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Toyota Astra Motor
Digitalization with the use of digital technologies/Improving business through digital technologies
Wilbertus Darmadi
Wilbertus Darmadi, the CIO of Toyota Astra Motor has more than 26 years of experience as an IT professional in the automotive industry. His current job role as a CIO requires him to work closely with multinational stakeholders and partners to help his company boost its business performance using the latest technology.
What are some of the recent technological developments in the manufacturing industries right now?
Machine learning is particularly intriguing since we have used AI and machine learning to examine a variety of items in order to get a predictive analysis. AI and machine learning can assist us in making predictions for the proactive maintenance in factories or manufacturing, as well as in developing preventive initiatives using all the data we get and the results of past maintenance. This is thus extremely useful for us when discussing machine learning and how to build up a business to become a data-driven organization. We anticipate that every company user will be able to use the data, not just from the production side but also from cloud marketing. All the data that we now store in our data warehouse can be used for what is known as self-service analytics. We also use data visualization technologies to enable everyone to get the data they want from all the areas and do self-surface analyses independently.
What are some of the key factors that you look into while gathering or utilizing data to reach certain business goals?
When we started the data journey around five years ago, the problem was how to consolidate all the data into a single enormous data warehouse since all of the data was stored in silos at the time. We were unable to have a comprehensive end-to-end data set since each business unit has and maintains its own data.
For instance, the demand-supply division and the logistic division each have a specific job and a set of data. As a result, the data was siloed at the time. So, our initial thought was to centralize all of the data into a single data warehouse.
Next, we focused on data validation. My colleagues, for example, were struggling with data cleansing, and it had become a never-ending activity. Therefore, we used a unique strategy there and cleaned the data from the front-end input. When entering the name of a city, it is highly usual for people to use different spellings. For instance, when typing Jakarta, some people use JAKARTA while others use JKT or West Jakarta. We don't want to regularly clean that data because all of the names have the same meaning. Therefore, instead of them having to type the information manually, we provided a drop-down menu from which they can select and click. That is one illustration of how we validate data at the front end in the beginning. Since the data is already clean before it is put into the data warehouse, we are no longer concerned with the issue of cleaning data.
Our next concern was how to use the data once it had been cleaned and compiled in a data warehouse. Despite the fact that we already had smart data in our data warehouse, utilization was at a very low level at the time. When we observed that the usage was poor, we launched an initiative to enforce the data utilization, which required everyone to speak using data rather than using assumptions. Starting with the top management was the natural thing to do because when the top management encourages it, the use of data will logically increase. As a result, we began developing data-based behaviors inside our organization, which eventually necessitated the use of data. We also provided data visualization tools like Power BI to our business users. And in collaboration with HR, we created a program to teach all levels of employees how to analyze data. The data utilization has been increasing due to the widespread training we are conducting to gradually but steadily develop a data-driven organizational behavior.
Time always flies. Do not wait for the right time to start digital transformation
Do you have any advice you would want to share with your industry colleagues regarding how to approach data, how to approach technology, or how to approach digital transformation in their business?
Data is crucial when discussing digital transformation since it is a component of it. Please evaluate your company's degree of digitization before beginning the digital transformation. Step one is, to begin with, digitalization before moving on to digital transformation. Digital transformation is a process that involves the business side heavily because if we are talking about digital transformation, we are also talking about business transformation. Therefore, my recommendation is that your organization should begin the digital transition, which I believe is necessary for this day and age. Time always flies. Do not wait for the right time to start a digital transformation.
