Intro

In the first of our interviews with data leaders on their data journey, we speak to Jennifer Agnes, CDO at Schneider Electric.

Name
Jennifer Agnes

Job Title
Chief Data Officer, Senior Vice President

Company
Schneider Electric

How did the journey of your data career start, and when did you become a data leader?

I became a data leader in practical terms back when I did portfolio management as a risk manager at GE Capital. For my portfolio reviews, inconsistencies in how the data was collected and displayed, in order to make risk decisions, bothered me.

So I started my own effort to design a standard portfolio review dashboard, with agreed definitions and calculations. Standardising figures meant I had the right metrics to know how to make investment decisions.

It’s worth noting that we used different terminology in 1996. We were doing dashboards in Lotus, and terms like ‘data leader’ hadn’t yet been coined.

I’d say I’ve been an accidental data leader since 1996. But I officially became a data leader in 2004 as part of my Six Sigma Quality Leader role, managing the GE Capital Risk Exposure Monitory Data needed for Risk reporting when Basel 2 started.

Towards the end of my time at GE Capital, and at the beginning of my time at Credit Suisse we were starting to see data leadership as a recognised field of expertise along with corresponding job titles.

Tell us about something significant that has shaped your data journey?

Key to me is that I’m an Underwriter and risk manager by trade, and it always troubled me that data was effectively being “created” and placed on PowerPoint. It needs to be consumed from the authoritative source for consistent usage across an organisation, so that it can make better decisions using high quality information to drive growth and customer satisfaction.

As part of the Six Sigma Leader role at GECC, I led the “Consistency for Growth” initiative for the Risk Teams which is where I first developed the concept of Triple A Data (AAA) Accurate, Accessible and Actionable. This was significant and is an approach I still use.

We were focused on 37 critical Risk Data Attributes at that time which were a mix of master and reference data as well as transaction data (exposure, balances, fees, payments etc.) for transaction-level risk models and efficient capital allocation as well as for internal and external reporting.

Accurate, accessible and actionable data is the data vision I use in my current role here at Schneider Electric.

What is the data related achievement that you are most proud of?

I have two – one is pretty technical and the other is more recent.

  • Under my leadership, my team led the migration of the real estate valuation system for the Commercial Real Estate business at GECC from an obsolete technology to a more modern one in 2010. The core business was to value the real estate assets, so this was a large and complex global undertaking. We transitioned out a 20-year-old system and brought in a new one, region by region over a 2-week period, which was only possible with an outstanding network of teams with a clear and common goal. It was crucial to ensure that outputs (valuations) were the same in the old tech (black box) and new tech (much more transparent). Essentially, we took out the heart of the business and put in a new one, with data and tech teams really working together, all while ensuring Business As Usual.
  • The second is here at Schneider Electric: creating the company’s first formal data strategy that gelled the vision I had established. Critical concepts include:
    – how to break down our data and team silos,
    – how to build data literacy
    – and the value of producing reusable data assets, including the essentials of master and reference data.

I literally started with a blank page – in MS Word – and it felt like writing a research paper. But it needed to be readable by a business leader, so I tried to write it with specific business cases to connect the dots. I worked intensively for several weeks, of course in collaboration with our teams here, but was nervous to share initially, wondering if it was comprehensive enough or if it was too much! Happy to say, the response has been great and it’s now adopted broadly, and starting to deliver value.

What are some typical data challenges – and some lessons you have learned along the way?

The fact is that things go wrong especially when you don’t expect it, and I’ve learned to be a good bad-news taker!

Culture is key. There is a cultural change that is required [when it comes to using data well], so that stakeholders begin to see data teams as business partners, not just IT delivery teams.

What goes wrong is missing deliverables, or not meeting stakeholder expectations – and people do tend to want everything all at once. Data is the hub of everything, so there’s always a LOT on the to do list, and often a capacity constraint. A good foundation is to get your teams and your partners to truly understand backlog and cycles (agile). One of the hardest things about the job is prioritisation.

I’ve learned that if I disappoint a key stakeholder (i.e. miss an agreed deadline due to an uncontrolled constraint), I have to own it and try to make it better by rebuilding the trust. That is why setting realistic expectations is always the first conversation; explaining the value of reusable data assets for other data consumers, and building trust is critical for this new culture – one where Data teams solve business problems not simply execute IT orders – to enable data driven decisions and succeed.

What are your 3 top tips for others looking to make a career in data?

  1. Network and trust is key – both your wider network and within the company you work at. Make friends.
  2. Be an outstanding listener. Talk business, not IT. Really learn and understand the business.
  3. “Say:Do” ratio needs to be at least 1:1. What you say, is what you do; people need to trust you.

Best advice you were given?

“I always hire people smarter than me, you should do the same”

This was from Kim Tanner [who hired Jennifer GE].

Anything final thoughts for us?

When presented with a challenge, see it as an opportunity, and always say yes – you never know where opportunities will take you. It may lead you to a career in data, or it may lead you somewhere else fabulous in life.

Curiosity is key – saying yes to challenges/opportunities will keep you learning every day and might even let you travel the world! On a personal level it is what led me to France for the first time, the second time and happily now back I’m back again for the third time.

Say yes!

 

Many thanks to Jennifer for sharing such an interesting journey with us – there is a lot in here that others will be able to relate to!

We’ll be speaking to other members of the CDO Hub, so stay tuned for our next interview coming soon.

 

Written by Tor Park

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