understanding of job roles can make the hiring process bumpy.

If the HR team were to become data-driven, then they would be able to track and analyse employee-related information to gain a deeper insight into the candidate’s profile. The HR data scientist could aggregate data from various resources and channels to accomplish this and avoid bad hiring decisions.

The HR workforce also is under pressure to create several estimates like the investment in the talent pool, cost per hire, cost on training, and cost per employee. How much should they spend and where? Instead of using guesswork, they can easily leverage data science to set accurate estimates for optimising costs, better forecasting, and reporting.

There has also been a shift in employee performance rewards. As performance-based compensations hold ground, how can your HR team ensure that they are rewarding the right candidate? The answer, no surprises here, lies in data again!

Finance

The finance team lends itself perfectly to data science. They are under constant pressure to navigate a complex regulatory landscape, ensure complete security of customer data, enhance risk management capabilities, and enhance cost efficiencies and sustainability. Given the growing volume of data that needs analysis for accurate outcomes, the finance teams need to create their own data scientists who will have the capability to manipulate the data and identify risks. They need to leverage data from multiple sources to predict customer lifetime value, churn, stock market rates, fraud detection, etc.

Marketing

Do you want marketing ROI? Then you need a team of data scientists. Data scientists act as the bridge between insights and customers. Given the growing volume of data and the platforms they generate it, marketers are under increased pressure to leverage this data and use it to improve their marketing tactics. Be it customising marketing experiences, mapping customer personas, and building context into their marketing plans – data science has emerged as the silver bullet that helps marketers to position themselves for success, and develop new approaches to marketing challenges.

Sales

Do you depend on CRM to augment sales? Well, that approach is archaic now. Today’s sales teams need the capability to leverage data assets to organise their opportunities, define their action plan, optimise revenues, drive insights, and gain deeper visibility into the market conditions. It is only when the sales team uses data can they capably understand the demand and supply dynamics and prepare accurate forecasts to drive healthy sales revenues. The data scientist in the sales team also gives you insights on how to improve sales productivity and provides granular insights into performance.

CXO

With an ever-accelerating pace of change, senior decision-makers are grappling with several ‘unknowns’. As organisations move towards becoming data-driven, CXOs too have to jump on the data science bandwagon. They need to have the capability to use data science to drive decision-making and use the intelligence derived from data to chart the growth path of the organisation and innovate new business models. CXOs also have to completely move away from using any form of guesswork when it comes to any organisational decision-making and look at data for fact-based decision-making. Having data science capabilities thus becomes imperative in these senior roles. Also, if an organisation wants to become truly data-driven, they have to have leadership buy-in. How can that be achieved if the leaders themselves are not capable of using and manipulating the data at their disposal for their related activities?

These are just a few departments that can leverage the skills of a data scientist. But all other departments, be it operations, customer success, customer service, etc. need data scientists in their midst to glean intelligent insights from data to optimise their operations and maximise business value from this data. Clearly, what organisations need now is an army of data scientists. And they can only do so if they can convert their existing resources into citizen data scientists. For this, they need an intelligent, easy to use and intuitive data science platform that helps them analyse the sea of data and derive the actionable insights. It is only when organisations create their own breed of citizen data scientists can they open innovation, create compelling products and unlock real business value to make a deep business impact.