#020: Can Data Curtail Culture and Creativity? A Corporate Conundrum!

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[00:00:25] Hi everyone. Welcome to the analytics power our digital analytics power hour. Don’t be confused with other power hours out there. This is Episode 20. Well Tim Wilson You are my cohost and I welcome you to the show. It’s good to be here Jim. Could you wait for Jim Kane. You are also my co host and I welcome you to the show as well. There it is. I feel like I’m 40 wounded from this intro that it’s like 2:00 a.m. in the morning.

[00:01:03] We’ve actually been drinking for four hours straight.

[00:01:07] Hey we want to reenact that lobby bar. We don’t say when we’re going to reenact that movie bar.

[00:01:14] So tonight we assemble my final word of analytics to discuss creativity can data curtail culture and creativity. Is it a corporate conundrum. So throughout our careers sometimes we’ll hear things like people say hey listen keep your analytics data away from my creative process. You’ll cramp my style or recently there was a big hullabaloo about a New York Times article about Amazon and specifically how Amazon using data to try to extract as much work as possible from there from their people thus creating a negative corporate culture. Because of because of data. And so tonight we’re today whatever time it is at the undetermined time period we’re going to talk about that. Let’s talk about it with disgust. Let’s rip it apart let’s crack it open and see about creativity and analytical data. Do you have to sign away your creative concepts at the crack of the data web. All right I’ll stop trying to be alliterative handed over to you guys. What do you think. What’s the what’s the relationship between being data driven and creative.

[00:02:34] Well you mean you guys know how I came to this stuff in the first place right. My background is mostly in sales and in sales people tend to use numbers and data to to get creative right. So are you going ahead your quota. Absolutely. I get numbers to prove it blah blah blah blah blah. And on the other side you know with some of the work that we do now at napkin we’re in a position where we can help people make more informed decisions at data and help them be more creative by uncovering things that you wouldn’t have seen that allow you to get it right on the first pass. And I think that those are the pros and cons to it. So you know I’ve gone into a number of organizations as a as a new analyst where they say we’re a data driven culture and we come in and they’re doing four times daily KPI reports that are six pages deep. No one actually reads them it’s death by data analysis paralysis and that stifles innovation because everybody knows you know I got to make sure nothing goes read on this page. They don’t do a good job. On the other hand when you actually have a business competing on analytics you can actually I think you’d be a lot more creative when you think about measurement and when you don’t the example that we always use at the office is that house the TV show House you know they sit down and they take everything they know and they find things out and they go to the white board and the patient almost dies. Pretty standard day napkin.

[00:03:53] Wow that’s a nice nice analogy. I almost feel like if we on this episode can come up with a handful of sound soundbites that the analysts who are in companies who get told that like I don’t want to look at the data I don’t know that analysts get told explicitly I don’t want to look at the data but I definitely know I have heard.

[00:04:18] I’m concerned that the data is going to we’re we’re a we’re a brand driven company and the data is just going to drive us to our home page is going to look like Google. And I think one I think that’s complete bullshit because to me the creatives are sometimes some of the best partners for analysts because they’re super creative but they actually want to know if their creative ideas work or not. They have more ideas than they can possibly run with. And they love to say I wonder if we could do X or wonder why it is happening and they actually would love to have the data kind of reinforce so they can actually get in a virtuous cycle with so I think is sort of where Jim was heading as well that there can be a virtuous cycle between creative independent thought ideation and the hard numbers that are testing that yes this idea seemed good but it didn’t hold up this idea seem kind of weak but it turned out it really worked. What I see happen more often is that once data gets brought in and the work getting a daily report that’s 20 pages long is 0. Now we don’t have to think now we don’t have to have we’re not supposed to have creativity. So it’s this horrible thing that is starting to permeate business. That data is giving us the answers. And so we’re not even going to ask the question.

