Digital transformation. What it is and its importance and relationship with the data

As a first definition we could say that the digital transformation is the application of digital capabilities to processes, products and assets to improve efficiency, improve customer value, manage risk and uncover new opportunities for income generation .
By digital capabilities we mean those that are electronic, scientific, data-driven, quantified, instrumented, measured, calculated, and quite possibly automated.

1. What is digital transformation?

The digital transformation is the integration of digital technology in all areas of a business, fundamentally changing the way it operates and delivers value to its customers . It is also a cultural shift that requires organizations to constantly challenge the status quo, experiment, and be 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 , of its supply chain and workflow, the skills of its employees as well as board-level discussion processes. management, customer interactions and their value to stakeholders.

Digital transformation helps an organization keep pace with emerging customer demands, keeping them going well into the future . Digital transformation enables organizations to better compete in an economic environment that constantly changes as technology evolves. To that end, digital transformation is necessary for any business, non-profit organization, or institution seeking to survive in the future.

Key technologies

Technology drives the need for digital transformation and supports the digitization of an organization . In addition, there is no single application or technology that allows digital transformation, but there are multiple key processes that an organization must generally have to face the transformation:

Cloud computing , for example, gives your organization faster access to the software it needs, new features and updates, as well as data storage, and enables it to be agile enough to transform.
Information technology enables an organization to focus its investment of talent and research and development money on customized solutions that support its requirements and the processes that differentiate it in the marketplace.
Mobile platforms allow work to be done wherever and whenever.
Machine learning and artificial intelligence technologies provide organizations with insights to make more accurate decisions about sales, marketing, product development, and other strategic areas.

2. The importance of digital transformation in a world of data

Organizations that see digital transformation primarily as a technology difference over traditional business process engineering transformation will end up losing the power of digital transformation.

How is digital transformation different from business process reengineering?

A digital transformation journey moves an organization from a process-defined world to a data-driven world. Let’s see why this is powerful and how it changes the value that an organization offers to customers and end users.

Digital collapse processes
In today’s world, companies are built through processes, trying to develop high-level processes. Six Sigma and other tools are designed to refine and improve those processes to create efficiency, focus, and quality improvement. In contrast to this, digital transformation reduces the processes that a company does or could do today, automates the work that people do, and turns the process into software. What remains is data. Digital turns processes into data. This allows organizations to view their business through the lens of the data rather than the objective of the process. Suddenly, the data make it clear that the matter people and the experience of the customer care

. For example, instead of viewing customer service as a set of processes initiated by the customer or the organization, it is customer data that forces the organization to think about the customer experience. As data emerges and the ability to associate that data with metrics or issues, an organization may not only become more efficient but also change what it does. The business impact that results from viewing the world through a data lens rather than a process lens is very powerful.

Rethinking assumptions
In a data-driven world, an organization can reconsider many of its old assumptions . When Airbnb, for example, separated itself from processes and focused on data, it realized that the company does not need to own physical assets (hotels). Aspects of a hotel business that made it competitive in a process-driven world came to a standstill in a data-driven world. People who have apartments in great locations are a different option than hotels and offer a different value in the customer experience.

By rethinking old assumptions about a business, we can get to the different places where value or opportunities arise differently from the world defined by the process.

Another example of rethinking assumptions in a data-driven world is HR processes. Companies built their employees’ expertise around HR processes that serve employees, such as payroll, benefits, employee communications, and recruiting. When we move to a digital and automated experience, the data focuses attention on the employee experience. Instead of asking what the organization does for an employee, the data shows the needs and what is happening to the employee.

Data enable rate
Speed is the new currency in business. Organizations must be quick to meet the needs or expectations of customers and employees in a competitive market . There are no shortcuts in digital transformation to reach this speed. But as an organization moves further and further into an automated software-defined world, it moves faster and faster as data and its important associations emerge. That allows the transformation of what the company does. In a process-driven world, processes must be routine and allow the defined result to be consistently obtained.

Digital transformation transforms processes, making it faster and more reliable to focus on what needs to be done rather than getting caught up in the effort to get the processes right. A data-driven world enables you to deliver a complete customer experience , “on time and in full.” From the customer experience, it is not how quickly the organization answers the phone, but how quickly the customer can complete an order. Customer experience and satisfaction lies in the fact that the customer does not need multiple conversations with the organization. The need for a meeting can be done quickly and done only once. The same experience expectations apply to employees

. In a process-driven world, a salesperson needs to ensure that the company calculates commissions properly whereas in a data-driven world, the employee can see the information.

There are no short cuts
The temptation to move from a process orientation to a digital orientation is to shorten a few steps. But in reality this is not possible. Digital transformation involves more than collapsing a process into a data set. As an organization moves on the path of digital transformation, many aspects of the business model must change, as processes and data are interrelated.

