It’s August and I’m taking some time off this month to travel and recharge a bit. 

But I didn’t want to leave you hanging for a whole month, so I thought it would a great time to share some recent podcasts where I’ve been featured as a guest. 

First up, we have an episode on Beyond the Pipeline with Vivin Vergis, where we do a deep dive into reporting for B2B SaaS orgs. 

This is a tough, thorny, sometimes painful topic, but Vivin asked some really great questions and we explore how to tell better stories with data, create a culture of objectivity, prioritize ad-hoc requests, and a whole bunch more. 

Let’s dive in to the episode.

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In this episode of Beyond the Pipeline, host Vivin welcomes Justin Norris, Director of Marketing and BDR Operations at 360 Learning and host of the RevOpps FM podcast. Justin shares his journey into operations, transitioning from an English major to a pivotal figure in marketing operations. They dive deep into the challenges of reporting in B2B SaaS, discussing concepts like reporting fatigue, the importance of storytelling in data presentation, and handling impulsive reporting requests.

Justin emphasizes the need for a cultural shift towards objective data analysis and the role of ops in being accountable for business performance. Tune in to gain valuable insights on managing reporting requests, addressing cognitive biases, achieving a single source of truth, and avoiding reporting fatigue in B2B SaaS.

Timestamps:

[00:02] Introduction and Justin’s Journey into Operations

• Justin shares his unique path from being an English major to becoming a pivotal figure in marketing operations.

[03:32] Reporting Fatigue in B2B SaaS

• Discussion on the challenges of data overload and how reporting fatigue sets in within organizations.

[07:22] Storytelling with Data

• The importance of creating a narrative around data and how effective communication can alleviate reporting fatigue.

[08:23] Handling Impulsive Reporting Requests

• Strategies for filtering and prioritizing reporting requests from different teams to avoid unnecessary work.

[14:38] Enabling Self-Serve Reporting

• Tips on empowering teams to generate their own reports and the role of ops in making tools accessible.

[19:35] Common Reporting Tools and Their Limitations

• Comparing the effectiveness of tools like Salesforce, Looker, and Tableau for self-serve and advanced reporting needs.

[27:58] Cognitive Bias in Reporting

• Addressing the impact of biases like confirmation bias in reporting and the importance of maintaining objectivity.

[35:45] Taking Action on Data Insights

• The critical role of follow-through on data insights and establishing a feedback loop for continuous improvement.

[39:49] Achieving a Single Source of Truth

• Challenges and strategies for creating a single source of truth in organizations and the trade-offs involved.

Welcome to the seventh episode of Beyond the Pipeline podcast.

2

Today's episode is all about getting

reporting right in B2B SaaS companies.

3

We've all come a long way when it comes

to reporting, thanks to some cutting

4

edge tech out there, but like anything

else, it's not the tech, but the people.

5

People and the process behind the tech

that really determine if you're getting

6

the right data and the right insight.

7

To discuss this with me today is

Justin Norris, director of Marketing

8

Ops at 360 Learning and host of the

Match acclaim, rev Ops FM podcast.

9

This is a topic that I'm sure a lot

of you all in ops would relate to.

10

I certainly did, and it's definitely

helped me structure a lot of my

11

thinking around building reports.

12

Let's get right into it.

13

Justin, welcome to the show.

14

So glad

15

Justin Norris: to

16

Vivin Vergis: be here, Vivan.

17

Justin Norris: Thank you for having me.

18

Vivin Vergis: Yeah, my pleasure.

19

Justin, like every other episode,

I started with a question,

20

which is not really the topic.

21

And the question is very simple is how

did you end up in operations, right?

22

And it's a story that is unique

for every guest and would love

23

to hear your part as well.

24

Justin Norris: I think like

many operations folks, I

25

ended up here accidentally.

26

Uh, I I was an English major by trade and

learned fairly quickly that, uh, you've

27

limited options outside of academia with

English in terms of, you know, a set

28

career path that it prepares you for.

29

So I went into copywriting, I thought

I'd try my hand at business copywriting

30

and from there got into marketing,

was very interested in marketing.

31

The psychological aspect,

understanding customers.

32

So really grounded myself in that

and then moved into a startup where I

33

was the third employee, uh, the first

marketing hire and really wearing all

34

the hats from a marketing point of view.

35

You know, re skinned the, the

product, helped hire SDRs, tooling,

36

systems, demand gen channels.

37

So I was doing it all, which was a

great sort of bootcamp and education and

38

all of the fundamentals of marketing.

39

But I found that I kept being inclined

towards systems, you know, like

40

I just loved getting my hands on

tools, got my first Marketo instance.

41

This was, you know, well over, uh, it

was 13 years ago now, I would say, and

42

just really was, was drawn in that area.

43

Even though operations, marketing

operations, at least wasn't even a thing

44

that I could articulate at that time,

but I kind of fell into it that way.

45

And then at a certain point in time,

you know, you hit a threshold of

46

like, How much you can contribute

within the organization that you're

47

in, within the place that you're in.

48

So at that point in time I said, uh,

let me go over to the consulting side

49

and, uh, and really specialize at this,

which I did for about seven years.

50

And then at another point in time

I was like, actually now I'd like

51

to be closer to the business again.

52

So I moved back in house from there.

53

Vivin Vergis: Got it.

54

Yeah, I think I think one thing

that's common is everyone starts

55

off in a startup doing everything

where operations is just one part.

56

And that's how they

stumble upon operations.

57

And that's how I did as well,

where you end up doing everything

58

operations is just a part.

59

And then, you know, you see the amount of

gains that you can do with and actually

60

operations is One area that not really

everyone wants to get into and, you know,

61

I think it solves a lot of problems.

62

These are problems that no one else

wants to solve and you probably want to

63

get into and, you know, start looking at

tools, processes and start solving them.

