There’s no such thing as digital transformation — only data transformation

Spend Matters welcomes this guest post from Stephen Day, the Chief Procurement Officer for the consulting firm Kantar, on his practitioner view of technology and data.

For the past 15 to 20 years, there have been three seismic shifts in our digital society:

• Computing power and the cost to compute have shrunk to a level that was unimaginable 50 years ago. In other words, the cost to store data, handle data and move data around has become very cheap.
• Companies are increasingly collating, abstracting and using data to a degree that has been quite unprecedented.
• There are so many applications that aid our lives that require data to run and operate.

Many people talk about digital transformation, but what does it actually mean?

When it comes to what’s going on in the world now due to these three shifts, it makes much more sense and is more meaningful to call the changes we are seeing “data transformation.”

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You might be wondering why all of this has come about and what’s changed over the course of the past several quarters that has made data transformation such a pressing issue.

For starters, everything we’re doing these days revolves around technology — computers, apps, smartphones, software, etc. All this technology shares a common denominator: the use of data to populate systems. Today, companies use data to drive business — but to use data correctly, you have to understand it. Otherwise, it’s worth absolutely nothing.

For the manual operations that still exist, this is an especially important issue, as there is virtually no easy-to-use data within these companies, and “digital transformation” targets that reality. However, whether your company is highly automated, poorly automated, low-tech or high-tech, you have to interpret, read and understand what the data is telling you.

Many companies automate the interpretation of data in a way that would cause most people to look at the result and consider it meaningless. They jump to conclusions that don’t exist in the data. So, regardless of the level of automation you apply in your company, it’s of utmost importance to interpret the data correctly and use it to guide your operations.

The good news is that the solutions built for procurement and spend analytics offer ways to extract data and make sense of it.

How data affects the supply chain

Historically, procurement data has been very static. Think of it this way: If your company uses a supplier, you ask for the supplier’s name, bank account details and contact details. Then you put that into the system, you place a purchase order and you go from there. It’s a very static process because, after you obtain the data, no one ever checks or refreshes it to make sure it’s in good shape.

That’s no longer good enough in today’s world where you may need to know whether the supplier is fiscally sound or if they have reputational issues or tax-filing problems. Is the company inclusive? Is it a woman-owned business? A veteran-owned business? Is it ethnically diverse?

The data that’s now needed to not only learn about the supplier but really understand the supply chain is quite detailed and very important. So, we need to start seeing data as something that we curate, manage and develop.

The last two years have shown several challenges that have stressed the importance of procurement data regarding the supply chain. With the onset of the pandemic, uncertainty drove the need to have different types of engagements with suppliers. The global disruption of supplier materials affected the availability and pricing of many items. Also, diversity and inclusion became a hot topic, and companies are now more concerned about their reputational impact than ever before. It’s a competitive market out there. Data allows companies to measure these issues and drive value.

The pitfall to avoid

A lot of procurement organizations see data as a one-time shot that can be left alone. This is simply not the case. There’s no use having powerful insight if you don’t have a system to review it, analyze it, make sense of it and use it.

Procurement data can be divided into three groups: spend data, commercial data (like contracts you have in place with suppliers, terms and conditions in which you do business, pricing and delivery schedules) and supplier data. Once you have that figured out, you need a plan of action and a management system that will allow you to make use of it all.

Principles for success

There are several things to keep in mind that will help you better navigate the data transformation journey:

• The right systems and tools are needed to be able to make use of the data and will vary by company.
• Mastering data management is a must to ensure the uniformity, consistency and accountability of data assets.
• Data metrics and KPIs must be aligned to your business strategy and targeted goals.
• Effective change management requires good communication to adopt new tools and processes.
• A good user experience is important to maintain engagement, usage and strong data input.
• Focus on adopting rather than adapting, because the adopting approach takes advantage of best practices and the processes of innovative systems.

Putting data to work

A good solution vendor will lure you in with a visually appealing interface that’s easy to use and hook you by using the right data to their advantage. Think of your favorite e-commerce platform. It’s probably easy to use and practically intuitive. You go on there searching for a specific deodorant and are instantly presented with it.

That’s not a coincidence — it is data put to good use, carefully curated to answer all of your questions and give you exactly what you want in a seemingly effortless fashion. And that’s really where the magic is happening.

Walmart and its transformation in response to Amazon is a great example. There is now a Walmart app where you can go online and order from the store just as quickly as you could from Amazon and, arguably, with accessibility that’s just as good. Has Walmart gone through a digital transformation, or has it simply rethought its operations and thought about how it can harness the data in its ecosystem to deliver better services? I’d say it’s the latter.

Data is a river

Trying to navigate what people mean by digital transformation is so difficult; it has become almost a brand to a lot of companies. I believe businesses that are under distress use this terminology to create a sense of panic for companies that don’t have digital transformation strategies, making them feel as though they’re missing out.

If you look at a lot of the B2B marketing that’s going on today, you’ll find these businesses writing their corporate narratives in terms of how they’re going to reinvigorate the business, and they’re talking about how they’re going to digitally transform. A lot of investors lean into that, but it doesn’t mean anything.

Think of it like this: If someone were to tell you that you’re a great athlete and good at sports, you would want to understand what sport they believed you were good at. Do they mean you’re good at football? Swimming? Some other sport?

In the same way, digital transformation is such a broad term, it means nothing at all.

If you really want to transform your business in a way that is consistent with the changes that are going on in the world right now, it’s all about how you harness data.

Curated data can instantly present us with what we want and need. Just like a river, data is constantly flowing. It’s not static or a one-time shot. It’s something you have to invest in and develop. If you look at it this way, it becomes a much more attractive proposition.

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