In a data-driven world, an organization can understand the context of all interactions with a customer, employee, or end user and whether the interaction will bring frustration or delight to that person.

In a data-driven world, an organization has the full context of customer, employee, or end-user expectations. So you can drastically change where the value is. And you can change the quality of what you do, as well as do it on time and in full, delivering the result that the customer or employee wants.

3. 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 beginning to change the transportation industry. Artificial intelligence and machine learning enable predictive approaches to decision making and drive business insight.

This digital transformation sweeping industries by storm would not be possible without data. Data is the enabler of new technologies and solutions. Data is where important and 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 driving digital transformation and what constitutes quality information.

Data optimizes sales channels
The potential to reach new customers is a critical factor in the adoption of digitization. But the 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 changed the way consumers buy products and use services . Companies had to respond by transforming their sales channels and adding e-commerce websites and mobile applications to their traditional channels, such as physical stores.

Data is key to understanding customers and their preferences. Structured data, such as that coming 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 hear what their customers want through their online posts, comments, and sentiments. This increased understanding enables organizations to optimize their sales channel strategies to suit 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, thus maximizing opportunities for cross-sell and upsell.

Data drives innovation and revenue
Another key to digitalization adoption is product and revenue innovation . Digital transformation enables organizations to create products that customers want rather than creating products and forcing customers to buy them.

Data on when, how, where, and why products are used provides product engineers, designers, and manufacturers with information on 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 the unstructured sentiments of their customers on Facebook and Twitter, they discovered that a competing product featured new functionality that it lacked. When structured data was analyzed in their CRM systems, it revealed the same reason why customers were abandoning the product. The company responded by adding that same feature to its product, and its sales rebounded. To create truly innovative products,

In addition to innovating with new and existing products, data helps organizations discover and capture new opportunities. The data enables organizations to predict trends, from consumer spending patterns to macroeconomic trends, enabling organizations to pool their resources and place themselves in the best position to be the first to move in emerging and future markets.

Data improves efficiency

As the business landscape becomes increasingly competitive, more and more companies cannot afford 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 one hour of flight. This allows airlines to draw up preventive maintenance plans and extend the life of their aircraft. The same goes for manufacturing companies. Data gathered by sensors on machines and other equipment in the factory enables them to determine their own maintenance schedule and automatically alert the supply chain and service engineers to ensure correct service is being performed and the right personnel and parts The right ones come at the right time.

Data also enables 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.

4. Data analysis as an accelerator of digital transformation

As digital transformation continues, businesses are beginning to understand that more needs to be done with data. Raw data alone does not generate information to drive business growth. Rather, it is the insights derived from the data that create true value. IoT offers new sources of data and technology is evolving to collect, process and store this information. Analytics of IoT data, particularly when combined with other business data, provides insight into the business, helping organizations better understand their customers’ wants and needs and ultimately differentiate themselves from their customers. competitors.

In order to effectively harness the value that can be gained from data analytics, a cultural shift must be made in the way organizations approach analytics. This cultural shift can be described as the three “I’s” of big data :

Invest in collecting, analyzing, and using data to help businesses avoid extinction during digital transformation.
Innovate with previously unexplored data to create new products and services, along with better customer experiences.
Improvise by exploring data and finding new meaning, which will then be turned into actionable information in a continuous cycle of data.

We no longer look at data for what we already know (or think we know). Instead, we explore the data and turn it into actionable insight, in a continuous cycle.This improvisation leads to innovation, which in turn leads to optimizations and new opportunities. This, of course, requires new investments, in people and technology, and it is this investment that heralds the new approach: building an agile, adaptable and resilient business through the application of data analytics.

Analytics are driving the future

Today’s digital transformation, triggered by the explosion of data and connected devices, should be seen as a world of opportunity for businesses, rather than a threat. The secret sauce for survival, however, is based on a cultural shift that focuses on the value of data analysis. Businesses that consider analytics critical will gain the most from their data, now and in the future . Organizations that invest in data collection and analysis will avoid its demise in the digital age. Innovating and generating new ideas on how to use this knowledge to create new products and improve customer experiences is the next step in the process. Finally,

improvisation and data exploration to find new meaning will lead to a series of ideas that will fuel the continuous data cycle .

5. Complementary material

Solutions and resources for digital transformation
Data-Driven Digital Transformation
Digital transformation in a data-driven world
Transformation into a DATA-DRIVEN company
Digital Transformation: Unique Customer Records and MDM Master Data Management
Digital Transformation: Unique Customer Records and Master Data Management (MDM) “Towards the Best Customer Experience

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Five Imperatives for the Chief Data Officer
Reimagine iPaaS for a Data-Driven Digital Transformation World

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