[00:05:53] And that bothers me enormously. You know when somebody comes to me and says we should do user experience testing on our site and I say that’s great but that’s not going to give you much if you don’t know what you really want your site to do. And then they say well what does the data say that my site should do. And I kind of want to put my head through a wall because the data shouldn’t be telling you what your site should do. The data should be helping you know that out the ideas.

[00:06:24] Yeah creative effort just like data doesn’t exist in a vacuum that’s sometimes what I. I’ve heard people say that it’s like don’t get in the way of the creative process like let’s people be creative but it’s not just being creative in a vacuum. Right. There’s a reason to be creative. Right. To put stuff on your Web site.

[00:06:46] Well I worked with the guy who was a he’s a kind of a senior senior agency designer and he actually said data helps give you creative clarity because he was kind of ranting is creative.

[00:06:59] He said I hate it when some account manager or some executive comes to me and says You’re going to love this project because we just want you to do something awesome. We’re going to put no guardrails on it.

[00:07:12] Just do something cool. And he’s like they think they’re giving me a gift. And the fact is what I want to know is what is the outcome we’re trying to achieve. That gives me some guardrails that gives me the destination of going to. Now I can actually be more creative because I actually know where I’m trying to go. So he and I had a lot of fun when it came to you know the importance of figuring out what your K.P. eyes were and even in that this was an agency environment and there were people saying oh the creatives aren’t going to like working with you because you’re going to be constraining them. And I kept pointing to this guy Todd Todd use what because I’m like No he absolutely said I would love to have clarity around what I’m trying to achieve. And then I can go balls to the wall when it comes to being creative.

[00:08:03] Have you done that Xstrata before. Why. Yes I have. So the guy who was one of the original organizers I think of d’été Toronto has a guy named Patrick Galinski. I don’t think he’s Oh yeah I had piles of them a couple of months ago. Very smart dude. He did a session like four years ago or something on how to use measurement in a user experience development project. That was a really really neat session to me to go back to the original question you know are we holding back creativity. Unless I beg someone to let us play we never get involved in a new site design project. It is purely designers and technologists. There was never any data kids in the room. So if we were in a scenario where where people were so concerned about the numbers that it was allowing people to not be creative you would think that the agencies are internal build teams would invite the measurement team to the building of a million dollar website. I mean call me nuts.

[00:09:07] What you’re saying is that measurement never gets used for new design but that because there’s a fear that it will stifle creativity.

[00:09:16] I think it’s because people don’t even think to try. That’s what I’m saying is this article kind of crying wolf. Have we gotten to the point where people are actually saying well we we shouldn’t even try and launch a new Web site because you know it could change these numbers.

[00:09:33] I don’t see it but I really think there’s a there’s a school of thought that says you really should you should stop redesigning your Web site. You should just take an incremental incremental approach and just continue to refine cause. You know it’s a it’s a Web site. It’s a Web site and you can iterate your way to a functional site. I think I’ve more run into qualitative. Hey we’re doing a site redesign. We’ve done some focus groups. We’ve done some music testing. Why on earth would we want to work at the Web analytics data. And I don’t know that I hear that as a maybe it’s along the same lines of where you’re going. It just doesn’t occur to them it’s not a oh this will stifle creativity so much as it just doesn’t quite fit in.

[00:10:23] But that seems like kind of a separate separate challenge of figuring out where the data can add value.

[00:10:30] Yeah usually because that Web site data probably isn’t tied into other aspects of how they’re understanding or approaching that design.

[00:10:40] If it were that it would be a pretty pivotal piece to how they were doing that I would say Well I think focus groups and maybe usability testing winds up just naturally organizationally just tends to be a little more tightly aligned with the creative and Eurex teams. Analytics makes sure distant right.

[00:11:01] Well I mean it all depends on the organization. I think the other thing that we’re not saying so far is that you know data can also be used as its own weapon to really break some stuff and hurt people you know. So we’ve been there where you know people seize data as a political tool to get their way you know and even hoard data and hoard analysts so that nobody else can really get in there and see what’s going on. So that’s the other flipside of that. Right. That’s where I say I think data or be analytical can sometimes be a problem not a good thing.

