Okay, so to begin, can you please state your full name? My name is Paul Harold Macklin. And your age, please. My age is 71. And where were you born? I was born in Coburg, Ontario. Where we are at the moment. And what did your parents do when you were young? My parents were farmers. Primarily, well originally they were produce farmers and then became dairy farmers and had a full herd of Holstein-Friesian cattle. Okay, and what did you do as a child for fun or did you help out? Well, as the oldest child on a farming operation, it's obviously the job to learn the trade. And so I spent my first 18 years actually being the lead hand once I was able to. Started driving vehicles at about age six. And the usual thing that happens on the farming or the farm of that day. So it was truly a family farm. Okay. And what at school, what were your favorite subjects or your strongest subjects? Or your interests? My interests, when I was in school, I think we're just general. I really, to be blunt, didn't know what I would like to do in terms of post-secondary education. And I only had one member of our family who had actually gone on to receive a university degree. So it was interesting when it came time to leave high school and determine where you were gonna go. And as a matter of fact, one of my friends actually applied for me. You can believe that. And so I got into here in college at Western, University of Western Ontario. And there I basically did an arts degree with majors in psychology and zoology. And I guess there was some interest potentially to go into medicine, but I abandoned that particular direction and went on to take a teacher's training course at Oisey and at the University of Toronto. And following that, I went out to Mississauga and at Gordon Graydon Secondary School. I had the opportunity to teach grades nine and 10 science. But I found that after a year that wasn't something that I really wanted to do. So although I guess in the end, I likely ended up being a teacher for the rest of my days, but it was not in the formal sense. And so I went to then to the University of Windsor, which was starting a law school. And I graduated from there. I came back, did my articles in Toronto and went to practice with a firm called Davies Ward and Beck. And there I practiced corporate securities law and taxation, which was something that I again quickly tired of after a couple of years, and came back out here to the country and in a rural area and practice law there for another 25 years approximately in a general way. And during that period of time, I was an advocate for various economic issues. And so I tended to be one who was promoting economic growth in our area. And after that, I suppose that maybe attracted some people to suggest that I should run for parliament. And... So there were other people's suggestions. There was other people's suggestions. This was not my, although I had been asked to run provincially a few years before and I simply declined, I just didn't see it as something that was in my pattern that I wanted to pursue. But I had a change of heart, I guess after enough people approached me and ultimately decided to run for parliament. And as luck would have it, and I do say luck because quite frankly, I think there are so many good people run for parliamentary posts. And you have to be in the right place at the right time with the right party. And that's being very blunt and I was lucky. And they reminded us of that on the day we arrived in parliament and said, realize that you're only here because you're fortunate to be in the right place at the right time. And so I found that my introduction to parliament was very, very basic. I was coming, yes, from a legal background and understanding how to use laws, but not necessarily fully appreciating how laws were created, nor appreciating possibly the way in which laws are created isn't always as pure as one would like to think. That's why they sometimes say that you don't want to know how laws and sausages are made. And it's quite true. In a majority government situation, you can get the full force of the philosophy that's being advanced, but when you come into a minority government situation, it's the story of putting water in your wine. And therefore you do get what I would call impurities in the philosophy you're trying to pursue. Others would argue that actually you're listening to the broader democratic voice and you're actually coming forward with laws that meet others' concerns more broadly. And that may be true. However, in the case of Westray, we are really talking about a majority government situation and we were able to go forward more or less to try to meet the goals that had been set out. What year did you enter office? I entered office in November of 2001. Excuse me, yeah, 2000. 2000. Yes, 2000, because 2001 came up quickly thereafter and then 2002 I did get involved in the justice ministry. Okay, and you had mentioned Westray, Westray Mining Disaster, that happened in 1992. In your words, could you say what you remember from that event or what happened? Well, when I was outside of parliament, of course, was when that occurred. But I did go back and sort of have to learn about Westray in order to properly appreciate what we were trying to do in terms of legislation. And I found it interesting because you see, here we have a person who Clifford Frame, who was the owner of Cura Resources. And he, in I think 1988, announced that he was going to open a mine in Sydney. Or Plymouth, sorry, Plymouth, Nova Scotia. And I guess the history of Plymouth was such that they'd had a number of mines there over the course of time. And yes, they'd had previous explosions because when you're mining coal, coal and methane gas are common friends in that way. So he announced that he was going to open a mine there. And so he