Iryna Bocharova
Dell
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Iryna Bocharova is in internal strategy at Dell. Her work spans everything from product strategy to go to market and innovation.
When it comes to starting research for a new project, whether that comes from a leader or quarterly goal, whatever it is, where do you start?
As a former consultant, my instincts always drive me back to my team and internal expertise.
So usually I will talk to more tenured team members within the strategy group and see if anyone has overlapped with the topic, get an idea of where our executives may stand on the issue. And then I will also try to reach out to my internal network of contacts (often other MBAs within other business units) and start getting a feel for where business units may stand.
That’s my go-to strategy.
What other types of research do you tend to leverage outside of the organization, whether primary, secondary, or otherwise, if at all?
Good question. I heavily lean on the financial sales reporting internal to the company. And I also look at third party data vendors – data on the general market and on our competition.
There's this growing consensus around different firms, where there are different altitudes and frequency of research. There's:
Big projects: We need a big answer to a big question, we might have internal data, we might have external data.
Ad hoc: I got a question, I need a quick answer, I need to get smart fast, I'm going into a meeting.
Recurring: always on, keep me smart, keep me educated.
I'm curious if that checks out. Is that sort of what you've seen in your experience? And if you lean towards one versus the other, which kind(s) are where you spend more of your time?
That's a great question. Because I rotate between different areas of strategy focus and expertise, I step into both buckets 50/50.
It really depends on what kind of requests come into my team from executives and from our leadership. It’s been mostly the bucket of quick answers: I need quick answers, I'm going into a meeting with the c-suite or we're preparing the quarterly business review meeting where we'll engage presidents of this group, and the COO will attend, and they need to have quick points of view.
So we need to back up their points of view with data and maybe they don't necessarily have someone on their staff who's readily available to pull together the data and create visuals and create a storyline.
What's the hardest type of research that, if you could wave your wand, would become that much easier for you to get done much quicker, much faster?
I’ll give you an external and internal point of view.
For the internal point of view: right now, I'm working on a project where I have to go ask around for data. And I'm struggling with the fact that there's almost one person per data point, and I need dozens of data points to put together the puzzle and put together the story.
So I kind of wish there was more cross-functional collaboration or bird's eye view in terms of who owns what, because it's taking weeks to try to track down people. It's almost like contact tracing during COVID. It's tricky.
But when it comes to the external point of view, I'm working with IDC data a lot, and I know that they get the data directly from companies.
They quality check and quality control the data. There's always probably a desire to have a more accurate view of the entire market – more accurate view of products and different price bands. The data vendor can only do so much, so the point of view that you get from external data is usually macro.
The moment you start drilling down into “I want to know something about, I don't know, the market in Germany and specifically the growing small business market. And specifically this type of form factor, this type of notebook…”? Good luck, the data will not be accurate, so you'll have to zoom out. And is that because the vendors that you're using just don't operate at that level of altitude or go to that level of nuance because they're trying to serve a lot of clients or if you were to go and dig, dig, dig, you still wouldn't find the answer.
It's hard to extrapolate what's going on there. A lot of this data is not publicly available, right? So there are companies where they can extract something out of public data, public filings. There are companies that are held privately and they're not publicly traded, so the information will not be out there, period.
What are the contracts? How they receive the data from all of those different companies, you know? There's got to be some kind of limitation on what we as competitors are willing to give the world.
Last two questions, speed round.
What's the first word that comes to mind when you think about AI in research?
Efficiency and being omniscient.
Being omniscient, that makes a lot of sense. Do you trust AI in research?
I trust and check. So I don't fully trust.
So you check?
I check. Because I see a lot of hallucination. I've used different resources and consistently every single one at some point does hallucinate.
So it feels like there needs to be a human? Someone, somewhere, making sure?
Totally, 100%.
Interesting! We'll see how the future plays out. Thanks so much for your time.