[00:11:41] So that’s that. I think that’s what I was trying to get to before. So you know again when we look at the topic we have the word data and culture and creativity in there and I don’t think it’s Data’s fault. I think it’s companies with toxic cultures getting a hold of something else to do weaponized reporting or making people do what I want or hiding behind bullshit that I shouldn’t have done two weeks ago.

[00:12:02] I feel at the point where we should admit that the whole title was from an exhaustive analysis of past podcast’s performance that we actually had machine learning and AI generate the optimal podcast top answer.

[00:12:17] And I think there is a creativity is typecast we have not yet we have not yet achieved the singularity because it’s going to be total shit.

[00:12:26] But you know that’s you know sometimes the data lets you down.

[00:12:29] Jim makes a good point. Tim I don’t know what you’re talking about machine learning. Yeah. No one’s going to believe that we have machine learning given last episode with no less. No but I think you made a good point.

[00:12:44] Data itself is not the problem it’s the use and the way that the agendas of the people using the data or the culture around the data. That’s why as an analyst I always try to be neutral. If you own the data you’ve got to be Switzerland or whatever is a good current example of neutrality maybe that’s not a good current example just given what we’ve learned about them from bankers and chocolate and what have you.

[00:13:12] Conspiracy theory Ed.. That’s right. Well there was.

[00:13:16] I do that reminds me of that the New York Times article. And we always say we’ll post stuff on our show page. We don’t really have a show page and we forget to post links but this was the New York Times article from back in August so like a month and a half ago. And one of the notes in it was how old you’ve got these I can refuse quarterly these reviews and you’ll have like 50 or 60 pages of data. You know the people would get grilled on them and if they don’t have the data memorized and I was reading that saying what the hell can memorize 50 to 60 pages of data. And where would that possibly make sense that the rote exercise is saying I know the data because I managed to memorize it.

[00:14:01] Yeah like a lot of things in that article I don’t think most of it rang true and that was one of them. I would love that process. Nothing is better than getting a hold of a data set you understand it looking for all the outliers in it and figuring out why things happened.

[00:14:16] Well I would but I would not want to be able to recall if somebody else is sitting with 50 or 60 pages to ask me about minutia. I would want to be plodding and visualizing and digging in and asking questions and I’d want to come up with 30 questions that I wanted to ask of the data. That were 30 questions that I might be able to do something with 27 of them and they’re all creative questions creative not necessarily creative design to create. Ha. What if we did this crazy wacky thing and 27 of them wouldn’t pan out. And I had to go in and say hey I have 30 different ideas that were creative independent thought some were way out there some were incremental and I used that 50 60 pages of data and I tested every one of them.

[00:15:06] The best I could and most of them were duds and it said these were the three that are my diamonds.

[00:15:12] But that’s not how the article represented. Wow.

[00:15:15] I don’t think a lot of people are in the position that we’re in where you can do that and not get kicked out of the boardroom. So when you were talking I was thinking of the episode that we did awhile ago and it was no one to hold and no one to fold and whatever we called it. When is it time to quit. ALLEN Yep we should call it. No one to hold the wonderful them everything Grace.

[00:15:35] I think we can update the AMAs update that. But to me a scenario if you go into an organization and people say that it’s a data driven culture because it I’ve seen this a bunch before we are a data driven culture and then and then you walk in and people are saying. So you’re going to write me a report that proves that e-mail kicked ass last week right.

[00:15:55] Or I agree. That’s the terrible headline out kiss of death get out.

[00:16:00] So in essence what we’re saying is if anyone says their data driven culture runaway I have I mean a large retailer where it is emblazoned in my brain how the business got closed and the accounting came back and said you’re going to love working with these guys. They’re all about the data. They’re totally data driven. They have binders of data they showed us binders of data. The problem is they just don’t know what to do with it. And so we told them you can tell them what to do with it. And I’m like one of the plucking binders of data. Why are you printing this stuff out.

