- Digital transformation offers us the opportunity
to access an unprecedented amount of data.
Data can be used not only to transform the business,
but also to create new business models
and new business value.
So how do you think about data monetization?
Let's put it into perspective.
A quote from Daniel Keys Moran goes like this.
"You can have data without information,
"but you can't have information without data."
So let's think about it.
There are five primary ways
that you can actually use data to drive new business models.
The first is through measurable business outcomes,
using data to look for opportunities to create cost savings,
or using data to create new revenue streams.
The second one is for the benefit of doing negotiations,
so think about conditions you might create with a partner.
The third one is productizing information.
So maybe you have a new information-based offering
where you're packaging up the data as an outcome,
and you're selling that.
The fourth one is about informationalizing products.
So think about having a connected product,
and that product has data exhaust,
and you are going to give that back to the client
as part of not only the data itself, the physical object,
but the data that comes with it
to help improve a business or an offering.
The fifth one is about just selling data outright.
So think of yourself as just a pure data broker.
You probably use a lot of them in your business today,
so it's something you might be quite familiar with.
Now, a second part of being a data-driven company
and data monetization
is to actually create a governance structure.
The first thing is to actually make sure
that you can maximize the value of data as an asset.
And that means you want to minimize the amount
of data that you give away.
So what you want to do is think about creating models
around pricing it and around thinking
about how you're going to sell it.
That means that you have to start with use cases
that talk about the different aspects of value,
and think about that value
across your different business units.
So business unit A might want to sell
or use the data in one way,
and business unit B might want to sell it in another way.
Well, you need to make sure that there's no conflict.
And so you want to actually avoid cannibalization
between your two business units
and make sure that you avoid lockouts,
that is opportunity lockouts.
Now, you also want to promote transparency
of data monetization efforts across the company.
Why, that's to ensure that you aren't
actually locking out someone else's potential business
or potential revenue opportunity.
You want to set policies and processes
that need to make sure you're looking at a common viewpoint
across how you think about data, common contract language,
as well as ways to maximize that value.
So think about use case-based.
You also need to make sure
that you protect intellectual property
and ensure compliance with all regulatory requirements.
To that end, not all data is created equal,
and it is quickly becoming a commodity.
So you want to make sure
that you build your data monetization strategy
based on a sustainable business model.