Why the middle market needs big data

Big data, Artificial Intelligence (AI), the Internet of Things (IoT) and 5G are transforming the business world. By embracing these technologies, organizations across the globe are realizing untapped potential in efficiency, customer experience, talent and profitability, and have been able to make better, more streamlined mergers and acquisitions. However, companies must also address the risks. We look at the transformative nature of big data from three perspectives: the benefits, the effects on our workforce and the inherent risks of information security and technology.

Harnessing transformative big data technologies
By embracing big data, companies can improve their business models and tap into its benefits to assist in the buying or selling of companies. Here are some ways intelligent technologies are enabling competitive advantages:

Improved business intelligence: Big data allows companies to compile millions of pieces of raw data that is then distilled into useful information for predictive, modeling or scenario analyses. This gives companies unprecedented visibility and insights into work streams, capital cycles, customer behavioral patterns and more, helping companies improve both planning and forecasting models. They can know when and how much to produce, allowing companies to reduce inventory costs and consider future headwinds that may impact their bottom line.

Big data also helps companies make more informed business decisions, especially when it comes to potentially buying other companies or selling your own. From a due diligence perspective, analytics can help potential buyers identify issues more quickly, which can help buyers and sellers close and integrate deals faster.

According to 2016 EY research, 46 percent of private equity executives believe the availability of sufficient granular data is the most important factor in keeping them in an acquisition process. Forty-four percent believe that a lack of confidence in information is the most significant factor that causes a PE firm to reduce its offer or walk away from a deal.

Advanced AI: By improving big data, AI has become even more advanced in its decision-making capabilities. With more data, an AI app can perform complex tasks and achieve more accurate outcomes. Additionally, with 5G, companies can handle massive data volumes from remote or mobile locations. The ability to capture data from remote sensors, transfer it to large data centers and apply it to both AI and machine learning provides companies with new opportunities. For example, the auto industry is fast on its way to introducing autonomous vehicles to the public through these advancements in AI.

Enhanced customer experience: Big data can help companies better serve their customers using insights gleaned from the customer’s actual actions and preferences. Big data has not only helped make customer service more proactive, it’s also allowed companies across various industries to make responsive products and services. In healthcare, customer-enhanced experiences could improve the health of a population by predicting potential health problems and organizing early medical interventions, such as a local flu outbreak. With information collected from big data, companies can design products focused on the needs of customers in new and unimagined ways.

In an M&A transaction, big data can also provide valuable insights into existing or potential customers. For example, in a retail deal, big data can reveal how customers are segmented, what they’re buying, when they’re buying and the influences on that buying behavior. Buyers can use that information to compare it to their own customer base to identify synergies and areas to complement.

Big data and the workforce
The emergence of big data has also opened doors for new talent opportunities and created a huge demand for a skilled workforce. Companies, governments and universities are working together to help prepare the workforce with the knowledge and skills needed to tackle today’s biggest challenges. Here’s how big data has already affected workforce needs:

Demand for skilled talent: While some skeptics of big data believe intelligent technology will eliminate jobs, others argue it creates new jobs for skilled workers. As big data and AI grow, data scientists and big data experts have become the most highly coveted workers in the IT field. Low unemployment rates and a strong economy create challenges for companies to win top skilled talent for these roles. As a result, some companies are turning to non-traditional sources to find talent. Instead of recruiting from universities, companies like Catalytic are finding their workforce directly from code academies or apprenticeship programs through city colleges. Others are paying for current employees to advance their education in these fields. Some even consider it more beneficial to earn advanced degrees in data science, than MBAs, given the heightened need for talent in this area.

Big data benefits HR: By embracing big data’s predictive and analytical nature, HR departments can make more informed decisions about recruiting, making better choices for the company. For example, employers can use big data determine where to distribute resources and find employees with relevant skill sets. It can also influence existing staff by learning factors that increase and decrease productivity.

Potential big data pitfalls
While big data is vast and carries significant benefits, companies should carefully consider certain challenges as they incorporate big data into their competitive strategy:

Cybersecurity risks: Compiling large quantities of customer data – particularly sensitive information – puts companies at a heightened risk for cyberattacks, which can damage consumer trust and mitigate data advantages. It has also come under scrutiny from the government, which is enacting new regulations for handling and storing customer data. According to a 2018 AtScale survey, respondents consistently listed security as one of the top challenges of big data, and in the NewVantage report, executives ranked cybersecurity breaches as the single greatest threat their companies face. Before embracing big data, companies must fully understand and enable systems to protect their customer’s privacy and comply with government regulations.

Change management: As big data is applied throughout an organization, companies must create a data-driven culture. With this new, fluid data stream, organizations will need to develop an approach to handle the influx of real-time information. This will affect work culture and may require restructuring, which takes time, money and manpower. For middle-market companies that have recently merged, this creates an extra layer of complexity to the change management structure.

According to the NewVantage survey, only 32.4 percent of companies were successful at creating data-driven cultures. Under the helm of CEO Dawn Zier, Nutrisystem was able to turn the company around by insisting every business decision be made through a data-driven lens. This cultural change helped the company increase its revenue from $367 million to $691 million and increase its operating income sevenfold in just six years.

It’s clear big data and other intelligent technologies offer significant benefits, including competitive agility and consumer satisfaction, but companies must be mindful of potential challenges. To compete in today’s data-driven business landscape, companies must embrace new technologies to stay ahead of the pack, while actively preparing for the risks. These technologies have the potential to change the way you do business and, when used together, become truly transformational for your company and customers.

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