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Digital Transformation , Technology Consulting

How to digitally transform a company

15 September 2022

Digitalization
Make it an habit

Digital transformation is a process, not an event. It is the next logical step in digital evolution after mobile computing, cloud computing, big data analytics, and the Internet of Things (IoT) rollout. As with previous industrial transformations, digital transformation will bring new opportunities as well as new challenges for companies wanting to transform.

A true digital transformation requires a complete assessment of a company’s products, services, processes, and strategies on a cultural, customer, and business level. Done right, a digital transformation means better customer engagement, stronger employee relationships, and more profitable vendor interactions. The main goal is to revolutionize an organization’s IT department to make the company more competitive and productive while discovering new ways to improve efficiency, deliver value, increase competitive advantage, and, above all else, raise revenue and profitability.

As with most business scenarios, early adopters reap the biggest rewards, and the digital transformation movement is no different. Early adopters have shown some extraordinary successes, and most of these accomplishments have occurred in the following six areas:

Artificial Intelligence

Major tech company CEOs are comparing AI and machine learning to some of the most important discoveries ever invented by man because they see its ability to revolutionize manufacturing, robotics, logistics, marketing, and customer personalization. The economic impact of AI will be driven by productivity gains from automation and AI labour augmentation, as well as increased consumer demand because of personalization marketing.

Data Optimization

Data is foundational when it comes to digitally transform a company. First and foremost, data needs to be trustworthy. “Junk in, junk out” is the analyst’s lament, and it holds true for data usage throughout an entire organization. Untrustworthy data should not be used because any models built on that data will be skewed by the bad data and useless for business purposes. However, when a company’s data is trustworthy and administered and maintained properly, it can reveal truths about a company’s operation that, although at times might prove troubling, can be the basis for real operational change that can increase a company’s profits and optimize its operation.

A digital transformation is about streamlining a business’s processes and utilizing data from platforms like social media and the IoT to help design and shape customer experiences. Trustable customer data in CRM and marketing systems make personalization marketing much more useful and increasingly effective.

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The Cloud

Today’s IT departments must handle complex systems filled with everything from distributed architectures, Big Data applications, microservices, multi-cloud containers, and real-time data streaming in from social media sites, mobile devices, and IoT services. Cloud computing is now a must-have. Without it, it would be impossible to keep up with the flow of not just Big Data but also fast data. Cloud technology is the backbone of any company’s digital transformation initiative.

Automation

Automation is a key component of digital transformation. It allows businesses to keep their systems functioning properly, reduces the need for workers because machines can do a lot of repetitive work more optimally, and even ensures IT systems are operating in a self-healing way.

As IT systems have grown increasingly complex, so have the support systems needed to ensure these systems work properly. Business Process Management (BPM) systems that aimed to improve a company’s business processes by analyzing, optimizing, and acting in self-healing ways. Artificial Intelligence and operations (AIOps), which added AI and machine learning to the process, evolved from early BPM systems. AIOps applications can consume huge amounts of data types, then analyze the system data, and learn about a company’s day-to-day IT operation, ultimately reducing system noise and accelerating root cause analysis of problems that arise within a business’s daily operation. It then proactively fixes any operational issue it finds while also providing end-to-end visibility into the company’s systems and applications.

Automation benefits include:

  • Improved performance monitoring
  • Increased productivity
  • Noise reduction
  • Reduced operating and labour costs
  • Increasing employee collaboration
  • Breakdown of data silos
  • Simplified root cause analysis
  • Seamless customer experience
  • Predictive and proactive IT self-healing

 

Another tool in the automation arsenal is robotic process automation (RPA). It can help a company reduce its labour needs and increase productivity by allowing users to configure one or more scripts that activate specific computer keyboard functionality, resulting in software that mimics selected human tasks. These can include data collection, data manipulation, response triggers, analytical model building, and a host of other internal IT processes. RPA replaces a human in an “outside-in” way, turning a computer into a functioning human responding to a set of strict, repetitive procedures.

With the use of AI, machine learning, and Natural Language Processing (NLP), highly intelligent chatbots that respond to customers with smart responses in a natural, human language and tone have been introduced to business on a massive scale. Today, chatbots are everywhere. The public has embraced them because they can mimic human intelligence by interpreting a consumer’s questions and then answering basic customer service questions as well as much, much more. They can offer product recommendations, provide stock detail, help users book tickets to a flight, a train, or even just an event, as well as order and pay for a whole host of items.

Chatbots can help businesses in the following ways:

  • Improve the customer experience
  • Increase customer engagement
  • Improve up-selling and cross-selling
  • Increase intelligent customer recommendations
  • Quickly answer customer and product queries
  • Create one-to-one marketing experiences for each customer
  • Help customers find products they want
  • Increase customer service efficiency
  • Reduce customer churn

Big Data

Although data seems impervious, its value can erode quickly. Used at the most opportune time, it can be one of the most valuable commodities. However, sometimes minutes of old data are worthless, especially in marketing. The process of capturing, cleansing, modelling, and transforming data is an exceptionally difficult one. The rewards, however, can be huge.