[00:16:39] Binders full of stuff really works out well.

[00:16:42] We had a catalog customer years ago and they were near coming on board we’re big on data data driven culture. And again it’s honestly it’s up when that phrase really is like oh shit here we go.

[00:16:54] Kind of phrases when you hear that but they they realize that the old IBM servers remember the old old monitors that could only be yellow blue and red. The computer that would work with their database was so old that they had to pull up the report for my analyst take a picture of it with a cell phone email them the picture.

[00:17:13] So I was like OK I guess that gets your data driven maybe.

[00:17:17] I mean honestly if you’re trying to think of the companies that are poor I’m drawing a blank now on the specific examples of ones that literally have honed in and saying nothing matters but these two things at all maybe you know Nordstrom’s take Nordstrom’s example Amazon sort of claimed it was it’s all about the customer.

[00:17:40] Nordstrom’s has had the good and the bad written about them. But I don’t necessarily think you have to have reams of data and be crunching the data all the time. There’s a level of saying are we really clear on what success is and do we have that. That’s to me a good chunk of being data driven.

[00:17:58] We know what we’ve defined what success looks like and you know if that’s someone walking around with a clipboard counting something and then once a week saying here’s how we’re doing that’s data driven and that’s if people are coming up with ideas to try out and they’re saying we’re going to try this. One thing this week and see if it moves the needle on that one set of widgets that we’re counting that’s legitimately being data driven. I think the opposite is what happens is we’ve got millions of rows and thousands of columns of data. And no one’s actually defined what success looks like which is going to lead us down.

[00:18:44] Okay success looks like profit you know fine but there’s been a large organizations there’s a there’s a gap between in that way a thousand people have to do a million different things in the end of the Year you say hey you know as will be a coin flip we did we did better or worse. So I don’t know necessarily the volume of data viewed it defines whether or not you’re actually being digitally data driven or not.

[00:19:09] I’m going to go back to the culture again you know something some companies need a real hard shake indeed is one of the places where they just aren’t able to compete. If you think about it I mean our discipline is what as like a mature ish discipline 10 15 years tops big digital is maybe 15 20 to 25. You know anything like the companies all of the ones that we work with are like 100 years old. Organizations with thousands of employees cannot move at the speed of internet. And you know some of the stuff that we do that we think is obvious is a cultural mindfuck for some of the companies that we work with except large companies.

[00:19:50] They basically. So e-commerce you know e-commerce. It’s still weird to me sometimes that e-commerce lines up in its own silo but it seems like retailers especially every single one of them said OK that guy who started up that one computer and start selling a few t shirts online and e-commerce winds up kind of divorced from the rest of the business into all of the sudden e-commerce is a hefty part of the overall PNL.

[00:20:21] And like oh crap we need to start focusing on this. And so then they have to pivot.

[00:20:26] But even outside of retail it seems like there are more and more companies that have a digital division or a digital department and they’re starting to say this area really really matters.

[00:20:41] That starts to get into the world of channel silos and omni channel and multi channel but I think there are times where that digital winds up carrying this big loadstone of your digital you have crap tons more data than we do. So therefore you are data driven and they just get kind of labeled as being data driven because they can produce gobs and gobs of reporters whether or not they’re really being data driven or not.

[00:21:11] You know I think even that’s advance. I’m not hating on big companies it’s just you know adoption of things that kind of revolutionized how you run your business are hard. And we’ve worked with some companies in the past where people in the C Suite don’t even like each other let alone have conversations about alignment on verbs. You know I think a lead means something and you do because we don’t like each other we’ll never figure that out right. I mean those are things we’re definitely a culture problem right. But then you end up in a situation where both of those people show up at a board meeting and they both have reports on leads that don’t line up and the problem has been analyzed data for each of them.

