Role of Data Science in strategy and decision-making process

In today’s digital landscape, businesses generate different kinds of data every day. However, the volume of data is so vast that it is manually impossible to collect and analyse it. This is where data science comes into the picture. Data science uses complex algorithms, technology tools and statistical techniques to convert raw data into meaningful information to act upon. It incorporates the elements of big data, machine learning, artificial intelligence and predictive analytics to "understand and analyse actual phenomena" with data.

An increasing number of organisations have realised that data science can be a powerful enabler to uncover useful business insights and gain a competitive advantage in the market. It has evolved as an important digital asset for organisations.

Let’s take a look at how data science is disrupting the business models across different sectors.

Strategy

It is said that a strategy is akin to a battle plan. A poorly thought and executed strategy can lead to losses or failures. Organisations have to formulate operational, financial, marketing, human capital and various other business strategies to accomplish their vision. In most cases, a strategy is governed by future business goals and profits. There is hardly any conscious effort to understand whether the said business goals will actually deliver the expected value. At the time of making a strategy, an organisation needs to question the what, why and how of business motivation and actions on a deeper basis. In the lack of proper and accurate data, this type of reasoning takes a backseat.

Data science can be very useful to answer these questions and design a data-driven strategy. It can help organisations to perform a SWOT analysis, identify risks and opportunities as well as evaluate past and future trends to arrive at a robust, effective strategy. It can help organisations notice patterns that they might have never noticed earlier. It also pushes the organisations to think out of the box, get out of their comfort zone and develop a culture of innovation and experimentation because risks have been already mitigated or eliminated.

Data science provides the much-needed business intelligence that is crucial to achieving desired business outcomes at optimal risk-return trade-off.

Decision making

Whenever it comes to decision making in the business, the elements of gut instincts and human biases are deeply rooted. When the decision fails, it starts the blame game with no one to take accountability and responsibility in the organisations. A lot of time and money is spent identifying the root-cause and resolution of why the decision did not yield the expected results. This further translates into loss of money and productivity for the organisation.

Data science empowers the organisation to take decisions based on quantifiable and data-driven evidence. It rules out decision traps such as human biases, judgement errors, ego conflicts, over confidence, status quo, overlooking different angles to look at a problem, faulty perceptions, misperceptions, over optimism and prudence. Data science can turn data into perceptive information and recommendations. Not only this, data science can also increase the accuracy of the decisions because it is based on logical facts and figures.

Another way data science aids in better decision making is through speed. Today’s organisations operated in a highly dynamic, volatile, uncertain and complex market. Agility, flexibility and adaptability have become crucial parameters to respond to a situation proactively. This means that some decisions need to be taken quickly in real-time to make the most of the business opportunity effectively. Data science can do that for business. Right from understanding customer behaviour and personalising customer experiences to keeping up to date view of financial transactions and engaging employees to seamless supply chain management, data science can be highly instrumental in strategic decision making.

Typically, data science can disrupt strategy and decision making in four ways – descriptive analytics (what happened), diagnostics analytics (why something happened), predictive analytics (what is likely to happen) and prescriptive analytics (what action to take). In a nutshell, data science takes the complete picture into account to make a data-centric business impact.

Rising demand

Given that data science can be a game changer in the market, there is a high demand for data scientists in various sectors such as manufacturing, financial services, health care, information technology, telecom, retail, education and many others. Organisations are looking for professionals who have deep technical skills to provide an analytical business outlook and deliver data-intensive business outcomes.

There are ample rewarding opportunities for data science professionals to advance their career. If you are looking for a career in data science, it is recommended to pursue a master’s degree programme in IT business management from a reputed B-school.

(The author is with Symbiosis Centre for Information Technology)