Today, Big Data’s potential is finally being realized because improvements in data collection, data cleansing, data governance, metadata management, data integration, data visualization, and data modelling have made Big Data much more accessible and actionable. The cloud, real-time processing, the IoT, AI, machine learning, and deep learning can utilize Big Data in previously impossible ways.

Analytics

Accurate, complete, and timely data are the three main ingredients of successful analytics. Today’s operational analytics solutions can enhance IT operations, increase productivity, reduce labour needs, and streamline operations. Analytics can be used throughout a company, including customer service, order management, fraud, risk management, product development, operations management, labour management, data governance, regulatory compliance, supply chain, and procurement, among many other departments.

Customer analytics can expose patterns and trends hidden in customer behaviour data that can help with personalised marketing. The resulting analysis can help companies predict future marketing outcomes. For example, customer analytics can help determine which of a company’s advertising campaigns will have the highest landing rates. This is extremely useful information when creating marketing plans and budgeting for the plethora of campaigns and channels offers can be sent through.

Analytics can be used to:

  • Understand sentiment drivers
  • Identify characteristics for better customer segmentation
  • Measure a company’s share of voice and brand reputation compared to a competitor
  • Attribution analysis
  • Anticipate customer problems with products and/or services.

 

AI and machine learning make it can be useful for customer recommendations, security, voice recognition, fraud detection, predictive asset maintenance, sentiment analysis, and website search engine optimization, among many other use cases. AI can review vast amounts of documents in a fraction of the time it might normally take. AI tools can evaluate large IP portfolios and provide recommendations at a fraction of the cost of hiring expensive consultants or legal representatives. Machine learning and NLP can analyze contracts or requests for proposals in seconds rather than in days, which can help speed up the negotiating and hiring process.

The Digital Transformation Process

A digital transformation should be treated like any other important, large-scale company project, if not more so, as it affects the foundation of a company’s IT department. Detailed project plans that lay out goals, costs, and objectives are required. These should identify key business champions and stakeholders as well as define roles, responsibilities, and detailed department goals. This blueprint defines how the project will start, what is needed during the implementation to maintain it, the tools necessary to complete it, including any software and hardware needed, and the labour required to run and oversee it.

Build a strong team

Trying to create a holistic solution from a disparate set of software and hardware requires the help of experts, so hiring outside consultants should be expected. However, a company can start by getting its data house in order and then decide which business intelligence software should be utilized. Companies with a large customer base should look at CRM and marketing automation suites before introducing analytics into the process. Analytics, especially AI, machine learning, and deep learning, should be left until the company has trustworthy data. Analytics might be the most complex part of any implementation, but it is also the most potentially profitable.

Choose your tools carefully

Before any implementation begins, deciding which tools to use is important. A one-size-fits-all option is not possible because software is so complex and can do so many things these days. There are products for data integration, data cleansing, meta-data management, analytics, AI, machine learning, business intelligence, and marketing, many of which have cross-functionality but none of which can do everything a company needs. Most companies are saddled with legacy systems, and any new software needs to be integrated with the old as seamlessly as possible, which isn’t always easy — or even possible in some cases.

Run pilots

Companies need to select pilot groups that identify potential use cases for the technology as well as layout particular areas of concern. To help push technology adoption, it’s important to build excitement from the onset of the program, through the launch, into development, and then onto results. Celebrate quick wins throughout the company. For failures, don’t fear a forensic examination of what went wrong. Once the project has been successfully developed, tested, and marketed company-wide, it’s time for a full launch.

Keep the momentum

Once launched, it’s important to keep the momentum going. Hands-on training and education are important. Feedback channels should be opened to foster a positive environment for opinions and comments, even allowing anonymous criticism that can provide a more honest appraisal of the new solution.

Conclusion

The term “digital transformation” was first used about 10 years ago, and although adopters have seen impressive results from their initial efforts, it’s not too late to join this revolution. Companies that don’t risk losing market share and being left behind by their competitors. Today, digital transformation is shifting into high gear. Almost every industry has been affected by it. Technological innovation is proving to be a key driver for success in companies such as Apple, Amazon, Google, Facebook, Microsoft, Nvidia, Alibaba, and Baidu, among others. Tools like AI, machine learning, deep learning, analytical software, business intelligence, and natural language processing are helping companies of all sizes increase productivity, boost efficiency, reduce labour costs, and improve their customer relations.

The digital transformation is here for good and kicking into high gear. Just about every business will be touched by it whether or not they want to be. But wouldn’t they? A digital transformation can help a business in a multitude of ways. It can help companies gain a competitive edge over their competitors as well as strengthen the company’s relationship with its customers, vendors, partners, and employees.

Digitally transforming a company is a highly ambitious goal, but it is necessary. Companies that jumped on the digital transformation bandwagon are now some of the most successful companies, many worth billions. A lot of the companies who ignored it aren’t lamenting their lack of vision anymore because they are no longer around to worry about a lack of foresight.

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