[00:21:49] Does that happen at the board level or do they not get alignment before. I mean it definitely have seen the pissing matches between my data versus your data my system versus your system showing up at a board meeting with conflicting data just seems like you’re just everybody at the bus.

[00:22:06] But that’s where the analytics data digital analytics data always gets treat. We don’t. But in most organizations they call it directional data because what happens is that’s bullshit. It doesn’t have to be it. It totally doesn’t have to be.

[00:22:21] Oh yeah let’s get a finance guy on here and he’s going to rip you a new name because you can’t bring it.

[00:22:29] You can’t ever make digital analytics data map one to one with transaction.

[00:22:35] So back that system data with Sub Sub 5 percent deviation like you can make especially for a large organization extremely accurate Business Improvement decisions.

[00:22:49] Maybe maybe 7 percent. I think you can make that.

[00:22:53] You can definitely make decisions. I mean direct. There’s nothing wrong with directional right. I remember going rounds rounds with white friends saying we got friends in our name like in a sense. I give it to them. That’s like a visionary thing.

[00:23:07] Because web analytics data is kind of messy and crappy and people want it to be precise the whole precision vs accuracy thing. Yes you have a hard number down to the penny and google analytics or Adobe analytics and that number is 5 or 10 percent off from what your system of record is. And guess what. You want to stifle creativity Chase. Closing that gap. Chase it for like a day recognize you can account for half of it and then walk away and say you know what.

[00:23:46] Because it’s directional data so I think we have our next toolbag. I mean I don’t want to totally derail this one but I think that this has been laser focus.

[00:23:57] We definitely don’t want to derail like some of the ranch spurs order order. There will be order.

[00:24:05] But you know I’ve seen reports before where the Web analytics numbers are 20 30 points off what they should be. People didn’t try and normalize them people didn’t try to see if they could make them as accurate as possible and then. But marketing uses that for the reporting and everybody goes oh it’s just marketing marketing math. I mean those are just their reports. It’s unacceptable.

[00:24:28] Well I’m not saying we need every time we need to channel Flav’s claims you know full credit for every sale and you know it’s you add up all the channels and suddenly made like 5 x the revenue that we actually made.

[00:24:42] So yeah that kind of stuff is just silly but that’s the thing is when culture fights good data usage and curation and all those things the question we should focus on going forward is I think we agree it doesn’t stifle creativity. What can someone do in an organization when data is being used in this way I think that you made a good point like when you were like let’s just put a fork in the title.

[00:25:12] Data is not stifling creativity. So let’s talk about the other. Now in their like culture can stifle creativity by using data as a weapon. Is that kind of where are. I think that’s where we’re all at right.

[00:25:25] We’ve brought up Jim Collins in the past and you know built to last. He makes the case that you can’t change culture and makes a pretty strong argument that you know a company’s culture is what it is. And again going back to as Jim was saying was it time to when is it time to leave and feeling like I have been pushing the boulder up the mountain a few times on the culture front. I wonder if the companies that are ultimately going to be successful long term are ones that have a culture that is conducive to data being used appropriately. It’s hard to say Amazon is not it. So if we point back to that six week old article there’s some things in there that do sort of make sense. And there’s a ton of creativity baked into that article.

[00:26:20] Maybe you’re doing some things right maybe doing things wrong but it’s hard to think that they’re completely abusing the use of data and using data to beat each other up in a non-productive way.

[00:26:35] But if you look at that article it’s not really about data. It’s about when you look at a development organization that isn’t running sprints properly and they’re just trying to jack the developers as hard as possible to get as much work as possible. I read that article and I really saw someone you know if we use the data in the business to make the business people run the equivalent of sprints we can grind as much work out of them as possible. I had nothing to do with data it had to do with a strong arm management tactic. To me that’s what I saw.

