HomeBUSINESSDigital Transformation In Companies: Which Strategy Leads To Success

Digital Transformation In Companies: Which Strategy Leads To Success

The digital transformation is determined by finding new ways to transfer existing data in the company for. According to the analyst firm IDC, digital transformation is standard today in the modern business world and could generate an additional business value of 18 trillion dollars. On the other hand, there are some challenges that this data represents for companies. It is essential to manage, integrate and analyze vast amounts of data. In addition, there is often the unwillingness to initiate the resulting changes and a lack of technical resources, which also prevents change. In the long term, it can have detrimental effects not to remedy these deficits and not to develop a successful digital transformation strategy.

Digital Transformation: How Companies Do It Right

Polaroid is a prime example of a company that has failed to adapt to changing market needs. For example, the photography pioneer has passed on from a $ 3 billion company in 1991 to bankruptcy in 2001 and ultimately to the sale of all of its brand and assets. The decision to continue to focus on instant film as its primary business, and the half-hearted digital transformation efforts at the same time, prevented the company from benefiting from the success of digital photography. So what are the most important considerations for a company to develop an effective digital transformation strategy? 

Digital Transformation: Insights Into Business Change

The digital transformation thrives on insights gained from analyzing data. These offer a new perspective on your business activities and thus enable the creation of new business models. Knowledge is distilled from context-based data. The ability that supports hypotheses. Data is the underlying raw material.

To advance the digital transformation, more data, more analysis tools, faster analysis cycles, and, in addition, automation of data preparation and engineering tasks are required to develop a profound basis for decision-making. This is the only way to gain deeper insights.

Awareness Of Business Opportunities

Applying this newfound knowledge enables companies to gain a better perspective and identify new business challenges and opportunities. For example, these insights can form the next step towards more complex and richer data models. These show how events are linked to one another and what influence your own decisions have on them.

Digital Transformation: Optimization Creates Added Value

Foresight as a result of these processes can lead to new business models. These should be introduced gradually, ideally in the first step with a small project to evaluate the product/market adaptation of the new digital model. The further optimization then transfers this process to a more extensive system until the central business model expands to all relevant situations.

The digital transformation often requires the constant further development of all individual products. The challenge is to move quickly and in the right direction. For this purpose, companies need a robust database, for example, to analyze and monitor the use of a product. Likewise, strong product management pushes the further joint development of the product.

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Digital Transformation: Automation Enables Scalability

While optimizing processes can help a company grow, automating them ensures long-term scalability. Regardless of the industry, today’s age requires that companies present themselves digitally. However, companies find that full automation is problematic because it entails completely redesigning business processes into a brand new architecture.

Automation used to be all about APIs and coding. That still applies today. More and more, however, automation is supported by machine learning algorithms that can also recognize patterns that remain hidden from humans. The functional landscape for automation must represent the maximum possible coverage of the product through APIs. This enables scripts, programs, and machine learning systems to manage the product’s behavior or the support system. Instrumentation should be integrated at all levels to support feedback loops that enable learning and problem-solving.

Scalable Architectures On The Advance

The scalability of digital processes is a core component of digital transformation. It enables companies to build on successes achieved iteratively and to allow new optimizations. 

A scalable architecture can also be built in stages. Scalability means: expandable if necessary or reducible if necessary. For example, Amazon Web Services offers automatic scaling with Auto-Scaling. It adjusts when you need more power, and it pulls back when you need less. It is essential to consider whether the existing architecture is scalable for the current phase. Although it is unnecessary to have expandable architectures ready at the beginning of an initiative, growth should always be planned.

Ultimately, the ability to remain agile as the business grows is a hallmark of a successful digital company. The options to renew oneself, adapt, and change at the same time with one’s surroundings. With companies operating in an ever-changing technology environment these days, agility is the key to running a successful business.

Machine Learning Gets Strategy Going

Developing a new digital strategy is not easy. Setting the wrong digital system can be expensive. One of the cornerstones of checking whether you are on the right track is the continuous search for new insights into your data, documents, and systems.

Collecting these insights leads to even more data and analysis. Their manual processing can take months and ties up time and resources. In addition, most automation requires rules and well-labeled records. This can also be problematic. However, machine learning techniques – such as clustering and classification – based on algorithms for similar grouping data can help reduce the manual effort required to prepare the data.

Digital Transformation: Ready For The Next Big Step

Many companies are faced with the question of whether they are ready for the next big step. Or whether they lag with falling sales and are uncompetitive only to fail ultimately. Developing a successful digital transformation may be challenging, but in the end, it can be the answer to the question. However, a reliable basis for decision-making is essential. Using the right tools to make these decisions in the first place is a prerequisite for moving a company forward.

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