Digital transformation

Digital transformation  is the integration of digital technology into all areas of a business, fundamentally changing the way it operates and delivers value to its customers . It also involves a cultural change that requires organizations to constantly challenge the status quo, experiment and become comfortable with failure.

Digital transformation  can involve reworking products, processes and strategies  within the organization by leveraging digital technology.

As such, digital transformation requires an examination and reinvention of most, if not all, areas within an organization , its supply chain and workflow, the skills of its employees as well as board-level discussion processes. management, interactions with customers and their value to stakeholders.

Digital transformation helps an organization keep pace with emerging customer demands, sustaining them into the future . Digital transformation allows organizations to better compete in an economic environment that is constantly changing as technology evolves. To that end, digital transformation is necessary for any business, nonprofit, or institution looking to survive into the future.

How data can drive digital transformation

The Internet of Things (IoT) makes it possible for us to have smart homes, smart factories and smart cities.   Autonomous vehicles are starting to change the transportation industry. Artificial intelligence and machine learning enable predictive approaches to decision making and drive business insight.

This digital transformation that is sweeping industries by surprise would not be possible without data. Data is the enabler of new technologies and solutions. Data is where important, actionable business insights are derived. However, most executives and decision makers are concerned about the quality of the data on which their solutions and insights depend. Many companies and decision makers do not understand what constitutes quality information and how it can be obtained, generated, collected and used.

Data, or more specifically,  quality data, is the critical differentiator that drives digital transformation and what constitutes quality information.

1-Data optimizes sales channels

The potential to reach new customers is a critical factor in the adoption of digitalization. But digitization of sales channels or digital transformation is simply a response to changing customer preferences. For example, the widespread use of smartphones and faster internet speeds have changed the way consumers buy products and use services . Companies needed to respond by transforming their sales channels and adding e-commerce websites and mobile apps to their traditional channels, such as brick-and-mortar stores.

Data is key to understanding customers and their preferences.  Structured data, such as that which comes from CRM systems, helps organizations generate information about their customers based on their past purchases and historical transactions. Organizations can also collect unstructured customer data from social media and listen to what their customers want through their online posts, comments, and sentiments. This greater understanding allows organizations to optimize their sales channel strategies to fit the needs and preferences of their customers.

Additionally,  customer data helps organizations tailor their sales channels for more personalized services and engagements . For example, a customer’s purchase history allows an organization to give that customer some personalized recommendations based on their past actions, thereby maximizing cross-sell and upsell opportunities.

2-Data drives innovation and revenue

Another key to the adoption of digitalization is product and revenue innovation .  Digital transformation allows organizations to create products that customers want instead of creating products and forcing customers to buy them.

Data about when, how, where, and why products are used gives product engineers, designers, and manufacturers insights into how to improve and innovate their products. For example, one company used social listening to understand why its sales were falling. By listening to and analyzing their customers’ unstructured sentiments on Facebook and Twitter, they discovered that a competing product featured new functionality that they lacked. When the structured data in their CRM systems was analyzed, the same reason customers were abandoning the product was revealed. The company responded by adding that same feature to its product and its sales rebounded. To create truly innovative products, companies must analyze data and find the gaps between what customers want and what they and other companies are already offering.

In addition to innovating new and existing products, data helps organizations discover and capture new opportunities. Data allows organizations to predict trends, from consumer spending patterns to macroeconomic trends, allowing organizations to pool their resources and put themselves in the best position to be first movers in emerging and future markets.

3-Data improves efficiency

As the business landscape becomes increasingly competitive, more and more companies cannot afford the inefficiencies that cost them time and money. Driven by data, digital transformation enables organizations, especially those with high-value assets, to improve operational efficiency.

For example, more and more aircraft are being equipped with sensors that measure operational performance. A single aircraft can be equipped with sensors that can generate 20 terabytes of data after an hour of flight. This allows airlines to develop preventive maintenance plans and extend the life of their aircraft. The same goes for manufacturing companies. Data gathered by sensors on machines and other factory equipment allows them to determine their own maintenance schedule and automatically alert the supply chain and service engineers to ensure the correct service is performed and the right personnel and parts are available. The right ones arrive at the right time.

Data also allows organizations to optimize the utilization of their assets.  Historical data analysis provides manufacturers with information on optimal equipment settings, such as temperature, pressure, electricity, and workload. It also helps manufacturers predict demand for their products, allowing them to perform critical maintenance procedures during periods of low demand, so that outages can be prevented during periods of high demand.

Why is digital transformation important?