64

And that's, that's what

really got me into operations.

65

Justin Norris: And how else do you know?

66

I mean, I, I do think that's the

great thing about being in a startup

67

is that, uh, You really have no

idea when you start your career, you

68

start working, like what you actually

like, you might have some thoughts.

69

Maybe some people have a set

career path, like doctor,

70

lawyer, accountant, or whatever.

71

But if you're just in this general

mix of businessy stuff, until you

72

try your hand at things, you don't

really know what you love doing.

73

And then you find those things.

74

So yeah, it's great to

have that opportunity.

75

Vivin Vergis: All right.

76

So moving on to the topic

of the day, Justin, which is

77

reporting in B2B SaaS companies.

78

And, uh, you know, I think there's

no doubt that data and reports,

79

they're paramount when it comes to

making decisions in any organization,

80

not just B2B SaaS companies.

81

But I feel like nowadays there is a lot of

data and reports are being thrown around.

82

I feel like there's almost like an

information overload or maybe, you know,

83

what we call like a reporting fatigue.

84

When do you think the sets in and

in my personal opinion, I've seen

85

this in, you know, early stage

companies where you have to go to

86

two, three tools to find your reports.

87

You have multiple.

88

Teams coming in with different

standards of reports and, uh, you don't

89

really have a single repository and

even to get the easiest of answers,

90

it becomes very difficult, right?

91

So do you see reporting

fatigue setting in?

92

And when do you think, or when

do you put a stop to generating

93

reports day in and day out?

94

Justin Norris: I don't think we can

ever stop the generating of reports,

95

but I think the way that we communicate.

96

And share that information within the

company, uh, can have a big impact

97

on that, that feeling of fatigue.

98

I'm an English major, as I said, so

I am not a person who can look at

99

a dense slide covered with KPIs and

just like, understand it instantly.

100

I can, I can find my way, but

it takes an effort for me.

101

I work with people who can

look at those dense slides and

102

be like, Oh yeah, and see it.

103

And I, I envy that ability,

um, but it takes effort for me.

104

But I, I think even for me, For most

general business consumers, that approach

105

of just like dense KPIs, slide after

slide, after slide, we go to sleep.

106

It's very boring.

107

It isn't helpful typically.

108

Uh, there's no sense of

priority or hierarchy, uh, to

109

information a lot of the time.

110

There's a long time, very well known

data thought leader, Abhinash Kaushik,

111

worked for Google, or maybe still does.

112

He talks a lot about data puking, where

you're just like, and it's sort of a

113

disgusting analogy, but it's accurate.

114

So I think the job of the skilled

analyst, or the business communicator,

115

is to create that story around the data.

116

And I almost liken it to Archaeology,

because if you think about archaeology,

117

you know, we go into the ground or we

look at all sorts of, uh, different data

118

points, ice cores, pollen samples, you

know, there's lots of different things you

119

can look at in archaeology, but you, you

start with those facts and then you need

120

to paint a picture, and if you think about

like National Geographic documentaries

121

or those sorts of documentaries that

are made for a mass audience, they do

122

a really good job Not necessarily the

accuracy of how they interpret facts I'm

123

talking about here, but just creating

a story that the average person can get

124

into and can understand, uh, or at least

that vision or that picture of the past.

125

So I think I would liken that to what the

analyst or the business communicator needs

126

to do with their data to tell that story.

127

Focus on a few core KPIs.

128

You can do a deeper dive into things to

illustrate a problem or highlight how

129

you arrived at something, but it has to

have that storytelling framework in mind.

130

And when I think of the people that I

work with that are the most effective at

131

doing this, my boss is really good at it.

132

Uh, our head of marketing.

133

Her background is product marketing,

you know, so storytelling, uh,

134

or our COO, he's from management

consulting, former McKinsey.

135

So again, very strong on communication.

136

So I think it's, that is the ability

that's critical and that can then

137

alleviate that fatigue because I think the

fatigue comes from just being bombarded

138

by numbers without context, without story.

139

Vivin Vergis: Yeah, absolutely.

140

I think that also connects to the

way an ops person grows, right?

141

Because if all you're doing is creating

reports on HubSpot and Salesforce and

142

just giving it to people to, you know,

analyze and get insights out of it, you're

143

just being the person who builds those

reports and not able to analyze them.

144

Right.

145

And I think that's also like

anyone who's out there listening.

146

I think if you're not able to analyze,

give stories out of the data that

147

you're preparing for your team.

148

I think that just keeps you

at a very low level at ops.

149

I think the next level of ops where

you need to really build is, you

150

know, creating those docs where you

really have a story built out and

151

sharing those with the consumers

of the report, mostly leadership.

152

And if they do have doubts, then

the second level could be the raw

153

data that they probably want to

dive into and get more insights on.

154

I think, yeah, I mean,

that's a great call out.

155

And I think.

156

That's something that I've learned

over the due course of time as well.

157

All right.

158

So Dustin, I think the next bit that I

really want to get to is as ops folks,

159

all of us get hit with a lot of requests

from across different teams, right?

160

Especially within marketing, especially

if you're marketing ops, you have

161

content reaching out, you may have.

162

The digital team reaching out

to you and a lot of other teams

163

reaching out to you to prove ROI

of their efforts and initiatives.

164

And that's okay, right?

165

Because as ops folks, you're the center of

the platforms and systems and reporting,

166

and that's okay for people to reach out.

167

But I feel like some reporting might

be very impulsive in nature, right?

168

Someone somewhere is probably talking

about, Hey, you know, this data

169

point would be really great to have.

170

And that data you need, or that

request immediately hits ops

171

and ops starts working on it.

172

Now these impulsive or these.

173

Reports are used.

174

One time and then never used again,

impulsive reports that are probably

175

required at that point in time and

not even looked at when the report

176

is shared as an ops person, what

are the right kind of questions you

177

should ideally be asking to filter

the requests that come through, right?