[00:27:09] I read that and I’d definitely Amazon’s the company I look up to. Amazon is also a company is the politically where I lean that I cringe the fact that I’m a prime member and some of their tactics and I read that and thought Wow I would literally be in their interview process and it would be a race to figure out whether they figured out faster whether I figured out the faster that I would not be a fit for that for that organization.

[00:27:35] But there there’s been a lot a lot of other articles written since that one came out that kind of debunks some of the some of the things that so I think there’s some balancing that needs to be done in terms of that article versus some of the other ones. I mean Jeff Bezos came out the day after that and basically said wow yeah are companies like that. I would quit. This is terrible.

[00:27:58] So it’s. So Tim you made a comment that wants the culture goes. There’s really nothing. So does that mean nothing you can do about it. Does that mean people should just leave when once they see like well this culture is messed up. Should they just get the heck out of Dodge.

[00:28:15] Well the point Collins makes is that there’s not a good culture and a bad culture that even if Amazon was as it exactly as it was described in the Times article that the trick is for Amazon to find enough people who thrive in that because they’ve clearly got people are based on the article there were people who had been there a long period of time and who love it and they love the fact they’re being challenged and it’s pushing them. So it’s not so much that a culture changes what he says is that a culture it may slowly and organically evolve over time but anytime somebody stands up and says we’re going to change the culture and especially if that is like the mandate for the senior management team to say change the culture. That’s the red flag that Collins would say is get out. Like look at what the culture is today. Do you like what the culture is today. And it’s binary. If the answer is yes stay if the answer is No. No matter what somebody saying about changing the culture it’s a total load of load of crap. So the culture is moving in maybe not glacial but in long cultures evolving moving perceptibly every decade or so you know they are what they are and you take something like Digital and Data popping.

[00:29:38] It’s not going to change the culture it’s whether or not the culture says we’ll based on our culture is here’s what that means for us and here’s how we’re going to use it and it seems like there are times where that clashes and it’s going to be really really frustrating for analysts who are really wanting to use data effectively. There are times where it’s like oh no the fact is the way the companies operated this just kind of falls right into it. And then you’ve got bodies that are only three years old or five years older. I mean even Amazon. 94 right. So the Amazon is 20 years old and has kind of been sort of founded on a both an operating model and a data component. So I think Amazon is using data effectively. They’re the ones that people point to from a personalization perspective. So they’ve operationalized the data it’s hard to think that would be exciting and energizing from that perspective it is baked into the culture.

[00:30:35] I would answer that one twofold depending on the type of listener that we have.

[00:30:40] So if you’re someone who’s earlier in your career and your analyst but you’re kind of lower on the org chart you’re reporting into people who are reporting into people and you are in a culture where data is weaponized it’s stifling.

[00:30:55] I think he got a you got a polish you can get out. I think if you’re in a more senior role you know you’re the director of digital measurement you’re in a situation where you can actually start to effect change. And I’m just saying cultural change I’m saying the assets tied to measurement which maybe help lead to change but whatever then you can actually do a few things. And the first one that that you can do is go out and start murdering every single standardized report that is of low value wouldn’t where that was going who were going to murder murder every display agency.

[00:31:29] Any report that is standardized that you know no one looks at it has five pages of numbers. All it does is make the analytics team look like nerds that had no value go out and turn them all off. The second thing that you can do any is data accuracy and data alignment. And we do a lot of work right now where we try and find what we call secret decoder rings or one number that exists in the digital analytics system and also exists in another tool of record. I mean it could be the order number it could be you know user ID now with Google Analytics but I’m starting to create environments where people can rapidly ask questions in different departments and have a high degree of trust in the quality of the answer in. And when you when you get those two things kind of going at once people stop getting standardized garbage reporting and people start being a little bit more agile with data that they trust across departments. We’ve really seen again I don’t want to say culture but definitely dialogue around data to keep deliberation goes away way up. And so if I was a director or a senior director or I own measurement I had a little bit of power. I try and stick it out and I do those two things actually that may be my wrap up.

