Day 59 — Demystify series 7/7: “(blank) Transformation: Digital, Data, Agile”

Original Photo by Justin Peralta on Unsplash

If you’re working with C-suite level or you pay close attention to companies’ annual shareholder letters, you’re probably not unfamiliar with the term “Transformation”. There are all different kinds of transformation, digital, data, business, solution, and Agile. What are the differences? Why are they important? In today’s article, I’m going to share my experience and knowledge around Digital, Data, and Agile transformation, with the following structure:

• Definition & Examples
• Importance & Differences
• Reality
• Future

Definition & Examples

• Digital Transformation: According to Wikipedia, digital transformation is “the novel use of digital technology to solve traditional problems”. These digital solutions enable inherently new types of innovation and creativity, rather than simply enhance and support traditional methods. Sounds pretty broad, doesn’t it? The most common digital transformation approaches are adopting cloud storage & computing, offering on mobile platform, and Internet of Things (IoT).
• Data Transformation: Paraphrasing the definition on Wikipedia, Data Transformation is the process of converting data from one format or structure into another format or structure. It is the foundation of data integration, application integration, and business insights extraction. For example, one US bank expects to see more than $400 million in savings from rationalizing its IT data assets and $2 billion in gains from additional revenues, lower capital requirements, and operational efficiencies.
• Agile Transformation: It is the process of transforming an organization’s culture and nature to one of agility. Transformation is about a fundamental change in the way people think and feel. Instead of adopting some Agile framework like Scrum and practicing the process, Agile transformation focuses on the attitude and behavior of “learn fast and learn often”. Some people distinguish this from adoption by calling adoption “doing agile” and transformation “being agile”. For example, Agile transformation helps breaking down functional silos and create delivery-focus teams to boost the organization agility.

Image source: Vitality Chicago

Importance & Differences

Importance

• Digital Transformation: In the last 3 decades, the front runners on the Fortune 100 company list kept changing their ranking. We saw more and more technology companies taking front row seats where traditionally were occupied by banking, pharmaceutical, automobile companies, and others. The force of technology has been disrupting the world, and the non-digitized companies saw the threat and wanted to jump on the band wagon of “Digital” before it’s too late.
• Data Transformation: it is the cornerstone for many kinds of IT related transformation or improvement. Two main reasons include: 1) without modernizing the data storage and format, it’d be hard to integrate with other software/hardware/platform for any improvement project; 2) without properly capturing data set in a “clean” way, it’s hard to do “data-mining”, extracting important information to generate business/customer insights.

Image source: Boston Consulting Group

• Agile Transformation: Whether it’s cloud computing or mobile offering, some argue that Agile transformation is one of the fundamental elements of digital transformation; reason being without the mindset of Agile, individual projects can easily fail due to lack of understanding of the problem, and ways to pivot to better solutions.

Differences

• Digital Transformation is a general term to describe digital related approach for business enhancement/transformation; while Data Transformation focuses on both converting existing data and new way to record data for more efficient way of data usage; meanwhile, rather than a set of specific approaches, Agile Transformation is about workers and teams adopting the thinking of “learn fast & learn often”. Surely they can utilize existing Agile software development rituals to help develop those habits, but at the end of the day, it’s the education and culture that make it happen.

Image source: Data Driven Investor

Reality Bites

Status & Challenges

• Digital Transformation: According to Forbes Magazine’s survey, only 44% of respondents believe their companies actually integrate digital strategy into corporate strategy, or feel their leaders are “digitally savvy and help the workforce think in new ways.” One of the many problem is there’s no single way to interpret how digital transformation should be done; as a result, either the endeavor stays in the board room and employees are lack of awareness of it, or it often confuses people what it is and what to do, given there’s no established “playbook” for it. The biggest problem of all is that digital transformation requires cultural transformation with proper training and education, making it an actual process to help people “look through a digital lens to do things more immediately in a more satisfying way and cheaper you can help other people do this.”

Image source: Starberry

• Data Transformation: Perhaps the easiest to implement among all three, given the impact area, required resource, and level of behavioral change are in much smaller scale. Data transformation is probably the only one of three that only requires IT department to be involved in the transforming process. However, that’s not saying it’s all well and good. Given the fast-pace nature in the IT industry, keeping up with the most modern technology sometimes can become a big cost for business leaders to swallow. It takes time and money to get it right, and most of the CEO will have to trust CIO/CTO’s plans without much knowledge to judge their decisions on data transformation.
• Agile Transformation: Because speed is essential in a digital transformation, a lot of organization mention Agile transformation is part of their plans of digital transformation. In my previous post, I talked about the true agility is not about rushing, but rather being able to quickly change gears. This new way of working is a behavioral change that requires appropriate planning, training, coaching, and supporting. However, lots of the non-tech companies want the fruits and forget to grow the tree first. As a result, people simply follow some Agile rituals without really being Agile: learn fast & learn often

Image source: Workfront

Future Evolution

• Digital Transformation: Lots of challenges for digital transformation is data related. Therefore addressing the data transformation issues is one of the biggest common solution for digital transformation. Another aspect is to craft a scalable digital transformation journey so that when technology evolves, the plan is flexible enough to accommodate various types of changes.
• Data Transformation: Except for existing approach and effort on data ETL: extracting, transforming, and loading, there’s also growing concern and counter-measure around data security issues. More and more investment are pulled in to ensure that not only the data is clean and useful, but also stay in the right hands.
• Agile Transformation: Thanks to the maturity in awareness of Agile, we’re seeing more and more cross-disciplinary collaborations and role overlap. For example, business school and IT department is teaching Design Thinking, designers are learning product & system thinking, basic coding skills, and strategy. We’re expecting more new roles to be created in order to break down silo and create balanced team.

Image source: HelloSign

Conclusion

1. Digital Transformation is a term that describes multiple effort on utilizing IT solutions to change the traditional solutions. Data Transformation focuses on better data extracting, transforming, and loading. Agile Transformation helps organizations “learn fast & learn often”.
2. The success of Digital Transformation is dependent on the maturity of data transformation and organization agility.
3. In order to make transformation happens, investing in education and training is the key to fully realize the intended results.

How do you choose between fast pace working vs. thorough analysis? What are the tips you want to share? I’m eager to learn from you.

ABC. Always be clappin’.

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Day 58 — Demystify series 6/7: “Project Agility: Working Fast & Slow”

Day 57 — Demystify series 5/7: “Design Thinking, System Thinking, Product Thinking”

The opinions expressed in this article are those of the author. They do not represent current or previous client or employer views.