178

Is it even worth your time to

be looking at all the reporting

179

requests that comes through?

180

Justin Norris: Yeah,

that's a good question.

181

I think there's different types

of requests and it's important to

182

understand sort of what a domain of the

business or the request is related to.

183

One of the core things we all have as

a business, right, is this operational

184

rhythm of, uh, regular, repeatable

reporting, like things like funnel

185

metrics, channel performance, revenue,

that happens, you know, on a weekly,

186

bi weekly, monthly, whatever, cadence.

187

And those things should

really be standardized.

188

And they should have, you know,

the right drills so you can go

189

in deeper into the information.

190

And you don't want those things

changing too regularly because I

191

think the predictability and the

familiarity there is important.

192

So that type of reporting, I think of

it as a product in the sense that, uh,

193

it is, uh, something that ops builds

and maintains for the organization.

194

It has new features.

195

So maybe it's a feature

request for that product.

196

So in that case, it's, you know,

how important is it, how urgent

197

are we actually going to use it?

198

You know, you, you stress test it

in all those ways, uh, and should it

199

be incorporated into that product?

200

The second The way I might think about

it is, or the second sort of domain

201

that a request could relate to, in

my mind, is performance management.

202

So this is a case where

something is wrong, something

203

is broken in the revenue engine.

204

It needs to be fixed.

205

And the team is digging deeper than

usual to try to isolate that problem.

206

And this is an area where I

think, at least at the scale of

207

organization that I typically work

at, like the startup scale up.

208

Space, you want to be very reactive.

209

You don't want to stand in the way and

be, you know, you know, we're behind on

210

opportunities this month on pipeline, but

I don't think I can prioritize, you know,

211

it's, it's not a, it's not a good look.

212

It's not a good career.

213

I don't think it's the

right business decision.

214

We're behind.

215

It has to be a hands on.

216

And then, ideally, these can

become standardised over time.

217

And then, ideally, these can

become standardised over time.

218

So as you go through that routine

a few times, say, all right, if

219

performance is down, this is the

20 step process that we follow.

220

We look, you know, we navigate

down through all the different

221

layers of the funnel.

222

And so we can standardise those reports

as well and make those less ad hoc.

223

And then I guess the third domain

or the third type of request is

224

more, I think, kind of like what you

were alluding to in your question.

225

Kind of innovation type requests.

226

These are like the, the what if, or

I wonder, or we're blue skying it.

227

They're new initiatives.

228

They're new ideas.

229

And those can have a wide range of

urgency and impact associated with them.

230

Could be a report that maybe never gets

even looked at by the time it's built.

231

The person's already moved on

in their mind to something else.

232

And so you, you do need to be

really rigorous there, like

233

you said, to evaluate that.

234

And.

235

I would look at, you know, timeline.

236

Is this, is there an upcoming event?

237

And we want to pull a report of a

certain type of prospect that's at that

238

event, so that we can do some outreach.

239

And there's a very specific

need associated with it

240

that has a clear outcome.

241

Makes sense.

242

If it's just like a general, what

if, it's hard to understand, um,

243

who's asking for it plays into it.

244

Quite frankly, there's, there's always

that aspect that needs to be considered,

245

but ultimately, you know, you, you, you

perform some kind of impact analysis.

246

What decisions are we going to make?

247

What activities are we going to do?

248

As a result of that info, and

then if it can't be done right

249

away, you know, you don't have to

say no, but you can backlog it.

250

And quite often that backlogging

is a forcing function by

251

the time you get back to it.

252

So is this still relevant in the,

like, actually, no, I'm, I'm good.

253

So sometimes that allowing it to

mature a little bit can be helpful.

254

Vivin Vergis: Yeah, I got it.

255

And I think, uh, you know, to your

point where, you know, you end up.

256

Saying no, or let's say deprioritizing

it for some reason or the other, right?

257

I think enabling self serve

reporting is also a great way to

258

ensure that, I mean, it's a win win

situation for both parties, right?

259

Because one, it reduces

dependencies on ops.

260

Second, you get your data

faster to get moving, right?

261

And while, you know, self serve is

great for both the sides, I think it's

262

mostly an ops to enable that, right.

263

In order to make sure that, and, and

a lot of things, practically what I've

264

seen is people are not really good with

tools and it's not their fault, right?

265

Maybe the tool by itself is intuitive,

but the way that you've set up

266

the data architecture within the

tool might be so complex that it's

267

probably hard for people to understand

which property do I need to pull?

268

Which object is it that I need to create?

269

What kind of report types I have?

270

It becomes very difficult for a very.

271

normal person who's probably used

bare minimum of the tool to understand

272

how to create reports or how to

look at data within the tool, right?

273

So what would be, let's say, you know,

and it mostly comes down to enablement,

274

but if you do want to start, if you're

just stepping into a company, you want

275

to start enabling users to do many things

on their own, including reporting, where

276

do you start in terms of enablement?

277

Justin Norris: Yeah,

that's such a big question.

278

I mean, I agree with you

that self serve is the ideal,

279

particularly for more mature.

280

What you want to avoid.

281

I don't know if you have those, uh, self

checkout things at the grocery store,

282

you know, where they have, you have

just like a screen and as a shopper, a

283

grocery shopper, you can just like check

your own items, bag, your own items.

284

The challenge I see with those

is that they're always breaking.

285

They're never working quite well.

286

And so there's always like a store

employee there that's constantly

287

having to go between the different self

checkout things and like help people.

288

They're frustrated.

289

So it's like we're trying to self

serve, but ultimately probably

290

they're still saving some time.

291

And if you just have one

or two items, it's fine.

292

Uh, but they're not fun to use and

they're frustrating and it still

293

involves a lot of time from the employee

in that case to go around and solve

294

problems and, you know, resolve issues.

