Impacts of Data Science on Today’s Corporate Culture
Data science has become a business mainstay…are you using it?
Though the notion of a total integration of data science into business operations may have seemed like a stretch a decade ago, the application of data into both daily and long-term strategic decision making is the gold standard for thriving modern businesses today.
Data science has become an operational mainstay because it has been proven to successfully impact bottom lines. There was a time not too long ago when data science was something performed only as a project — such as annually forecasting sales based on the prior year’s sales. Today, companies that recognize the value of data science have a plan for data harnessing, regular analysis, decision making processes, and rapid implementation. Successful companies are putting analytics to work in nearly every internal department to increase productivity, create and offer products to match customer needs, and more. This shift toward a data-driven organization is impacting the structure and culture of organizations overall.
Today, companies that recognize the value of data science have a plan for data harnessing, regular analysis, decision making processes, and rapid implementation.
Transforming hiring and staffing structure to align with data science goals
Businesses are hiring for data science. Large organizations have been developing their in-house capabilities, starting with a very senior hire, to build out a data science group. There is no denying that the need for business-oriented data experts is skyrocketing, and many seasoned data science practitioners have advanced to senior level strategic roles by being on the forefront of analytics strategy, change management, and data-driven decision making. Businesses are looking to hire (or outsource) data specialists who go beyond the application of statistics, can formulate business strategies, measure results, and agilely implement course corrections as needed. Such professionals and their departments are increasingly being given greater prominence within organizations.
Another trend impacting organizational structure and hiring is the advancement in data processing technology such as maturing big data applications and increasing utilization of unstructured data. There is a larger demand for engineering related skill sets in Analyst or Statistician hires, and as a result, the line is becoming blurred between analytics and technology. Data scientists are becoming fluent within open source software and emerging data environments (i.e., cloud computing) to enable faster and more efficient processing
Businesses are looking to hire (or outsource) data specialists who go beyond the application of statistics, can formulate business strategies, measure results, and agilely implement course corrections as needed.
Data scientists are also becoming instrumental in building the applications which serve up the analytical insights as a result of their combined knowledge of the underlying data and the programming languages that are used to create efficient queries. This shift in technology is increasingly impacting the nature of skills being sought by organizations in its candidates, as well as the departmental alignment of such resources and their capabilities.
Organizations with data science cultures make the most progress
The successful integration of data science into an organization’s DNA begins at the top. There must be full organizational support, a clear vision set by upper management, and transparent expectations for the transition to data-driven management to be effective. With a clear vision defined by the top management team, the organization can stay laser-focused and demonstrate success quickly. Getting everyone on board with the importance of data science is key, especially if it requires diverting budget away from traditionally funded aspects of a business. For example, hiring a data science team might mean hiring fewer people in other parts of an organization, which might make other departments or functions unhappy.
Fostering a culture of data science-backed creativity can encourage a team to think outside of the box. The innovative vision set by the leadership team needs to flow down to the business areas and across the firm. When the organization is operating with such a mindset, data science and technological innovations can make a lasting impact and change how the organization functions. For example, having a well-defined customer segmentation can successfully bring about a positive change in a company’s measurable success with regard to the products developed, regionally offered, and micro-targeted. Similarly, cross-selling based on data-driven predictive models has led companies to major revenue growth. Pricing optimization, improved supply chain efficiency, enriched customer understanding from textual data analysis, and automation of previously manual data processes are further examples of the transformative power of data science.
The successful integration of data science into an organization’s DNA begins at the top.
Innovation is imperative
Organizations have always been faced with the challenge to innovate or die, and that challenge not only persists today but demands an ever-increasingly fluent management approach to keep up with the evolution of customer behavior, new technologies, and the speed of business changes especially among competitors. The adoption of data science to understand, improve upon, and measure the results for all aspects of a business is the way of the future. Organizations must set themselves up for success by adopting the data-driven culture from the top down, and to build up capabilities either in-house or through a network of trusted partners to turn data into actionable strategies starting now.
