Data Visualization Software: The Case of Nike

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Table of Contents

Introduction
Nike
Data Visualization with Nike Plus
How Nike Utilizes Data Visualization
Key Benefits of Nike’s Data Visualization
The Present and the Future Impact of Data Visualization on Nike
Potential Areas of Improvement
Conclusion
References

Introduction

The advent of big data and growing access to a massive amount of information created an environment where the development of artificial intelligence impact all industries and impacts the way they are collecting, storing and managing data. Nonetheless, any type of data could become a liability if the person or business receiving it would not be able to understand or decode it. This is why data visualization is a crucial business asset that may be used to realize the organization’s full potential with the help of experts in the field and all the insights gained from the processed data. One of the most popular data visualization instruments is Tableau. It has a large customer base and provides every end-user with interactive visualizations that are handling big data operations and datasets with ease (Nair et al., 2016). They also pay close attention to machine learning and artificial intelligence.

Another example of data visualization software is Datawrapper. Even though it is not as popular as Tableau, its simple interface attracts numerous customers who need to present statistics and create charts on a daily basis (Jess et al., 2015). A similar instrument called Sisense may be the simplest out of all three, with a drag-and-drop interface that is easy to use and understand. The users have the ability to gather data from a variety of repositories at the same time and perform queries across several dashboards (Cunningham & Stein, 2018). Sisense is compatible with big data operations and may provide the end-users with the answers to any type of problem.

Nike

A Brief Overview of the Organization and Data Visualization Usage

Nike is the most popular shoe and apparel company in the world. It focuses primarily on basketball and soccer players, but also sells a variety of products in the track and field sector. The brand also produces different sports items for children and pays close attention to competitive and recreational activities. According to Trabucchi et al. (2017), approximately half of Nike’s revenue comes from outside the United States, with more than 1,000 retail stores across the world.

Data Visualization with Nike Plus

The data visualization instrument that is used by Nike is called Nike Plus. The first thing that customers have to do to get the most out of Nike’s data visualization is to purchase all the required components. These include the sensor and the tracking device, where the sensor is expected to read the distance, pace, and calories burned with the tracking device, establishing the connection required to read all the data (Sosulski, 2018). The sensors are only compatible with Nike shoes that have a NikePlus connector. At the moment, there are at least 300 shoe styles that are compatible with NikePlus, ranging from $40 to $350. The tracking device is then synchronized with the sensor to send out the information to Nike servers and help customers store every byte of data related to their physical activity and health condition (Sosulski, 2018). Sports watches manufactured by Nike are also compatible with Nike Plus. All the data from the sensor is transferred to the tracking device in real-time so that the end-user would have the ability to access all the vital information while they run. As the data gets stored online, users can easily track their progress and share the results with the community.

How Nike Utilizes Data Visualization

The key to Nike using their Nike Plus initiative is the possibility to establish connections among Nike customers. Mostly owing to the advent of Nike Plus, the company has been able to develop a community of runners who track their progress and share the results with the community (Zepel, 2018). Each run recorded with the help of Nike Plus sensors contributes to the vast amount of rich data on other runners, helping everyone improve their running style and achieve better results. On the business side, Nike uses the data collected through Nike Plus to recommend specific items and products to the end-users, stimulating the market.

With the help of the Nike Plus initiative, the company attracted millions of people to the brand and allowed each individual to contribute to the running community. Nike Plus is a powerful tool because visualization stimulates the rational and sensorial segments of the brain instantaneously. Nike helps its customers exhibit the data that ignites the willingness to discover others’ successes that could have been ignored otherwise (Zepel, 2018). Overall, Nike Plus is a professional marketing platform that started as a mere data visualization app and then turned into a fully-fledged instrument intended to help the brand reach the customers and communicate with them.

Key Benefits of Nike’s Data Visualization

The most significant benefit related to Nike Plus is the company’s ability to read all the trend- and pattern-related data and identify the potential trends before they break out. This is a crucial concept that allows Nike to dominate the market and outrun its competitors by far, as the organization accurately predicts the milestones that the community is going to achieve. Without the data on patterns and trends, Nike Plus would be a useless data visualization application where the majority of decisions made by the company’s management would be based on assumptions and not facts (Burgio, 2019). Therefore, the use of data visualization allows Nike to rediscover the potential of untapped data and utilize every byte of information that is uploaded by the community.

Another benefit that is directly related to Nike Plus is the increased value and quality of collaboration. The Nike team improves the experiences of the entire running community by celebrating specific milestones and providing customers with purchase-associated benefits. Therefore, the company knowingly fosters innovation and creates positive experiences for the customers in order to make collaboration easier both within and outside the company (Gunther et al., 2017). The Nike team eloquently relies on visual representations from Nike Plus instead of going through hundreds of thousands of lines of data.

One more benefit that is highly visible due to the usage of Nike Plus is the operation-result relationship that is actively promoted by the company. For Nike, data visualization is a primary means of representing the connection between the brand and the community. The team responsible for the Nike Plus initiative uses data visualization to make quick decisions while gaining insight into critical metrics that could have been ignored otherwise (Burgio, 2019). For example, if a certain running community contributes to the development of an anomaly (such as excessive running activity or its complete absence after a prolonged series of scheduled runs), the company will be able to drill down the data to find the best approach to the problem. Therefore, data visualization allows for swift data analysis that is easy to access and understand.