295

So you have to make sure that whatever

system you're setting up actually

296

does enable true self service.

297

And you have to know what is the

escalation point where you bring in

298

an analyst or the data team or, or

some, you know, Resource above that,

299

where the self serve isn't appropriate.

300

The few things I think about in terms

of actually enabling that to happen.

301

So number one is like, where do you do it?

302

I don't know if this is a controversial

take or not, but a lot of people like

303

to rag on Salesforce reporting, but I

think it has one of the most powerful

304

reporting engines has ever built.

305

A lot of organizations, at least the ones

that I've worked with are on Salesforce.

306

I think that is probably the ideal

starting point for, for self serve.

307

You know, I've worked with like tools like

Looker on and off for more than 10 years.

308

I've yet to see one where, uh, anyone

beyond, you know, an analyst type

309

profile, um, Could use it comfortably.

310

Just something to do with

bumping into limitations.

311

Still the interface feels technical.

312

Even most sales people or sales

leaders can create a Salesforce report.

313

Plus you're close to the data.

314

That's another key point.

315

If you ever had the experience like

looking at a report and you're like, I

316

want to see what's behind that number

and you click and like nothing happens,

317

it's a very frustrating experience.

318

Uh, and Salesforce, usually

everything is drillable.

319

You can go down to the row level.

320

You have that trust that I understand

what this data is comprised of.

321

Uh, you, users are already working there.

322

You can go into a record and take actions.

323

The gap between action and insight.

324

It's very close.

325

So I actually start there for

at least for most organizations,

326

obviously there's limitations in

terms of bringing in other data.

327

Uh, and so then there's like

the hard skills aspect, like how

328

do I build a Salesforce report?

329

And I think that's the easiest

part of the problem to solve.

330

Because there's trailhead courses,

people can learn how to do that.

331

The challenge beyond that,

and you touched on it.

332

And then the last one is understanding the

data that you're actually working with.

333

And this one is definitely, uh, well,

there's some shared responsibility,

334

but I think this is an ops problem.

335

We need to get those

irrelevant fields out there.

336

You know, most people work in a Salesforce

org that's now over 10 years old.

337

I do.

338

And.

339

Again, the archeology example, you

know, there's different layers, like

340

you can almost see fields related

to different periods of the business

341

where people had a certain idea or

vision of how they wanted to operate.

342

They created fields for that

and then they changed their

343

minds three or four years later.

344

New people came in, they

created other fields.

345

And so all that history is just there.

346

And if you're a user that's like.

347

I don't know, region or number

of employees or country.

348

Like you can have like six different

fields for each of those data points.

349

You have no idea how they're populated.

350

No idea where the data comes from.

351

No idea which one is accurate.

352

So we need to do our

job and clean that up.

353

Um, we need to ensure that

labels are up to date.

354

Like I work for a French company.

355

So some of the older fields, the

labels are actually in French.

356

I can figure it out.

357

I can translate them, but there's

significant friction there.

358

So having up to date labels, clear

nomenclature, description fields, help

359

fields, having that actually populated,

um, our team now does a great job of,

360

uh, Whenever a new field is created, they

will link in the description field back

361

to the original request so we can get all

that business context, uh, surrounding

362

that field and ultimately having a

glossary for users and then knowing how

363

to filter as well as like the next thing.

364

And this is the risk with

self serve reporting.

365

You've probably seen this too, where

like five different users, like.

366

Um, and then they're like,

Hey, my report is broken.

367

It doesn't add up.

368

And of course it's because they've

all filtered on region in a slightly

369

different way or filtered by a team

or they don't know how to identify

370

new versus repeat business in the

same way or opportunities credited to

371

marketing your sales in the same way.

372

So I think the distillation of

that is if your data is a mess.

373

Nothing works.

374

And then creating like a safe environment

where everything's kind of labeled.

375

Everything is clear, um, and then just,

you know, enabling the users on the

376

tool, which I think is the easiest part.

377

Vivin Vergis: Got it.

378

And the other thing that I would probably

add is a lot of the requests that I get is

379

from, Possibly already a report when the

request comes in, just that the person is

380

not aware that the report already exists,

that addresses the same use case, right?

381

So I think just like a data glossary,

you could probably have a report

382

defining what each report does.

383

Justin Norris: Absolutely.

384

We just, it's funny.

385

I just, uh, built.

386

That as I, my colleagues on the

sales ops side, they'd created

387

like a reporting library, which

I thought was an amazing idea.

388

Um, so we just did that for the BDR

side and yeah, it creates that clarity

389

of like, here are the list of reports.

390

Here's what we maintain.

391

Here's what we are responsible for.

392

You go and build something else.

393

That's great.

394

But we can't, we can't own

the, the accuracy of that.

395

Vivin Vergis: Yeah, got it.

396

And to your point where you were talking

about, you know, building dashboards and

397

reports out of, you know, Platforms like

local studio or tableau, you know, sure.

398

It's not something that you can double

click into and, you know, figure out

399

what's underneath the data, but do

you think at what point do you think

400

a company can move from, let's say

system related reporting, like HubSpot

401

Salesforce into a more complex system

of Snowflake, Fivetran, Tableau, you

402

know, all the SQLs, do you think it's

an upgrade or a downgrade or at what

403

maturity level Do you think a company

should probably think of moving into

404

a more complex reporting system?

405

Justin Norris: I think it probably has

still has to happen at a relatively

406

early stage because despite all the

great things that I just said about Um,

407

Salesforce reporting, you inevitably do

run into limitations, whether that's with

408

the data model or your product data that

you want to splice it with is not there.

409

And you don't necessarily want to be

pushing all of that data into Salesforce.

410

So I think it's probably as early

as you can get the skill set

411

internally to build and maintain that

infrastructure, which realistically 100

412

people, if not a little bit earlier.

