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Industry Insight: 'I’ve Seen Many Big Data Initiatives Fail Because People Focus On The Technology Solutions, Rather Than The Business Solutions'

We talk to Miao Song, CIO, ASPAC at Johnson & Johnson

17Jan

Ahead of her presentation at the  Big Data Innovation Summit in Singapore on March 1 & 2, we spoke to Miao Song CIO, ASPAC at Johnson & Johnson.

Miao has more than 20 years of experience working in the IT industry, spanning different areas of expertise including IT operations, application development, strategic planning, IT management and governance. She has international experience from working in different locations in China, Switzerland, the Netherlands and Singapore, taking on local, regional and global senior IT management roles.

Recently, Miao was the Group CIO of Golden Agri-resources, one of the largest palm oil companies in the world. Prior to her current role, she had been with Royal Dutch Shell for more than 14 years, taking on several roles in different IT domains. Before joining Shell, she worked as ERP implementation manager for Nestle, one of the largest food companies in the world, for more than 4 years.

Can you give any examples of how data is changing Johnson & Johnson?

There have been so many changes in the last ten years in the data space. Primarily, it’s not because the volume has changed, but I think that on top of the data volume change, the structure has changed. We have talked about unstructured data, data becoming volatile, and internal and external data, but I believe beyond that, the major change is how we capture the device data, so the IOT has played a very important role in the last ten years.

The second example is to look at technology trends. In the last ten years, I believe that technology has developed tremendously. The speed of technology development was much faster than any time in the last 50 years. I will give you an example - artificial Intelligence which is now widely used for data analytics to generate insights.

We also often talk about in-memory databases, in-memory data grids, data lakes, and all the new architecture to support data. That has developed tremendously. If you look at all the vendors or the industry as a whole, no company has reduced their investment in data. In other words, everybody is focusing on data and analytics, primarily focusing on advanced data capability in the last 5 years.

Some research has even said that in the next five years, the amount of data in the world will grow tremendously. It’s not double or triple, but thousands of times more in terms of volume. How we capture the insights, how we generate insights and how we leverage data are questions for every single organization.

How have you seen the use of data change over the past 10 years?

It has changed tremendously. Johnson & Johnson has three business major sectors. We have consumer businesses, that’s our Neutrigena, baby products, and other products, we also have medical devices, and we have pharmaceutical businesses.

In all the three major sectors, data has changed them tremendously.Each enterprise is driven from the technology at some point. We are driving enterprise data analytics capability and we have developed enterprise reference architecture to support data infrastructure, so there are huge investments in data. Now we are doing what we call an enterprise data initiative, where we integrate all the sources of data together through in-memory data technology. That’s one of the examples.

Another area is that we have also developed very strong capabilities, is in data lakes, to leverage data lake technology, putting data into the cloud. We are also using data mining in the pharmaceutical space, primarily looking at clinical trial data. In the medical space and beyond we are looking at how data can be used in medical devices. We are also looking at consumer data outside the organization - we are doing work with IBM Watson and Apple to look at healthcare industry insights for example. All of this work we are doing is leading the industry. It’s why we invest heavily in this space.

There has also been an organizational culture shift as the management have really realized the value of data. The culture is really focussed around making a decision based on data and insights rather than making a decision based on experience. I have seen this cultural shift inside the organization with my own eyes.

What challenges are you currently facing when implementing data related projects?

I think there are a few things. Let me talk about this from the business perspective and from a technology stand point.

From a business perspective, we continuously drive a data-driven culture. The second challenge from a business perspective is really around data governance because we have such a huge volume of data. Our data volume is probably as big as, or perhaps even bigger than, any financial services company. The challenge is really how we make sure our business people fully take the responsibility to govern data from an end-to-end perspective, not just focusing on internal data, but also external data, which really challenges our own data governance.

The second one I see is probably bigger and bigger need for cyber security. How you secure your data, how you make sure your confidential data won’t get disclosed, that nobody is hacking into your system to grab your confidential data. I think these are the two major challenges from a business perspective.

From a technology stand point, I think that technology is changing very fast. We make sure our internal IT employees have theconfidence and skill sets to really manage data. For example, data scientist capabilities and data analytics capabilities to help the business develop insights rather than just building the solution. It’s kind of a forward thinking to focus, not only on technology solution but also having domain knowledge to generate the true insights.

I think those are the major challenges we have and we are probably not unique as a large global organization.

How do you see the use of big data in the consumer products industry changing in the next 5 years?

I think one is culture shift and the second is that there will be more utilization of external data. Taking the consumer industry as an example,I think there will be many opportunities in external data. For example, how you leverage data in social media to generate consumer insights, and how to eventually reflect that in your R&D, product development, customer behaviour analysis, artificial intelligence, and machine learning and natural language processing to really working on data. Now I think we are focusing on more in that space. Even the product design we are going to have, looking at consumer behaviour and the external data. So I think it’s gonna be more external focused rather than internal focused in the next 5 years.

In the pharmaceutical space, the volume of data continuously mined and analyzed will help to set our strategy around clinical trial data. We are also going to collaborate with institutions or research organizations more closely. It is not just in the internal data, but the whole ecosystem that has to work together. In the medical space, I think IOT data, sensor data and the data we collected from devices will be much better utilized to help the practice develop and help business model development in the next 5 years.

What can the audience expect to take away from your presentation?

I think there are a few things I want the audience to take away.

One is that when you want to drive your data initiatives, it is not just a group of people in an organization. The key thing is that the whole organization really should look at data effectively from an end-to-end perspective. In other words, when it relates to developing a solid, robust and modern technology solution. Beyond that, the culture and capabilities of an organization to extract data and generate insights is super important today and in the future.

The second one is technology which is very important for people like us, who really have to do two things:

Understand the business problems. When you drive data initiatives, you have to be aware of what business problems you are going to resolve and to have clear goals and objectives at the beginning.

I’ve seen many big data initiatives fail because people focus on the technology solutions, rather than the business solutions or business problems.

Those are the two takeaways that I want the audience to get. I believe that with more close collaboration between the real business and technology groups, we are going to drive the best value from the data within the organization. 

You can catch Miao's presentation at the Big Data Innovation Summit in Singapore on March 1 & 2.

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