February 11, 2019 | By

AI IRL Podcast Episode 6: Big Companies Need to Be More Agile, Digital, and Analytics-Driven

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We hear a lot about digital transformation. But what does that mean? And how do you companies make changes that are transformative and not simply additive?

Sid Raisoni, the Head of Analytics at Nestle Waters, is an expert on digital transformation in big companies.

In a recent episode of AI: IRL, he unpacked what transformation truly is, an analytics-focused 5 step transformation strategy, and how employees can drive transformational change.

What is Transformation?

Transformation is a major shift in an organization’s capabilities so that it can deliver value-accretive results so that the more it does it, the more valuable it gets.  And that result must be relevant to an aligned purpose, have clarity of direction and accelerate your business.  The needs to be that the company is now able to do things it couldn’t before.

“Transformation is a major shift in an organization’s capability so that it can deliver value accretive results, relevant to and aligned purpose, that it couldn’t deliver before.”

Big companies need to realize that they must transform and turn themselves into more agile, more digital, more analytics-driven organizations.

An Analytics-focused 5 Step Transformation Strategy,

If you think about transformation from an analytics perspective, there should be a strategy put in place that follows 5 important steps:

Identify the questions whose answers fundamentally add strategic value.

Uber is a great example of this. They answered 2 fundamental questions — Where is the customer? When do they want to go?  They answered those questions through new technologies and as a result, they changed an entire industry.

Determine how existing and new data structure synthesize, get deployed, and are served?

A lot of companies struggle with legacy IT structures that don’t allow the more open, agile environment that cloud solutions are enabling today. There’s all this data and while it’s still valuable, it’s a question of:

  • what part of it’s valuable?
  • to whom?
  • how do you make it accessible to those audiences?

You don’t want to build more redundant data or just take data that’s sitting somewhere and rebuild it in another database. You also don’t want to lose what you have today because that’s what you’re running your business on.

So architecture has to be looked at, how do old and new structures synthesize and how do they get deployed and served?

Have a very well-oiled set of 3 categories of resources:

  1. Data scientists
  2. Data engineers
  3. Data translators

These are also people who sit between the scientists, engineers and the business and help translate a lot of the value back and forth. As such, you need to have a very well-oiled and refined set of resources that can do a balance of all three and can operate in a way that is constantly adding value and constantly learning and pivoting from where they are.

Rethink the business design

This is probably the toughest piece the most underfunded, but it’s critical – as this is where the value of data is used.  The value of data ultimately depends on how it’s used. If you don’t change your operating model, your process, and your way of working, then the value of data will never get realized.

In the Uber example – if the Yellow Cab companies knew what Uber knew, would they have been agile and flexible enough to meet the consumer needs? Possibly not.

So the business design has to be thought through carefully. You need a strong coalition between analytics, the business, and the value.

“The business value has to be front and center of any transformation strategy.”

Have a growth mindset.

You are not going to get everything right the first time out, so you have to have the grit and the persistence to understand that only version 2, 3, or 4 will truly be valuable.

Part of the growth mindset is failing fast and failing frequently. Being quick to try and see what works and asking the questions:

  • What did we learn?
  • What can we do in the next iteration?

However, what makes this complex is the fact that not everything can take a fail fast approach.  Some things that are mission-critical and you need to be really thoughtful about and take a more incremental approach.

Regardless of the approaches taken, the growth mindset needs to be a change from top down rather than bottom up. It needs to be part of the DNA of the organization.

How To Drive Transformational Change in Your Organization

There are 4 things you can do to help drive this transformational change in your company:

  1. Volunteer: Chances are your executive is thinking about this, and would appreciate volunteers who want to see the change.
  2. Collaborate: Transformation is about putting disparate groups of people together and helping them collaborate like never before.
  3. Build an Enterprise Capability: Understand risk and compliance, especially with data. Hire for the new world rather than the current one. Look at how to change processes to inspire transformation.
  4. Integrate AI into the workflow: Mckinsey estimates anywhere between 9.5 trillion to 15.4 trillion in value if AI is implemented on an annual basis.

This AI discussion with Sid Raisoni was taken from our podcast. If you want more AI: In Real Life.  If you want more AI: In Real Life, check out our podcast on iTunes.

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