Hello everybody, it’s great to have you for this session today.
My name is Prakash Ayer and I am a Client Partner at Cognizant and also part of Dutch
Leadership team.
I am very happy to have Joern Kruscha from Bayer with us.
Today in this conversation, we are going to discuss about the Data Modernization program
at Bayer, together with Google Cloud Platform and Cognizant.
It’s great to have here Joern, thank you so much for your time.
Hi Prakash, great to be with you today.
My name is Joern Kruscha and I am the Corp Science EMEA Data Lead.
EMEA means Europe, Middle East and Africa.
I am very fond of doing things on data and that’s what we did together with Cognizant
since last year.
Let’s get started Joern.
What is Bayer's unique approach to staying ahead of the competition?
At Bayer, we have got a vision that is driving us - “Health for all, hunger for none.”
That is the vision driving Bayer.
At the Crop Science division, we are working for farmers, helping them to produce high
quality crops.
We engage in different markets, from huge farms down to small pockets.
We have high quality products; high quality services and we want to generate high-yield
and high-quality crops.
That is where our digital journey comes into play and data can help.
We are continuing to evolve on this journey.
What is Bayer’s vision for creating a data-driven business.
And how did you set out to achieve that vision?
At Bayer, we strive to be the digital-enabled leader in the agriculture business.
Because digital drives innovation, improved decision-making, improved customer experience
and improved employee experience.
To us, “digital enabled” means “data-driven.”
For any modern company data serves as the foundation.
We already generate an abundance of data, and we need to ensure that this data is being
leveraged to the fullest extent.
We need to understand what kind of data we have got, how it links together, and how it
can generate more value, it is utmost importance to us.
That's where the FAIR principles come into the game.
FAIR meaning F- Findable, Accessible, Interoperable and Reusable
I doubt that we will see a day where all our data once resides in a single platform.
Nevertheless, bringing data together into a single platform helps to achieve all the
four FAIR principles.
That’s what we did, together with Cognizant.
We created EMEA data FAIR, we started onboarding data for four applications - we used data
sources like Salesforce, MS Dynamics, SAP ERP systems and Homebrew systems.
We linked them together in a same system and now we are really exploring new purposes because
a lot of people are interested in reusing the data.
That’s what the great story is about.
If I could ask why Google Cloud?
What unique value does Google Cloud bring to the table for Bayer in this data modernization
program?
In Crop Science we were looking for this new platform and we chose Google BigQuery.
BigQuery has built-in AI and ML functionalities.
There are also geospatial functions that Agriculture business very much relies upon, and there
was lot of trust that development is moving ahead in the right way.
For my region, EMEA, it also important that we can store data wherever we want to.
So, we are creating a space on our own locally, literally stored within the EU and everyone
knows GDPR can understand what importance that is.
While we benefit from the efforts of global team, we can setup our own space and by this
suit our regional demands.
And the flexibility from Google BigQuery is this area is key to us.
Thank you much Joern.
I am sure the audience, especially the data leaders will be able to learn a lot from these
insights.
What specific business and technology value did Cognizant bring to table for Bayer in
this program?
It’s important that we are not only ahead of all the technology but we it also meets
our organizational demands.
Sometimes, I need a partner who is not going for a super best solution but a solution that
fits into the overall organization.
And here Cognizant comes into the game.
And looking at a big company like Bayer this requires a lot of experience and even more
patience.
I want to share some statements from my team that they gave about Cognizant working with
us –
“Cognizant has deep understanding of full-stack encompassing their domains.”
“They set priorities and adjust when unexpected situations arise.”
“They very quickly understand what we mean”.
And believe me understanding what Bayer means is a tough business.”
“Finally, they respond with clarity and honesty.”
That was important for us.
Really appreciate that Joern, its always nice to hear nice words from our clients.
What will be your top three recommendations to a data leader who are embarking on a similar
data journey like yours?
First of all - value the data workers.
They have more knowledge than they are given credit for.
Focus on the value they are creating, rather than talking about the technology or quality
of data they are using.
Or let me say, don’t smirk when you see them using Microsoft Excel as the centerpiece,
just show appreciation for their results.
Second: balance between local tailoring and this goes with end user scheme, making end
user happy and the global strategy which is the single version of the truth.
You have to manage diversity; I am still seeking out on this one.
Maybe you should check ideas like inheritance or forking in this area.
Most important build on trust.
Give unconditional trust from the very start in your workers and your partners.
But this is true for any project.
Thank you so much, I am sure lot of data leaders will benefit from these learnings.
If we were to ask you to do a bit of crystal ball gazing, what do you think will be the
future of data and how might it impact organization business strategies?
I think usage of data and demands will continue to rise, its beyond the data science hype
cycle that we currently see.
So, first what out for usage of data in rather easy modes, or commonality, so paths that
are not decision sciences.
I see a lot of movement there.
And then comes the question of squeezing the knowledge out of data, we link the data together
to learn more from it.
I assume so that maybe a machine can find links between IOT sensor sending data and
customer retention.
It’s just a dream, let’s see what we can squeeze out of it.
Finally, I still have hope that we will have a data access policy that is based on information.
I doubt we have seen it in last four years.
Currently, we are doing access management again, and again and again on different technologies.
Finally, access management only relies on the content.
I would love to see that we solve this once and forever because we are taking the content
and not the technology taking into account.
Which is why, I rate access management as rather boring.
Thank you so much Joern for your time.
There are lot of insights and takeaways for this session, and I am sure our audience will
learn a lot from this.
Thank you once again for your time.
I wish you a nice day.