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HBR: Where Digital Transformations Go Wrong (response)

Ms. Conway and Mr. Codkind make a multitude of interesting and provocative statements in the recently published HBR article on Digital Transformation.

Let me start by saying in large part I agree with many assertions they made, such as 60% of orgs think their data isn’t good enough (spoiler alert: it is), and most think the competition has the advantage because their own infrastructure isn’t set up.

To help those who insist their data isn’t good enough, we’ve provided this handy C-Suite Excuse Form you can use in your next board meeting (download PDF here).

Revene Analytics C-Suite Excuse Form

While the article does make many good points, here’s where I must object to Ms. Conway and Mr. Codkind:

YOUR FIRST STEP IS TO HIRE A DATA SCIENTIST?!?

Oh, if it were only that easy. Listen, if we could plug in an FTE and solve our digital transformation issues, we’d all be happy as clams and this article would never be written.

The truth is that Data Scientists are like electron microscopes. If you know what you’re looking for and you have a great sample ready to go – perfect. Unfortunately for most, we’re sticking a large log under a rickety 5th grade science class starter ‘scope and expecting tea leaves to be read.

The truth is that data scientists aren’t miracle workers. You can’t just hire one. Or two. Or a few.

If you’re wanting results, you need the data to be operational. The data must be put into the right format first. That’s not what data scientists do. If you’re handing a Data Scientist raw data that’s like asking a precision jeweler to pick up an axe and head into the mine to dig out some gems. It’s not what they do and a waste of their talents.

So, what’s a business to do?

You don’t have to hire a Data Scientist (or a dozen). You can scale up laterally, not internally.

Less cost, less risk, quicker, and with a bigger payoff.

How?

The Revenue Analytics Manufacturing and Distribution team is well known for our 1/3rd model. A third Data Engineers to cleanse and format the data, a third Data Scientists to drive results out of the data, and a third Strategists who understand what actions are business reasonable and what the actual business goals are. Data Scientists, as you may know, aren’t typically known for their business acumen.

The 1/3 approach allows us to act like an extension of your team – you don’t need to have an internal team to manage your pricing challenges, we can do that by working collaboratively with you, driving results from our analytics engines such as Price+, Product+, and Base+.

Okay, so what did Conway and Codkind nail?

Pricing and digital transformation is a journey – not an end goal. You don’t get to cross a magic finish line and retire. The competitive market will change, COGS will change, taxes and tariffs may arise, customers’ needs always change, heck your own offerings may even change.

The biggest mistake you can make now is delaying – but you don’t have to.

Take the first step now by starting a conversation. With a risk-free POC and money-back guarantees, what’s stopping you?

 

Jared Wiesel

Jared Wiesel is a Senior Vice President at Revenue Analytics. In this role, he serves as the practice area lead for Manufacturing and Distribution. Jared has led and executed project work across four continents with experience in multiple industries including retail, consumer goods, automotive, manufacturing, amusement and entertainment, freight, and specialty services.


Jared Wiesel is a Senior Vice President at Revenue Analytics. In this role, he serves as the practice area lead for Manufacturing and Distribution. Jared has led and executed project work across four continents with experience in multiple industries including retail, consumer goods, automotive, manufacturing, amusement and entertainment, freight, and specialty services.

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