Each year companies generate exponentially increasing amounts of data and it is critical to obtain useful information from that data. The business information thus obtained may be from corporate databases, external sources or internal systems, which needs to be organized or structured for effective use. Business intelligence incorporates data analysis and data mining, both of which are vital with regard to customer relationship management or CRM. Voluminous data must be searched and analyzed to identify useful patterns or relationships, and this information is used to predict future behaviour. Most successful businesses utilize data entry outsourcing services to ensure timely and efficient data mining. Data mining is the process of extracting the data, evaluating it in detail from various perspectives, and then summarizing it, highlighting the relationships within the data. The summary can be descriptive (providing information about existing data) or predictive (providing forecasts on the basis of the existing data). The data mined helps managers at all levels to extract and scrutinize information about their company such as its products, operations and the buying behaviour of customers.
But today companies across various industries have a new approach called “data storytelling” for quick day-to-day decision making and to increase business value. This involves logical reasoning to arrive at sensible deductions. Businesses now increasingly analyze and quantify their key data points including sensors, websites and sales to drive business growth. This change has renewed focus on data scientists, their skills and role within a company. Statistical Analysis and Data Mining is listed as the number two skill among the “hot professional skills” in 2016, by the leading business social network LinkedIn. Moreover, studies show that the demand for data scientists has almost tripled over the past five years.
It is evident therefore that businesses need to promote a data-driven, investigative and methodical culture within the organization. For this, the best method is to work to develop data skills in all employees and provide them with all the tools necessary to analyze data. So what are the ways in which the desired change can be brought about?
- Encouraging the data analytics culture: Encouraging a successful analytics culture involves trusting your workforce to study the data, form their own questions and find the right answers. This will breed a strong sense of involvement and commitment in the workforce and help to enhance their productivity. When data analytics is entrusted to your workforce, you are empowering them. Make sure that you provide them with the right analytics tools, appropriate training to use the tools and proper data access.
- Human resources training: Training may include software training through the use of the actual software system, via online videos, case studies etc. Any training must have a clear focus on features and functionality. The training should also ideally emphasize critical thinking and analytical interest. A strong foundation should also be given in applicable fields such as data visualization.
- Adapting to a new work culture: Many organizations may not find it easy to accept the new changes but working as a team will surely help. The management team can lead the way by using data to communicate how the business is functioning. They can also pass on information regarding how business data informs management decisions.
- Encouraging data literacy at all levels: Data literacy should be encouraged at all levels. Ask for data-driven reports and answers from your employees. Have them support their answers with data that has been analyzed and authenticated.
- Hiring data literate professionals: Building an analytic culture with existing employees alone may not be enough. So it would be a good option to hire data literate staff with previous experience in data analytics. They should also have a sense of curiosity and desire to analyse the data efficiently.
Fostering an analytic culture will definitely take time, effort, investment and resources. You must have in place the appropriate technology, and provide the right training for your employees. Data must become the foundation of all communications and interactions to ensure a data-driven analytic culture. Meanwhile, businesses can also merit from external support services such as data cleansing outsourcing, data mining, and data conversion outsourcing among others.