went about trying to raise the financing. And I think part of the story is that the federal government helped finance in some respects. The provincial government of Nova Scotia helped finance in some respects. And in the end, both parties were heavily into the support of this mine. And including Nova Scotia agreeing to buy 275,000 tons of coal every year from the mine. And this was quite an economic driver in the area. And each of the parties involved were interested in the economics. I mean, obviously the federal government and the province wanted to make sure that lots of employment. And the owner obviously wanted to make sure he could make a return on his investment. And I think that all works into the theory of, well, so many of these cases where people get intertwined economically and then other issues start to develop. In this particular case, it was fairly early on that they recognized that, and I say they, being the provincial authorities, recognized that the plan for the mine wasn't going ahead exactly as they thought. And in some respects, the mine was, well, first of all, they didn't think that the miners were properly trained. They felt that there hadn't been an emergency plan put in place. They found out that very early on in this process that they were starting to mine in a direction that they hadn't previously stated they were going to do. And so all of a sudden, they're almost foretelling of what might ultimately occur. And so they started the mine in September of 1991. And once the mine opened, I guess there were some pretty early warning signs of the problems that were about to ultimately be pursued because what happened was they had a few roof falls. They had problems with, as I say, no emergency plan and the provincial authorities started to observe that this was happening. And at one point they even said they were going to pull the permit on the mine and that would be the provincial authorities. But as it went on, the next thing that seemed to be a problem in the mine was the amount of coal dust that was allowed to accumulate. And as one learns, coal dust is a very explosive type of particle once it's been suspended. And especially when you combine it with almost like an ignition stage in methane gas. So if it lights, you have this incredible potential for explosion. And in this process, I think that everyone came to the understanding that we were dealing in a very dangerous commodity. And yet at the same time, and I heard rumors personally from people later that in order to keep the mine going and to keep everything operating, that there were actually attempts at taking devices that were to stop vehicles from operating when methane gas got too high in its concentration, that they were being modified so that they could carry on and work. And that to me, I don't know whether it was fact, but certainly was rumored from people I spoke with during this process. And you could understand because everyone was caught between trying to be safe and go home at night. And yet at the same time make a living and not be shut down or find that the mine itself would close. So a lot of conflicting positions, everyone cheering for them to go forward. And yet at the same time, knowing that they were working really on a precipice, that if anything did go wrong, it would be serious consequences. And the provincial government even came along and at one point asked that they get rid of this coal dust and they called it, have it stone dusted, which was taking another aggregate ground up and it somehow minimized the amount of coal dust that would be in the air. But then the mine was only open for eight months, which is quite amazing. And then of course on May the 9th of 1992, the report is that a mining machine ignited methane gas and the methane gas then combined with the coal dust and had this enormous explosion, with 26 miners being killed and only 15 bodies ever being recovered. They finally just entombed the rest and left them there. And yet the mine manager right after the explosion was making a statement publicly that this was as safe a mine as there is. Well, I think ultimately that was proven not to be so. And once the explosion and recovery efforts were finished, the province tried to take action right away and they appointed Mr. Justice Peter Richard to take on an inquiry. Now here we are in 1992. His inquiry really never got, for various reasons, never really got rolling until I think 1995. Because again, one can only sit back and speculate as to what was going on in the politics of the day. But within a few months after the event, the provincial authorities came in and laid some 50 plus charges against mine managers and the company. And those charges weren't in place all that long because what happened was that the RCMP decided they were going to investigate criminally and they did, and they started investigating. So as soon as the RCMP had taken on the criminal investigation, it wasn't very long before the 52 provincial charges were actually dropped. And therefore the RCMP at that point was carrying the load in terms of investigation and potential criminal charges. And in 1993, the RCMP did lay criminal charges of manslaughter and criminal negligence causing death and they charged both the company and two mine managers, as I recall. And the trial on that, now we're now speaking in 1995, so it was two years after that, but the trial started and it wasn't very long before those charges were stayed because in fact there had been legal imperfections, in particular there hadn't been proper disclosure between the defense and crown. So those charges were gone. So here we are in 1995 with no provincial charges having been successfully followed through because they were withdrawn. We have the criminal charges that were thrown out by the court and now the only way we're