In an age where big data is ubiquitous, what is business data innovation? It is the creation of novel techniques for analyzing data to make business decisions. In fact, the US Securities and Exchange Commission uses such data to identify suspicious filings and facilitate fraud investigations. Wind energy companies use complex weather models to predict the weather, and Intel uses predictive modeling on chip manufacturing data to reduce costs and increase production. With the explosion in data availability, new technologies and applications began to emerge, making this data increasingly valuable.
When a company collects and analyses data, it needs to be classified by capability, market, and value proposition. The data should be collected with innovation intent, not simply for gauging organizational health or budget decisions. Furthermore, it should be paired with organizational value knowledge. Finally, it should be measured to ensure that the new data solutions are successful. To achieve the ultimate goal of business data innovation, it is imperative that the organization creates an environment of continuous innovation, incorporating new ideas and techniques and embedding them in the business process.
A recent survey of 1,250 companies has identified the need for more data-driven decision making. Data-driven decisions allow companies to develop more personalized products. Companies can also make smarter hiring decisions, improve product development, and improve customer engagement. This means that they can better understand their customers’ needs and preferences. With the right data, a company can create products and services that benefit both the customer and the company. But how can data be used to create more personalized and relevant experiences?