413

It's never been easier

to build out that stack.

414

I mean, you can literally go in

less than a day and spin up five

415

Tran and snowflake and Tableau, um,

spend a bit of money, but you can

416

get it all going and start bringing

in data and stitching it together.

417

Like it's just never

been easier to do that.

418

And that was not the case like eight

years ago, eight or nine years ago.

419

And I remember really thinking about

like, Oh, I just, because I was in the

420

consulting side is I would love if we

could offer like a cloud based completely

421

cloud based sort of BI solution.

422

And those tools were kind of out

there, but it was not nearly as common.

423

As it is right now, but you need,

you need that maturity to be able to,

424

to be able to build those reports.

425

And so probably the way I think a

bit, if we come back to like the

426

different domains, the operational

rhythm reporting in those dashboards,

427

probably living off of the warehouse

and living in snowflake and some ad

428

hoc reporting potentially there, but

more often than not for like truly.

429

And then having a data governance

process and, and team and sort of

430

council that makes sure that the data

is clean and consistent between systems.

431

Vivin Vergis: Got it.

432

Got it.

433

And just one.

434

question is how important do you think

it is for Ops folks to know languages

435

like SQL and you know, learning

how to use visualization tools?

436

You know, I'm pretty sure there are

a lot of data analysts who's going to

437

be, you know, they're helping you out

with these, but do you think it adds

438

on to your skill as an Ops professional

to be knowing those languages?

439

Justin Norris: I mean, I, I definitely do.

440

I guess I don't think it's that important

because I don't really know SQL myself.

441

I know it like well enough that

every time I need to do something,

442

I'll go and like Google it.

443

I guess now I would use chat GPT

to write the SQL query for me.

444

So, um, but I, all those, all

those skills are an asset.

445

All those skills make

you, uh, more dangerous.

446

I think it, I think it just depends

at what level you want to work at.

447

And you may find this as the same.

448

I'm curious if you relate to this, I

guess, but I have always found that I

449

Flex to fill gaps that are around me.

450

So if we're like, Oh, we need to do this

thing and nobody knows how to do it.

451

Like, like, okay, I'll,

I will figure that out.

452

But right now I have a strong

data team that I work with.

453

I have no need and no incentive really.

454

And perhaps at the stage of the career

that I'm at, it's not like my main focus

455

to be adding that on to my, uh, my resume.

456

But yes, I absolutely think it's an

asset, but maybe, maybe it becomes less

457

necessary, perhaps with the rise of

like AI and tools and things like that,

458

where you might be able to like, yeah.

459

Structure your data with

natural language queries.

460

Vivin Vergis: Yeah.

461

Yeah.

462

Yeah.

463

I mean, absolutely relate to that part

where, you know, there is a gap that you

464

probably have to depend on some other

team to fill and, and that's something

465

that drives me to start learning.

466

I mean, I didn't know SQL until very

recently when I had to depend on

467

an agency or someone else to help

me out with certain queries, but

468

then I, every time I had to reach

out to them, it was a pain because.

469

The lead time to turn things around,

making them understand the business

470

part of, uh, what you're really trying

to achieve because they're coming

471

in only with the tech skill, right?

472

So I think the fact that you understand

the business with some skills in terms of

473

tech, I mean, might be a very basic SQL.

474

But I think it really helps you

in, you know, turn things on faster

475

and also have the context about the

business while you're, you know,

476

bringing in those technical skills.

477

Justin Norris: Necessity is

the mother of invention, right?

478

Vivin Vergis: Absolutely.

479

Yes, absolutely.

480

Right.

481

I think the next topic is something

that I've thought about quite a lot,

482

and I think I've experienced this in

my previous roles as well, is, is about

483

biases when it comes to reporting, right?

484

And these, these might not be

biases that you really want to

485

bring in, into your reports.

486

Some common kind of biases that I see

is, you know, this is, you know, and data

487

is something that is, is basically based

on who's building up the report, right?

488

If I want to prove something right, and

I think it's called the confirmation

489

bias, if I'm not wrong, but if I really

want to make sure that a campaign

490

looks pretty in the eyes of the

leadership, I can do it irrespective.

491

If the core data proves wrong, there's

always a way that you can possibly make

492

a data point look better than it is.

493

And there are different ways

to weave data around how you're

494

trying to save the story.

495

Just like you said, that you can

build a story around how your

496

campaign worked out really well.

497

Right.

498

And I've done it in my previous

role as a program manager, where I

499

wanted to make sure that, you know,

my numbers are coming out, right.

500

You're not fudging data.

501

You're not faking data,

but you could still.

502

Say it in a very different way, which

looks pretty right as an ops person,

503

I think it's very important to make

sure that you don't take sides.

504

You need to bring up the actual.

505

picture because it helps

everyone around it.

506

It helps you take the right decisions.

507

It helps the leadership understand what's

actually happening on ground, right?

508

How do you, as an ops person,

how do you make sure that

509

these biases don't creep in?

510

And how do you make sure the right

kind of data is being presented?

511

Justin Norris: Yeah, we're

all biased, like you said.

512

Right.

513

And yeah, I mean, it's so funny.

514

Look at any social, political issue today.

515

And everybody has data to support,

you know, you can find data

516

about why you should eat meat.

517

You should find data about

why you shouldn't eat meat.

518

You should find, you know, every, almost

every topic that there's people on

519

both sides and they all have their data

and they all have their data points.

520

And.

521

Yeah.

522

I think the most important thing

is cultural and it's you as an

523

Ops person can influence it, but

honestly it goes beyond just Ops.

524

It's do we have a commitment

as a company to objectivity, to

525

rationality, to understanding reality?

526

And is there an ability to Put

forward different points of view

527

and to dissent without consequences.

528

And I think if you have that, it doesn't

mean that you necessarily don't have

529

bias, but it means that you have a,

like a dialectical process through

530

which people can challenge each other.