The Present and the Future Impact of Data Visualization on Nike

The immediate impact of data visualization on Nike is highlighted by quick communication with the customers and stakeholders where all parties are efficiently brought together. The data is shared much quicker, and every dataset is presented in the most understandable form possible. As Nike Plus ensures clear and effective communication with the customers, the company has the chance to increase the effectiveness of its operations and contribute to the employees’ productivity as well. Satisfaction and motivation also improve across both customers and employees, strengthening the brand image, and reducing the turnover rates among both workers and consumers (Poon et al., 2015). On the other hand, Nike Plus can be used to save time and help employees tailor reports and make decisions much quicker than before, as they only have to access visual data and not go through multiple data sets in the form of text. Therefore, Nike Plus is an efficiency-inducing system that requires both customers and employees to gain innovative knowledge and apply it to real-life situations.

As for the future potential impact of data visualization on Nike, the most probable venue would be the ability to unlock the full potential of big data. The advent of this technology created a new stream of innovative decisions and significantly increased the amount of data collected by companies. The problem that Nike has yet to resolve is how to analyze all the data obtained from the sports community and deal with the inefficiencies that would be identified during the data analysis. Big data is going to become an essential business asset with time, which should motivate the company to focus on data absorption as well. The data continues to evolve, and it creates premises for additional applications of data visualization where even random data could be included in the graphs. On the other hand, the advent of big data serves as a hint at the fact that more sophisticated data analysis techniques are coming. Nike will be slightly forced to adapt to the innovative visualizations.

Potential Areas of Improvement

The Nike Plus initiative could be used by the company to amplify messaging capability. Knowing that pictures and visualizations have a powerful impact on customers, Nike could come up with visual messages for the end-users, motivating them to achieve new milestones and purchase associated products. As a trusted brand, Nike has all the chances to reiterate the same message in different vivid ways intended to impact the audience and empower them (Poon et al., 2015). The company would strengthen its positive image and create a bigger running community through data visualization. With the help of Nike Plus data visualization, the organization would also be able to reach out to internal stakeholders and compose powerful messages motivating additional investments and product launches. It will be much easier to persuade end-users and stakeholders through the visuals, giving rise to Nike’s organizational story. If the company chooses a wrong communication strategy, it will lose even loyal customers and reduce the value of data visualization (despite the data being useful).

Nike Plus could also become more beneficial for the company if the data collected via sensors and trackers were more comfortable to process and understand. If the company follows its own history and trends, it will pay much more attention to proper communication with customers and data analysis. This is an inescapable requirement for Nike if the company expects to process larger data sets simultaneously. Additional insights into business management would be beneficial for Nike Plus, as the organization could share visuals across the team members to motivate them to perform better (Burgio, 2019). This is a critical concept because visual information could significantly aid the organization’s decision-making process and compare the existing trends with the fresh ones. The customized Nike Plus initiative would be the best instrument for Nike’s management, who would become able to make informed and quick decisions.

Accordingly, another area of improvement could be enhanced decision analysis, where the company would have exclusive insights into the community’s preferences and aspirations. Given the fact that decisions are never made in a vacuum, all the information available from the data visualization software developed by Nike could serve as the key source of unbiased, timely data. Gaining access to relevant information is the first step toward making accurate decisions that are not going to damage the brand or the organization in general. The existing data visualization software could be improved by direct employee education, where Nike’s data workers would be required to share unbiased data. On a bigger scale, this would protect Nike from overlooking important information and making bad decisions that were not evidence-based. Knowing that customers never step away from honest feedback, data visualization may only be deemed deceptive in the case where team members refuse to disclose the deep-down facts.

Conclusion

Data visualization quickly became one of the most important business technologies that are currently used practically everywhere, from local businesses to large industry moguls. Nike’s example shows that a simple data visualization technology can be used to develop a close community of individuals who share interests and motivation while remaining loyal to the same brand. Therefore, the company does not misreport any customer-related data and protects itself from poor decisions by performing recurrent analyses of all the data collected through sensors and tracking tools. With no missing or incorrect information, Nike accurately predicts the next move they should make and the market’s reaction to their decision-making.

The existing data visualization experience with Nike Plus allowed the company to increase its financial performance. The company’s customers willingly purchase Nike Plus-related products and tend to achieve more due to the visual representation of their successes. Nike’s example also shows that a data visualization is a potent tool that has to be utilized prudently. Otherwise, the company risks disclosing itself to market and customer losses due to improper messaging and incorrect decision-making. Nike Plus provides the community with powerful messages and detailed insights into their achievements, having Nike stand behind every predicted trend and correct decision the company had made since the advent of Nike Plus.

References

Burgio, V. (2019). Uncertain infographics: Expressing doubt in data visualization. Semiotica, 2019(230), 143-166.

Cunningham, L. M., & Stein, S. E. (2018). Using visualization software in the audit of revenue transactions to identify anomalies. Issues in Accounting Education, 33(4), 33-46.

Gunther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191-209.

Jess, T., Woodall, P., & McFarlane, D. (2015). Evaluating the applicability of multi-agent software for implementing distributed industrial data management approaches. In Service Orientation in Holonic and Multi-agent Manufacturing (pp. 199-207). Springer.

Nair, L., Shetty, S., & Shetty, S. (2016). Interactive visual analytics on Big Data: Tableau vs D3.js. Journal of e-Learning and Knowledge Society, 12(4), 139-150.

Poon, C. C., Lo, B. P., Yuce, M. R., Alomainy, A., & Hao, Y. (2015). Body sensor networks: In the era of big data and beyond. IEEE Reviews in Biomedical Engineering, 8, 4-16.

Sosulski, K. (2018). Data visualization made simple: Insights into becoming visual. Routledge.

Trabucchi, D., Buganza, T., & Pellizzoni, E. (2017). Give away your digital services: Leveraging Big Data to capture value: New models that capture the value embedded in the data generated by digital services may make it viable for companies to offer those services for free. Research-Technology Management, 60(2), 43-52.

Zepel, T. (2018). Contemporary data visualization: A cultural history and close readings. University of California.

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