[00:32:43] So there you go. Well and there you have it it may be as simple as data is important. So is culture. Don’t use one to fight the other or damage the other. There we go. Tim what about you takeaways or Wrap-Up thoughts.

[00:32:59] I feel like we kind of bounced around a bit but I think we headed into this knowing that we would bounce around a bit. I think culture is kind of an interesting topic I’m kind of fascinated by it as you know one of the things that sometimes does culture and creativity the things that I look for in the organization the things I listen for when I’m working with them there are ones that you get really excited about working with them because you say wow we’re going to have fun.

[00:33:28] We’re going to have fun with the data because you have a lot of questions. When somebody asks the question and Jim had an example earlier were data driven come in and prove that I’m right as opposed to we have a ton of questions and we think and we hope that data might help us answer some of those questions. That’s kind of the fun part because then we can start saying what. What are the questions and you’re asking the questions because you’re having independent and creative thoughts you’re looking at the site you’re looking at what people are saying about the site and you are sparking ideas in your mind and when you’re saying I have this idea. I don’t have confidence that it’s right. I wish there was a way to know that it was right. That’s kind of setting up a virtuous cycle with that data. And that is not what. Happens. I think in many many companies and to Jim’s point I think the larger and the older the company the more likely it is they’re struggling with that. And data is kind of a weapon of advancement and competition. The

[00:34:35] culture which is not going to change rapidly the degree of creativity that’s baked into the organization and the receptiveness of that creativity to validating having creativity now. I

[00:34:47] had an idea and it’s right but I had an idea. I don’t like to know if it’s right or not. It’s

[00:34:52] kind of the distinction between whether data is going to play nicely there or not I like it.

[00:34:57] So maybe we’re coming down to if you have a bad cultured don’t be data driven. What. Because you’re just you’ll just stifle creativity or fix your culture but then be data driven.

[00:35:11] If you have a bad corporate culture then go to search discovery dot com slash careers and marry someone who’s not Michael sat for once.

[00:35:20] Right. So like that’s the beauty of it. I don’t even have to say it anymore. It’s just an accepted fact in our community. I mean I hate to bring this back to a we’ve covered the topic.

[00:35:32] You know the whole careers thing Bay we’re in a sweet spot. Fight the good fight for a year for a couple of years and then step outside of it a little bit and figure out where you’re fighting the good fight that you’re going to lose after 20 years. Chances are there are opportunities and hopefully you’re going forward to the next opportunity with your eyes a little more wide open or looking for something that’s going to be a little bit more. Fun and rewarding.

[00:35:59] So I’m just started out to already just surrender to that sweet sweet paycheck. We should make stickers that say this is a data safe company and people can display it on their website. Nice. Like what. Dave how are you going to display stickers on their website. They don’t have to go every time just come to their watch or they’re going to go with travels to travel to put a sticker on their senator. All right. We’ve talked about a number of things but now we want to hear from you. Have you seen data and corporate culture curtail creativity. If you could get a sticker on your website saying this is a safe place for data would you. We’d love to hear from you. So comment on our Facebook page or on Twitter or on the measure slack.

[00:36:46] So for Tim Wilson and Tim Kaine Michael Hellblazer thanks for listening. We’ll talk to you next time.

[00:36:54] Thanks for listening. And don’t forget to join the conversation on Facebook Twitter. We welcome your comments and questions Facebook dot com slash and Onizuka now or on Twitter. Made up. Word.

[00:37:16] Makes in up a batch of those pot brownies am I right. No no no but. Fine.

[00:37:23] It’s just the way you file man. Binders full of women. I when you say. We are the data. We are the children were the ones to look for a brighter day. To review the greater good to find out more profit.

[00:37:45] No I just love being at my own heart was a reference to stop by the action. Don’t put that in the book Kill You to Death.

[00:37:57] Yeah we get a show out of that somehow you will need to cut that out.

 

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