531

Say, I don't know, this

assumption doesn't seem right.

532

What about this?

533

What about that?

534

And you can work towards a

shared and hopefully More

535

accurate picture of reality.

536

If you don't have that, uh,

culturally, you're going to be in

537

trouble because you're going to be the

person saying, well, what about this?

538

What about that?

539

And then you're going to get shut down

by the C XO, whatever, or by the CEO.

540

Who's only interested in hearing the thing

that supports her, his point of view.

541

So finding a company that has that

I think is, is really important.

542

You got to check the environment that

you work in to the extent that you can.

543

Not everybody can these days.

544

It's hard, but to the extent that you can.

545

Choose where you're going

to invest your time.

546

I feel really fortunate that, you know,

rationality is a big part of, uh, the

547

values and the work methodology where

I work doesn't mean we always agree.

548

But you're, everyone is free to

like put forward that, um, that

549

point of view and to put forward

like a fact based perspective on

550

why they see things the way they do.

551

I think the cognitive bias tends

to be in the so what, because the

552

metrics usually are pretty factual.

553

Like we have so many leads.

554

We have so many opportunities.

555

Is this good or bad?

556

Like, What are the consequences?

557

Sometimes a KPI can rise or fall and

someone may make a big deal out of

558

something and start like a fire alarm.

559

And you're like, well, actually,

if we look at it in context,

560

the drop is not meaningful, it's

not statistically significant.

561

So, reasonable people can disagree,

I think is the other thing.

562

But we need to have that, that

back and forth process to kind of

563

sharpen the sword and figure out

what truth is as much as we can.

564

Vivin Vergis: Yeah, absolutely agree.

565

I think the part of culture that you're

saying, I think the bias creeps in because

566

you're probably, you probably have an

unconscious feeling that, Hey, you know,

567

if I don't show data, which looks good for

a particular campaign, I get shot down.

568

Because of that fear, you end up

probably looking for data that

569

makes your campaign look good or

anything that basically looks good.

570

The other part is, and I've, I've kind

of felt this in, in a lot of companies

571

is about the way that ops team report the

reporting structure of ops teams, right?

572

Because when ops team is aligned

to marketing, sorry, marketing ops

573

is aligned to marketing sales ops

is aligned to sales, and you have

574

a pipeline problem where you're

probably dipping in almost all.

575

Metrics marketing comes up with

the story, which makes marketing

576

looks good saying that, Hey, you

know what, you've done this, right?

577

And I think the sales efficiency is

going down and sales ops comes with

578

a different version of the story

saying that marketing is probably not

579

giving us good quality leads, right?

580

So I think the reporting structure and

I probably don't have an answer here,

581

but I think the reporting structure for

ops teams probably falls apart there

582

where you're taking sides and maybe

that's where a central ops team or a

583

central structure where ops reports

into a CRO and then you're looking at

584

a holistic view of the organization

of the pipeline and not taking sides.

585

Do you have a comment there

in terms of structure possibly

586

taking a say in, in these devices?

587

Justin Norris: Yeah, I mean, they

absolutely, it absolutely does the

588

first thing I'll say and just your

point about like everybody wants to

589

report data that makes them look good.

590

I think that's true, but there's

a weird like career hack that I've

591

noticed where you can actually build

a lot of credibility and trust by

592

reporting data that makes you look good.

593

I don't want to say it makes you look

bad, but that isn't favorable to you.

594

Obviously you don't want to like show up

and be like, you know, I'm, I'm an idiot.

595

I don't know what I'm doing.

596

It's more just if you're running

a program and it's not going well,

597

then step being the first person to

step up and say like, we are behind.

598

Here's my analysis.

599

Here's why that builds so much trust

because everyone, if someone is just

600

constantly the good news and I can do

no wrong, are you really going to trust?

601

That person, you know, whereas if we

all know that nothing is perfect, but

602

if someone steps up to the plate and

takes accountability, accountability

603

and responsibility goes so, so far.

604

So I think, you know, building a culture

where that's normalized is great.

605

And that alleviates a lot of that

pressure to be like, I'm right.

606

I'm right.

607

We're good.

608

You're bad.

609

You know, that.

610

The very immature, uh,

behavior, in my opinion.

611

Yeah.

612

And then, you know, coming into

like how, like the different

613

teams, certainly unification helps.

614

Um, and I am, I am a big believer

in that, but I don't work in a

615

centralized op structure myself

and we don't have that problem.

616

I think because in part commitment to

rationality and then shared, uh, systems,

617

shared data models, you know, yeah.

618

If I'm reporting out of like Marketo that

has a different data model and a different

619

view of the world than what my sales

team and sales ops counterparts use, then

620

we're not going to ever see eye to eye.

621

I think when it comes to core business

metrics, we have those standardized.

622

And so at that point, there

really is one version of the

623

truth in terms of the facts, the

interpretation can vary, but I think.

624

In, in my experience, and maybe

I'm fortunate, like, uh, we

625

are hardest on our ourselves.

626

And I think that's really

how it should be rather than

627

trying to avoid accountability.

628

So again, you know, cultural, I

think a lot of it starts there.

629

The more that we, we talk about that.

630

Vivin Vergis: Got it.

631

Yeah.

632

Yeah.

633

Makes sense.

634

And I think you also alluded

to data and insights.

635

Every company has data and every

company has a team that basically

636

gets insights out of this data.

637

And it's almost like

a commodity right now.

638

And I feel like what is rare is taking

action on those insights, being able

639

to make changes based on those insights

and also create a feedback loop between

640

the data team and the team that really

needs to take action on those insights.

641

Yeah.

642

Have you been in any situations where

you ask for accountability on the

643

insights that you generate, right?

644

It can't be just that we keep

generating these insights.

645

You don't see any action.

