The media has been talking a lot about Artificial Intelligence, mainly about how companies need to use this new technological wave. However, amid this much information, there is still a lack of clarity on one point: how can I generate real value for my company and achieve the desired results? If you want to know practical examples, continue reading this post.

In the MIT Sloan Magazine article “How Leading Organizations Are Getting the Most Value From IT,” the following is said: “Many of the most important investment decisions that CEOs currently face are related to technology. That was not the case a few years ago. But now every company is, in fact, a technology company and every CEO, a technology CEO”.

Today, technology decisions are no longer exclusive to IT executives; they involve the entire organization, not only in the decision but also in the execution. Digital transformation is not exclusive to IT; it is a necessity for the entire organization.

So, keep reading, because regardless of your position, Artificial Intelligence is a matter for everyone.

LEARN, IMPROVE, INNOVATE AND ENGAGE

Learning, improving, innovating, and engaging are the four phases that allow you to go forward!

LEARN – Big data analysis and insight production

Indeed, one of the most important AI points is its incredible ability to generate value through the insight of big data. This ability, obviously supported by the concept of Big Data, can be used to understand consumers’ behavior, individually, in groups, or the whole. We can predict situations and behaviors and improve products; that is, we can enhance our operational capacity according to the insights obtained. This improves performance, obtains greater profitability, and positions ourselves better in competitive segments.

In itself, although we are talking about the potential and values ​​generated by AI, one thing is fundamental: data. Without the data, there is no AI that works, so before starting any AI project, check if you have or can produce the necessary data so that you can generate value with your AI projects.

One of the crucial points in this learning process is discovering your relationship with your customers, identifying who delivers the most significant return, and starting to serve them with more attention. Find out who has the potential to buy more and create engagement models. Finally, learn to become more efficient.

IMPROVE – Transformation of value chains (operational transformation)

First, it is essential to understand a value chain’s concept: A value chain represents the set of activities performed by an organization from relations with suppliers and production and sales cycles to the final distribution phase.

The value delivered to a customer, whether through product or service, is, therefore, the result of the work of an entire chain, that is, everyone who participated with activities or inputs (from raw material, manufacturing or transformation, packaging, marketing, sales, support, customer service, among others). This, in the end, makes the output something that makes sense to the customer and represents great value.

Now that you understand what the value chain represents imagine the potential for using AI in this context. There are countless possibilities, from the use of cognitive workflow tools that use machine learning algorithms, helping in each stage of the production process, to the use of visual computing to validate stages or the quality of the product itself.

There is great potential for increasing competitiveness and differentiation by transforming operational activities with the use of AI. All operational activities can be supported by artificial intelligence, regardless of the type of activity. Improvements can be applied from complete automation to support the human activities involved.

INNOVATE – Transformation in business models

When collecting all the insights with data analysis and transformative power in operations, innovation possibilities appear. The experimentation and validation process, with AI support, is more efficient and allows testing new models quickly. 

An exciting example of the transformation in the business model is Nike, which launched in 2018 the Nike House of Innovation store on Fifth Avenue in Manhattan. It seeks to stir emotions, captivating, and involving all its customers’ senses. Also, Nike created numerous applications integrated with sensors in sneakers and other sporting goods, which later combine these captures into large “Big Data Lakes” that are processed by Machine Learning and, in the end, offer experiences beyond a simple manufacturer sporting goods. This is undoubtedly an example of transforming a business model based on sporting goods that migrates to a business model of experiences.

Regardless of your business model, innovation can be achieved with the right use of the right tools.

ENGAGE – Better customer experiences (transformation of experience)

With insights produced by data analysis and the real-time learning acquired with users and customers as they use apps and websites, we can shape creating greater engagement. Creating these experiences can expand the possibilities for sales into loyalty and enchantment of customers and users.

Experiences are the current power of differentiation in the competitive market. There are several ways to offer experiences, whether at the time of purchase, whether in customer service, post-sale, or outbound (proactive actions for access to buyers). Today companies in this foray offer fast, simple, and efficient channels for the user to carry out services (exchanges, returns, etc.) and interactions with the company.

The use of chatbots is an initial channel that easily and efficiently connects this customer experience. Keep in mind that chatbot is not just to reduce operating costs – although it is a significant benefit – it should not be the primary objective since it does nothing to reduce costs if it worsens the customer experience. Align both strategies, but focus on providing the right experience for your client.

It is also essential to understand that chatbot is the path that many companies are currently using as a starting point. Still, the customer experience journey is longer and more complete and involves many other factors that must add up, to promote better experiences. As practical uses examples: adequate solutions for customer service under the concept of multi-channel, internal workflows integrated into the entire value chain, predictive machine learning influencing tastes and forms of interaction, among others.

Conclusion

Intelligence is the most critical asset in modern organizations, and we say this because human intelligence, combined with artificial intelligence today, brings almost limitless possibilities. Whether by the delivery of AI’s predictive and precision capabilities that significantly enhance proactive actions or by the human being’s creative capacity, who, through insights, can propose new models and quickly validate them with data support.

We are beginning the era of intelligence, the sum of HI + AI. Use this power sparingly! Did you like tips? Visit our website and learn more about the 4Biz platform to improve your organization’s performance.