If you know how to use it, big data could be the key to even a small business's success.
Big data for business offers an evolution of management and marketing tools as a reflection of technological advancements. It is also a consequence of our times when just looking at a small set of historical results no longer gives you a competitive advantage. We need to think dynamically.
A widely found misconception is that big data is only suitable for specific activity sectors or best used by large organizations. Small and midsize business owners are usually intimidated by data science, although their businesses also generate enough information to get actionable insights. Through education and real-life examples, this unjustified fear can be eluded.
The areas where data science can have a significant impact on business include planning, automating processes, performing market research and scouting talent.
When you make a strategic business move, you need to have proper reasoning and motivation behind your actions. Also, to seize opportunities, you can't afford to wait months for regular business evaluations. Data science gives business owners a way to make decisions while hedging risks.
Tools for success
By combining internal and external data, it is possible to validate decisions. Even if your company is too small to create a relevant inflow of data, you can use freely available databases with information from the same industry or from governmental institutions. Just having data is not enough; it needs to be in an easy-to-use format, like a dashboard.
Use the reports you generate to set new performance metrics. Give people access to data and reports, and even use gamification techniques to motivate them to reach their goals.
Most companies regularly waste their employees' time on repetitive tasks and could benefit from simplification by automation. A mixed team of project managers and data scientists could identify the parts that should be performed by machines instead of humans.
The benefits of this approach could be seen in diverse areas, from document processing to decision-making. For example, AI-powered text processing can handle some of the duties of an assistant manager and summarize, sort, classify, and retrieve documents and conversations. Other deep-learning algorithms can be trained to match the skills of expert evaluators. These steps don't mean replacing staff with computers, just giving people back some time to use more creatively.
Big data and marketing research are a match made in statistical heaven. The combination can uncover patterns about client profiles, their preferences, the efficiency of advertising methods and even projected ROI for each marketing channel.
Mass products are no longer a viable model. Personalization is in demand, and the only reasonable way to know what people want is to use lots of data. There are free tools like Google Analytics that offer in-depth insights of your customers and create profiles. By looking carefully at the data, you can identify new niches to target.
Before big data, there were focus groups and surveys, which were highly biased because they could only include a few participants. Now, every commercial, webpage or social media advertising post can be tested for relevance with thousands of users. A/B testing shows what people like and what makes them engage with the company.
The same logic that goes into finding your ideal client applies to getting excellent staff. First, you need to understand what motivates and engages your perfect worker. This is similar to understanding your client's motivations. Next, the machine-learning algorithm can be trained to identify success factors for people in similar positions. Once these are distilled, the real search work will begin.
Modern tools can merge online profiles from different platforms, not just the professional ones like LinkedIn. An HR staff member evaluates the potential candidate from a much broader perspective, including their ability to work in a team, personality and stress resistance. At the very least, the preliminary stages of this process will soon be automated. Weeks of sorting through resumes will turn into just a few hours of interviews with qualified, short-listed candidates.
A new religion
More than half a century ago, W. Edwards Deming, the driving force behind the lean movement, jokingly said, "In God we trust; all others bring data." This idea is more vivid now than ever. Data has become a currency, a way of doing business, and the foundation for sound and hedged decision-making. Yet, data by itself is only a tool, a solution. To make data speak its truth, a management team needs to ask the right questions. The same set of numbers can give the answers to very different problems.