AWS Cloud Enterprise Strategy Blog
Creating a Pathway to Innovation by Becoming Data-Driven
Are you and those in your company struggling to innovate? Are you asking how others are innovating but still not finding a mechanism to drive innovation yourself? At work, we face problems daily and are consistently working to solve those problems. So why are our problem-solving activities not converting into innovation?
As an automotive industry executive for over 20 years, I became deeply familiar with the Kaizen method and lived by its principles. Kaizen originated as a Japanese philosophy of continuous improvement in business practices. While Kaizen has proven benefits, the transformational innovation enterprises seek requires more significant change than incremental improvements.
Over the past two years, I have met with hundreds of enterprises, often discussing their ability (or inability) to innovate. From these meetings, I have learned that while there are numerous methods, one common foundational mechanism promotes innovation: a data-driven mindset and culture.
Based on this insight, my first question to anyone stating they are struggling with innovation is, “Are you using data to drive innovation?” In nearly every case, the answer is the same: no. So why and how can being data-driven lead to a company becoming more innovative?
Being data-driven is the first step. But let me work backward from innovation to illustrate the need to be data-driven and what additional abilities you need to set your organization on the path to innovation.
Innovation
Why is an enterprise, or (maybe better stated) those within an enterprise, able to innovate? Let me start by defining innovation. Innovation isn’t doing the same things better—that is the definition of Kaizen. Innovation is doing new things; its success is measured by a single large-scale change or multiple small changes that result in large-scale change.
Agility Enables Innovation
Operating with agility can feel daunting, but an organization can begin by conducting small and fast experiments, learning, and pivoting or scaling accordingly. Agility, and an agile mindset, means your organization avoids being paralyzed by current plans and promotes a willingness to change. How often do you find yourself continuing down a path based on a plan set long ago despite knowing the results are not happening as intended?
Change and disruption are constant, and companies are forced more than ever to adapt across multiple dimensions, including their values, brand, organization, people, technology, and products. According to an Accenture study, 85% of CXOs say they are not very confident their operating model can meet shifting strategic priorities.[1] A vast majority of organizations realize they must make major changes to meet their goals, so innovation is needed. To enable innovation, agility is needed.
I recently learned firsthand the importance of agility in transformation from AWS customer Kenny Chang, Executive Vice President at Korean Air. When the pandemic began, Korean Air had to ground its entire passenger fleet. At the same time, its cargo fleet was out of capacity. Between its data-driven culture and the data capabilities it created with AWS, Korean Air was able to rapidly analyze its data, making quick, confident decisions to pivot its passenger capacity to carry cargo in only eight days. Kenny said, “Being business agile was the key to making the largest profit in the 53-year history of the company.” Korean Air’s story is an inspiring example of how adapting with agility can create success.[2]
Speed Underpins Agility
Increased speed in all operations enhances an organization’s ability to be agile. I believe everyone has the motivation to move faster. That motivation may differ by individual, but we all want less friction, whether by simplifying or eliminating a task through automation. Throughout my career, I have seen that an organization’s decision-making process is nearly always a leading barrier to moving faster. At AWS, we address this with the Leadership Principle that leaders “Are Right, A Lot.” Everyone should be empowered to make decisions, but decisions need to be right a lot.
The AWS mechanism for this is to make decisions with 70% of the data we wish we had and to adapt quickly if we find the decision was wrong later. Coming from the automotive industry, I initially found it difficult to embrace this principle; the common mindset in automotive is that perfection is required out of the gate, or there will be a penalty. At AWS, I have learned that the perfection we aim for is more realistically achieved by making decisions faster and adapting rapidly when needed.
Efficiency Removes Barriers to Speed
In the automotive industry, I learned that efficiency is at the core of going faster. But in any business, finding the path of least resistance, doing more with less, and eliminating waste positively impacts your ability to increase speed. Much of what slows down business is information gathering, reporting, and the inability to find the answers to the most important decision-making questions. Powerful steps to improve an organization’s efficiency and promote speed include eliminating redundancies, obsolete activities, and KPIs; automating reporting to answer your business’s most-asked questions; and getting to the 70% of data mentioned above in real or near-real time.
Data Enables Efficiencies
The answers are in your data. Data helps you identify areas of waste that can be eliminated, creating time. Being data-driven helps you make better decisions faster, which supports a faster response to the unexpected and improves your efficiency and time to value. Knowing where to focus your resources to provide the most meaningful action is key to operating efficiently. These learnings come from solid analytics.
Descriptive and diagnostic data analytics tells you what happened and why, helping identify areas that need improvement. Real-time data helps you see what’s happening and drives quicker action. Predictive and prescriptive analytics help you see what’s coming and give insights on how to drive desired results, leading to higher levels of efficiency. If an entire organization becomes data-driven (including a robust feedback loop with a goal of learning and improvement), these efficiencies scale proportionally, compounding the positive impact.
I often hear statements from executives such as “We are not at that level yet,” or “We manufacture widgets and can’t innovate with data like digital-native companies.” But with the AWS cloud, the ability to implement a secure, flexible, and cost-effective data lake is attainable to all. As in the Korean Air case study, a data lake on AWS can help you bring all your data together to promote deeper, faster analysis and higher levels of efficiency.
Data needs an enhanced sense of urgency. Now more than ever, organizations must significantly enhance their capabilities with data to survive. An IDC study in 2020 forecasted that the amount of data created in the following three years would surpass the amount generated over the previous 30 years.[3] The opportunities to analyze and find new answers to your business problems are higher than ever—but only if you utilize data. Analytics gurus have used the phrase “Either use data or be buried by it” for many decades; the IDC study highlights the urgent need to be capable of using data as a core driver for your business.
Innovating is a complex undertaking, and there is no one simple fix. I hope I’ve provided a mental model that is practical for any organization to implement. In some cases, data itself can lead directly to innovation because it may contain the answer or solution to a problem. But for all other scenarios, a data-driven culture creates an effective cycle that enhances efficiencies and improves your organization’s ability to go fast, which improves your ability to be agile—the most natural way to improve your organization’s ability to innovate.
[1]COVID-19: Busting the myths of agile transformation, Accenture