646

You don't see any feedback loop in

terms of what has happened from those

647

insights and what more data is required

to make those insights more crisp in

648

order to, you know, make sure that

the followup action works out well.

649

Have you encountered any situation

like that or have you set up a feedback

650

loop anytime during your career?

651

Justin Norris: Yeah, definitely.

652

I think this is the single.

653

Most critical issue.

654

I mean, there's many critical issues,

but without this part, this taking

655

action, we don't have any impact.

656

It's all kind of a waste of time.

657

So it takes us to the heart of the matter.

658

And And what are the roles and

responsibilities within that process?

659

I think that prioritization is a really

important piece here, like coming back

660

to that reporting fatigue question,

because, you know, we live in this

661

universe of infinite information.

662

There's so many different data

points we could look at, and if

663

you have too many things, you

won't take action on any of it.

664

It's like, Oh, this is interesting.

665

And that's interesting.

666

And that like, you're just

kind of like wandering around.

667

Uh, one of the techniques I learned

it from my COO, but I think it's,

668

it's a technique that's around there.

669

It's this notion of a KPI tree where

you look at like, what's like the core

670

things we're trying to do as a business.

671

All right.

672

We're trying to produce revenue.

673

All right.

674

Well, what are the, the key

things that lead to revenues?

675

Like we have so many leads,

so many opportunities, so

676

many close one opportunities.

677

And then you like continue

to break those down.

678

Like, well, what leads to an opportunity?

679

It's like, well, did we

follow up with the lead?

680

Did we have a meeting?

681

Did the, they attend the meeting?

682

Did the.

683

And you keep breaking it down, breaking

it down, and you end up with all the KPIs

684

that are actually, you know, directly

related to those core things and kind

685

of a logical sequence and in a logical.

686

hierarchy.

687

Once you have identified these

are the KPIs that actually matter.

688

It doesn't mean that there's nothing

else that's potentially interesting,

689

but these are the ones that we need to

really own to make this business work.

690

Then there's an accountability process.

691

And I think we've all had the

frustrating experience of like

692

trying to do this in an ad hoc way.

693

But I think if it's structured in

the sense that where you have regular

694

meetings, where like, if you've got

to stand up in front of your peers

695

as an executive or as a leader of

some kind of manager, And say like,

696

yes, I did this, or I didn't do that.

697

That's the sort of thing

that motivates people to act.

698

Or if their boss is talking about

it in a one on one, or if they have

699

to present on it at an all hands.

700

So again, culture, building that culture

of shared accountability, and a regular

701

business readout of those Quark APIs.

702

We actually have a philosophy, Uh, to

some extent of like manual reporting,

703

which again is counterintuitive,

but like having people fill out

704

spreadsheets of, of things, it's

like, well, why we have the tool here?

705

Why not just, you know, but in doing that,

it brings people closer to their data.

706

It forces them, creates a certain friction

that you want to force people to look to

707

at certain KPIs, but yeah, there are still

frustrating situations and the functional

708

business owners need to own the action,

but I think ops can be a forcing function

709

and that's another way that ops can.

710

You know, like you said, elevate

yourself from just being like the

711

reporting desk where it's like, here's

your report, kind of like delivering

712

a pizza and being a more strategic,

more impact oriented function or

713

say, Hey, what did we do with this?

714

Is this KPI moving?

715

Are we taking this action?

716

It's a really powerful shift.

717

I found

718

Vivin Vergis: got it.

719

And I think even even when it comes

to ops teams, like you said, right, if

720

you're able to nail down your KPIs, what

matters to the business the most, and you

721

gear your insights towards those KPIs,

or those core metrics that matter, then

722

you can also prioritize your insights

or your effort and finding insights that

723

affect those outcomes the most, right?

724

Because any insight is

not worth acting upon.

725

And you might have an insight, which

is probably great, but if it doesn't

726

impact directly those core metrics or

KPIs that you're after, then you're

727

probably, you know, wasting your

effort in finding those insights.

728

So I think that's also one way

to maybe prioritize the way that

729

you look at data or the insights

that you're trying to find.

730

Justin Norris: Yeah.

731

That's great.

732

Totally true.

733

Vivin Vergis: Yeah.

734

And, and I think, uh, we definitely

be missing out, you know, especially

735

since we're talking about reporting.

736

And if you miss out on this topic,

which is the single source of truth,

737

I think everyone talks about this,

everyone chases this, but very

738

rarely have I found something finally

saying that, Hey, you know what,

739

we have a single source of truth.

740

In your experience, is

that even worth an effort?

741

Sure.

742

I mean, you probably don't want to

navigate between, you know, five

743

to six different tools to get data.

744

But honestly, I feel there's always going

to be some level of data that you probably

745

have to manually report or go through,

let's say, X number of tools to find.

746

But what's, what's the best balance there?

747

Or like you say, I mean, is, is there a

way to do this, uh, in a frictionless way?

748

Justin Norris: The answer is

probably a bit different at

749

different stages of a company, right?

750

Like I've never tried to create a single

source of truth at like a 10, 000 person

751

company or a 100, 000 person company.

752

So we're talking probably completely

different challenges in the context

753

of like a sub, sub 5, 000, sub 1, 000.

754

I don't know what the number

is, but a company of that size.

755

I think it's an achievable thing, uh,

but it kind of depends on what we mean.

756

If we mean the single source of truth

is going to answer, you know, the, be

757

the magic eight ball that answers any

question that we ever have and every

758

data point we could ever possibly

want is there and we will never

759

need to look at another source tool.

760

It's probably not realistically achievable

by which I mean like, yeah, you could

761

do it, but the cost and effort of doing

it would be way, way, way outweigh.

762

The benefit.

763

So I think coming back to like, what

are like the different domains of

764

reporting, you know, the operational

rhythm, troubleshooting, and then

765

more innovation, things that are

operational rhythm, definitely be in the

766

source of the single source of truth.

