At present, an incredible amount of data is available from a myriad of sources. If harnessed correctly, this is a veritable gold mine for businesses across the board.
How does one delve into this data and extract useful information that is actionable and relevant? Here, data science enters the scene.
This new field is an incredible cross-pollination of fields of knowledge, including statistics, mathematics, computer science, data visualization, data mining and information management. Added to this, many data scientists have experience in infrastructure design, cloud computing and data warehousing. As you can see, this is a complex field with experts from many disciplines.
Data science is the torch illuminating a treasure trove of data. Data scientists are the modern-day equivalent to Indiana Jones in the electronic realm of Big Data. This can benefit any company in any industry, regardless of the company’s size, net worth, industry or market.
In this article, we will investigate how data science is useful to businesses and allows them to stay ahead of the pack.
Mitigate Risk and Fraud
When data is unusual in some way, this often indicates that a system or situation poses a risk or threat, or it indicates fraud. With the effective application of data science, these scenarios can be detected immediately, allowing role players to take action in a timely manner. In the case of fraud, predictive fraud propensity models are developed using big data methodologies that include statistics and networks. This peace of mind is essential in today’s digital world where fraud is rife and highly sophisticated.
In the past, new business ventures went hand-in-hand with tremendous risk. Executives relied on gut-feel and had to make decisions in a very shoot-from-the-hip, unscientific manner. The stakes involved were high and mistakes were often made, leading to tremendous losses for businesses.
Nowadays, data scientists would work alongside decision makers in order to inform them of what is pointed out be the data. By analyzing data from past business ventures, marketing strategies, product roll-outs, social media, markets and the like, various scenarios can be modeled and explored. Decisions can be tested on these models, mitigating the risks in new business ventures. Risks and pitfalls can be understood and decisions optimized before taking any action.
Relevant Products & Customer Satisfaction
Knowing when and where which products sell best is key to the success of any business. With data science, advanced algorithms are used to find these patterns, allowing businesses to optimize around prime markets and timelines.
Using historical data and trends will point to where products are generally used and can help companies determine how their product is adding value to their customers’ lives and businesses. Combined with analyses of their competition and other related products and fields, this could point to potential improvements in existing products and services.
This would also enable companies to predict which new products are likely to be successful, leading to development and innovation that is specifically targeted to enhancing customer experience and company profits.
When used correctly, Big Data enables companies to understand their customers on both a collective demographic and individual level. This allows companies to curate marketing packages to individuals, thus enhancing and personalizing customer experiences. Here, you are able to combine certain metrics, such as age, location, stage of life, gender and financial position, among others, to tailor a product or service accurately and specifically for a certain demographic.
When done effectively, this would lead to a boost in sales, increasing profits. As an added benefit, this would allow you to reach individuals in that specific demographic that you did not have access to beforehand. Broadening your reach broadens the efficiency of ad campaigns, which in turn would translate into increased profits.
Exploration of the data at hand may lead to the discovery of new solutions or opportunities that used to seem highly unlikely. Adoption of these potential new strategies could put a business at the forefront of that specific industry. In practice, this could mean completely new products being rolled out or existing products used in a new manner or marketed to a new demographic, among other possibilities.
Enhancing Decision Making & Business Processes
Data science allows performance indicators and the effect of business decisions to be tracked and quantified. This optimizes the in-house learning process and indicates key focus points for staff. When used effectively, data science would enable management to steer a company in the most sustainable and profitable direction and allow staff to buy in to that vision based on quantifiable data.
Now, companies are able to take direct action based on trends backed up by data. This enables the definition of clear, attainable goals, which in turn translates to increased profit.
Change is inevitable. Getting the best possible results out of change is not. Data science can help companies determine what effect each change has on their company in order to optimize future decisions. Again, this allows companies to optimize their internal structures and systems to get the best out of every staff member and business tool in order to stay ahead of the pack.
Data is impartial and if analyzed correctly, will point you to the best possible solution for business. Here, organizational performance will be increased and optimized.
If your staff is well-versed in your analytics tools, they are better able to understand new business ventures and related decisions and will be enabled to make better business decisions themselves. This would lead to increased efficiency on staff-level, freeing up time for employees to focus on key issues and challenges. This has a knock-on effect on other structures in your business. In the long run, your business will be a streamlined, lean machine running at optimum speed and churning out profits and customer satisfaction.
Data science allows you to work smarter, not harder. Efficiency is key, especially in the modern rate race.
Optimized Talent Pool
In order to flourish, a company must attract and employ the right talent. A company’s talent pool often translates directly into a measure of its success. Data science allows you to comb through resumes, social media and other online sources of information on your potential candidates quickly in order to find the right candidate and speed up the hiring process.
It is well known that often, potential candidates look good on paper, but aren’t a good fit for the company for various reasons, ranging from practical issues to work ethic and company culture, among others. Using data science to mine social networks, professional online platforms and recruiting databases would narrow down the search, finding candidates who are statistically the most likely to fit onto your company and the role that you envision for them. This streamlines the recruitment process and often finds the right candidate even before the first interview.
Data science is logical, thus the solutions pointed to through data science are often best-case scenarios that are optimized to offer the desired outcome for a specific business situation. This is also true when is comes to in-house talent development. Data science can be used to determine which fields your employees should know more of or master in order to stay ahead of the game in your specific industry. This would allow you to develop in-house training programs or find the most relevant courses outside the company to best improve your in-house expertise. Now, your talent pool will remain at the cutting edge of developments in your specific field, progressively pushing your company forward.
A Word of Caution
Data is only useful if it is structured, accurate and readily available. It is of the utmost importance to use the correct analytical tools to comb through data in order to unearth the relevant facts. These facts can translate into actionable goals that will allow the business to make headway in a specific industry.
Since most data that is captured is unstructured, advanced predictive analytical tools are often necessary to comb through the data and obtain useful information. A combination of statistics and predictive algorithms are used in order to do this efficiently.
Incomplete or skewed data will lead data scientists to draw inaccurate conclusions. This, in turn, could lead a company completely down the wrong path, having dire or even catastrophic consequences. For this reason, it is imperative that the quality of a set of data be determined before basing decisions on it.
If results obtained from data is not readily available, actions based on a specific set of data could be delayed. In today’s fast paced world, this delay could be catastrophic, since the data set might no longer be relevant.
Data is only useful if it is current, in correctly processed and readily available.
Data is a powerful tool that is essential to staying ahead in the current business environment. Taking the time to understand data in order to properly utilize it will propel your business to the forefront of your specific field. It could also broaden your scope, allowing you to tap into previously unutilized fields. No business can afford to ignore the relevance and importance of data science.