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Digital transformation drawbacks and how to overcome it

Digital transformation drawbacks and how to overcome it

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Majority of the time digital transformation failure happens due to poor execution. For digital transformation success it is not only about adopting to new technology and understanding it deeper.

Digital transformation is no more a tool for the future. With the fast-evolving economy and expectations of customers changing rapidly, the digital transformation process has already become norm in world. Many get into a deception about how hard it is. According to many its an initiative not for weak hearts. One of the foremost reasons why more than 70% of organizations have such low records in digital transformation success, is because people are not using it wisely.

Let us look at some of the digital transformation mistakes to not make

Do not adopt technologies to be in trend

Many companies adopt new technologies without understanding the goals and targets to achieve with digital transformation. Some organizations apply the new technology tool to be in trend. Many are unaware of how to execute while some even blindly copy their competitors to use it. These reasons are no way a good strategy to implement such a complicated analytical tool. To succeed in this don’t get overwhelmed by the ubiquity of digital transformation, and don’t plunge into the unknown headfirst. Take your time to create a firm strategy that will alleviate business risks and intelligently streamline your organization through the digital transformation process.

Digital transformation is time taking process

Many firms are of the idea that digital transformation can be derive success in a day. But the truth is not that. It is a continuous process of data collection and applying it for use. If one plans to execute the entire digital transformation process in a short span of time, this will of no good. The data collection and execution are a very short duration will lead confusion in the minds of sellers and also consumers. Every new technology or innovative strategy you adopt will inevitably lead to more changes in the processes and priorities of digital transformation. It will impact every side of your business in some way.

Not making proper use of data collection

Many are of the view that data collection is digital transformation. But that is wrong, proper strategy to implement the transformation through data is the success. Dumping data without proper will lead no way. Data is valuable but knowing which data mining process for understanding which data for which purpose holds the key.

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How technology advancements help in digital transformation for global industries
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How technology advancements help in digital transformation for global industries

Organizations that triumphantly executed digital transformation have seen faster growth in their industries in comparison to their competitors. Surely, this process varies for each domain, business, industry, organization and their relative peculiarities. The right solutions are always achieved depending on the behaviour of a customer, preferences, analysis and different business logics of a company. The

Not so long ago experts were proclaiming that the mobile is going to be the future. And, guess what? They were not wrong. Some of the extraordinarily successful applications and businesses are mobile-based. Just think of the names like Instagram, Uber, Swiggy. Didn’t they transform the thoughts of a human into exceptionally well-crafted businesses and apps? Yes! They did. And for all those successfully running transformations there has been a secret that we need to know. That is, how they bridged all those gaps between a human and a machine and made a remarkable equation. How did they master it? Rapid Changes need adaptability With evolving technology, humans started to find a solution to every problem they encountered and started converting that as key thought of a business. Now, devices and machines are understanding from a deeper level than that of a human. Just think about all the technologies used in health care? How we have transformed from checking pulse with a finger on the wrist to having an oximeter for accuracy? There was take-away of food while we were kids and now food to your doorstep with a click. From buying a ticket at the station to booking it on the app. With changing needs and adapting new trends there has been a good equation we need to learn between a human and a machine. How do machines learn? Artificial Intelligence and machine learning happen basically in four types. This is exactly how the data is processed, observed, corrected and output is obtained. The key techniques in which the ML or AI leveraged to learn are as follows • Active Learning: Generally the models incorporated in machine learning are to guess the solution, check if it correct and go ahead to solve a similar problem. Active learning is a similar kind of work that AI and ML do. They take prioritized mathematical techniques from the subject matter expert and follow them to derive results. This method improves a positive collaboration between a human and a machine. • Transfer Learning: In this technique, the neutral network is well trained to solve a particular type of problem. Then the knowledge acquired in solving that problem is now transferred to apply for another different model but a similar kind of issue. For example, a problem solved in recognizing a car is relatively transferred for similar issues related to identifying a truck • Reinforcement Learning: This technique is used as a trial and error method. Where the successful methods are rewarded as right moves and the error methods are considered to recheck the process. This is mostly done by AI agent and is taught successful strategies. Through the process, the AI understands how well it can make the right choice to avoid consequences without any explicit instructions from the programmer. • Meta-Learning: This technique is a subfield of machine learning. It is programmed with certain types of algorithms that can teach a machine how to absorb the data. Simply how to learn what to learn. This helps the machine to upgrade in the form of skills and environments without the necessity of loading huge datasets. How should a human learn? This question might surely sound surprising. But, to have a great equation with a machine, humans need to upgrade on few things and learn a few. • Team game: Forming a potential team that is skilful in upcoming trends helps to work as a better team with those having skills in the current trends. This collaboration can bring out results that are meeting the current needs of a business and are also braced to encounter the new demands. • Discover: There is never s straight line to great innovations. Sometimes the non-linear process of going two steps back can bring out great ideas that can create wonders. • Test: Learning is always a process that goes on forever. It becomes successful only when tested and then identified as the right way. So a successful project gives a lot of skill enough to embrace another one. • Fail: The most common of all. It helps in a way better than a successful project. It gives clear guidance on what not to do. And, when it happens, stand again to start again. • Lead: Ensure everyone on the team is coached and trained to take over the project at any given time and circumstance. Throughout the process of a project, situations keep on changing and one needs to be well informed to face anything. • Unlearn and upskill: Every time a new problem arrives, the same process that succeeded in the previous issue might be completely irrelevant to this one. So be open to unlearn outdated processes and upskill to the emerging solutions. Conclusion From observing new technologies and how they are transforming digitally, it is very much evident that not just machines, but humans have a lot to learn to form a great equation. A good partnership between humans and machines can only be achieved if machines are made with accurate tools and technologies, and humans who can embrace diversity, nurture it across the industries and their ecosystems.
digital transformation

Understanding equations between humans and machines to master digital transformation

Not so long ago experts were proclaiming that the mobile is going to be the future. And, guess what? They were not wrong. Some of the extraordinarily successful applications and businesses are mobile-based. Just think of the names like Instagram, Uber. Didn’t they transform the thoughts of a human into exceptionally well-crafted businesses and apps?

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