767

And again, it's never been easier

to do that on a technical level,

768

get five trend, get snowflake,

get your tableau, your looker.

769

You're off to the races, you can

pay with a credit card where it gets

770

sticky and where it gets challenging

is the definitions is the enablement

771

of people on how to use that the

rigidity of data warehouses where

772

every new question that is not already

baked in now requires data teamwork.

773

Oh, we've got to build

that into our data model.

774

We've got to write that query.

775

We've got to, you know, so with

that power comes a certain rigidity.

776

I've yet to see a system that

just can like suck in data.

777

And then provide unlimited flexibility

and like, you know, effortlessly

778

stitched together those relationships.

779

And maybe we're going to get

there, like get closer to that.

780

But today my experience, even trying

to do something as simple as blending

781

sales loft data and Salesforce data to

say like, I want to like bring in all

782

the activities and stuff from sales law.

783

And then I want to bring.

784

All the, um, all the opportunity

information from Salesforce, even that can

785

like be such a big project because there

are subtle differences and how, you know,

786

Oh, a meeting over here is like this.

787

And a meeting over here is like that.

788

APIs are not all completely

consistent or logical.

789

So, Oh, we can't filter this like this.

790

So now we've got to like suck in

everything and then go to this other

791

endpoint and get this other data

point and then filter it by that.

792

And.

793

So again, it's all doable,

but you're spending money

794

in human time by doing this.

795

So yes, a single source

of truth, but for what?

796

And you have to like, you

have to make hard choices and

797

prioritize what you want there.

798

And where you say, actually, we're just

going to report on this out of the.

799

Uh, the source, uh, system, the, the,

the, the point tool, and that's okay.

800

Vivin Vergis: All right.

801

So Justin, I think that brings

to the end of the segment.

802

We'd love to probably ask you a

few more questions, but I think

803

that's the time that we have.

804

Uh, but I'd love to have the last

segment with you, which is, uh, again,

805

it's got nothing to do with the topic,

three very random questions, uh, that

806

I haven't please feel free to answer

it in any which way you would like

807

my, my first question is basically.

808

What's the one truth that very few people

agree with you on with respect to ops?

809

Justin Norris: I don't know to what extent

people don't agree with me about this,

810

but I don't hear as many people talking

about it, uh, which is that ops should

811

be accountable for business performance.

812

And that's just something that is kind of

normalized in the culture where I work.

813

But I know that a lot of ops

teams Or I've heard this attitude

814

expressed like, well, we do X, Y, Z.

815

Like we deliver the systems

or we fulfill your tickets.

816

Uh, we give you your campaign, whether

it works or not, you know, that's sort

817

of on you and you can understand having

that separation of powers, but I think

818

that is a very limiting mindset for ops.

819

So I'm actually a big believer

that we need to be partners in

820

performance management and be

like a kind of coach and challenge

821

things where they don't make sense.

822

And have that as a part of our role.

823

Vivin Vergis: Yeah, absolutely.

824

I mean, I think tying the ops, uh,

outcomes to the business is one of

825

the biggest things that I think will

help ops understand their value and

826

obviously help the business understand.

827

How important ops is to the entire

outcome of your business, right?

828

My second question is, you know, I

think there's a lot of talk about

829

what's going to change in the next

five to 10 years, what are the new

830

technologies that are going to come out?

831

What do you think will not

change in the next five years?

832

Justin Norris: Yeah, I'm going

to go out on a limb and say that

833

I think that most teams will

still have their data as a mess.

834

In, in five years, um, it's probably

not a very bold prediction, but it's

835

not something that AI can easily fix.

836

Maybe it can help in some ways,

but, um, since AI is, is based on

837

the data that you provide into it.

838

If the underlying data itself is a mess,

you know, how, how easily can we fix that?

839

Maybe we will see some, some

improvements there, but honestly,

840

I think it's a huge challenge.

841

I think it requires discipline.

842

There's never enough resources.

843

It's hard to prioritize a

data debt payback projects.

844

Uh, so I think that we will

continue to struggle in this area.

845

Vivin Vergis: The last question, uh,

Justin, for the day is, is what quality do

846

you think is most critical for Ops folks?

847

Uh, creative thinking,

communication, speed to execution.

848

And the last time I asked this to

my guest, she also added another

849

option, which is learning to say no.

850

So which one do you think works best?

851

Justin Norris: Oh, am I allowed

to add other options too?

852

Or do I have to, do I have to push?

853

Yes, of course.

854

Vivin Vergis: I'll probably

pass it on to the next guest.

855

Justin Norris: They're, they're all, I'll

stick with your, your original three.

856

I mean, I think they're all important.

857

If I had to pick one, I would

say a communication because

858

if you can't communicate, then

none of the other things matter.

859

You can be creative as you want,

but if you can't communicate, then

860

you won't get buy into your ideas.

861

You can execute quickly, but if

you can't communicate, nobody

862

will know about it properly.

863

You won't be recognized.

864

You won't be able to get people on

board with what you're trying to do.

865

So I think communication.

866

Is a prerequisite for All of the

other things, uh, especially as

867

you move from being an individual

contributor into leadership and beyond.

868

So I'm going to pick that one.

869

Vivin Vergis: Got it.

870

Got it.

871

All right.

872

So, uh, I think that's wraps up

our, uh, time for the day, Justin.

873

Thanks a lot for doing this.

874

Thanks for the amazing insights.

875

I've personally learned a lot again.

876

Like I said, I think we could have

gone on for a longer time, but I

877

think this has to end somewhere.

878

So again, it was a privilege to

host you and, uh, yeah, I would

879

love to connect again sometime.

880

Justin Norris: Me too.

881

Thank you so much.

882

I really enjoyed it.

883

Vivin Vergis: Cheers.

884

Thanks.

885

Thanks