going to find any hope of resolution and I suppose responsibility being assessed is only through Mr. Justice Richard's inquiry. So Mr. Justice Richard did carry on with his inquiry. As I say, it didn't really get going again until 1995. Now here we are, way some years from the original explosion in 1992. Now he brought out his report in 1997, so two years later. So here a tremendous period of time has passed. There has not been any resolution that's meaningful. The public and the victim's families are really very distressed at this proposition. So in 1997 when the report came out, I felt when I went back and looked, one of the most telling statements about this entire event was a quote, and I will quote Mr. Justice Peter Richard. He said, this is a story of incompetence, of mismanagement, of bureaucratic bungling, of deceit, of ruthlessness, of cover-up, of apathy, of expediency, and of cynical indifference. End of the quote. And you know, the more you study and look at the situation, you came to understand that he was so right in his assessment of what had gone on. And what that means is at the end of the day is the process that we had in place was just not effective and certainly didn't give any recourse for families to pursue. And so 1992 the explosion and its aftermath was significant. But one of his recommendations, Mr. Peter Richard was recommendation number 73 in which he really asked the government of Canada through the Department of Justice Institute of Study on accountability for corporate executives and directors for wrongful or negligent acts of a corporation and that we should introduce through the Parliament of Canada a process whereby we would modify the criminal code or other other statutes as necessary in order to make the workplace and the owners and operators of those workplaces properly accountable for workplace safety. And I think that was what really triggered, I think, a great deal of the ultimate process in Parliament. In Parliament itself, what we found was that the New Democratic Party was instrumental in working with the steelworkers, the United Steelworkers and I can't say enough about the United Steelworkers and the way in which they pursued this on behalf of their workers and the families. They were a constant in all the proceedings that I participated in Parliament. In February, I think the first of the private members' bills, this is 1999, now the report came out after Justice Richard in 1997 and in 1999 we have the first appearance of a private members' bill in the House of Commons. And the House of Commons, again, private members' bills are used quite frequently to raise awareness and to try to encourage the government but rarely do they actually go through and become law themselves or at least not frequently. So in this particular case, the NDP had over a period of time four private members' bills that came forward and in April of 1999, the Honorable Peter McKay had his motion that he brought forward. Again, everyone is trying to raise and elevate the debate on this issue and he brought forward a motion that was debated and it was to get corporate executives and directors to be held properly accountable for workplace safety. And in that, he did help in the process and this was, of course, his writing where this mind disaster had occurred. So he had a very strong interest in moving it forward. And when it was talked about and debated in the House, what were the general reactions from the rest of the House? Generally speaking, the reactions were a great deal of sympathy, a great deal of understanding as to what had gone on. I think the major concern that seemed to arise in all of the discussions and even as we worked our way into a more formal bill was a chill, I think one could say, about the corporate responsibility. I think it extended beyond just the natural resource industry. It extended into, for example, people who held volunteer positions in other organizations.  So I think the feeling that everyone got was a sense of a chill in the broader community of what this might mean. Yes, I think everyone accepted the fact that there should be more responsibility, but I believe that making responsibility more elevated in the corporate structure where people didn't necessarily control the situation but yet could be considered to be the directing mind is where the whole issue started to become a bit dicey because if you don't control the situation you don't necessarily want to be liable. But the way that you deal with that liability is to do all things that are reasonable and expected to make the workplace safe. So that was sort of a sense that was there. There was a sense though within the community and I say that community of stakeholders that there still was a need. But whether we were reaching too far was the next question. So in 2002 when I had just become the parliamentary secretary we were engaged in pursuing one of these bills that had been referred to the Justice Committee and we'd called for briefs and we'd called for witnesses and during the period of time following February of 2002 we heard some 34 witnesses and again as I say received a broad range of briefs from various interested parties and this all came together in a report and then that report was brought before the House in June of 2002 and it was a year after that before the government did eventually bring forward the bill and I guess everyone is always concerned about the passage of time but I think others are equally concerned about trying to get it right and make sure that the legislation reflects the true need and is a remedy for the situation that you see in terms of corporate mentality generally. So we took the time to get at least what we thought was right and so we introduced the bill in June of 2003 and with the introduction of the bill as luck would have it the parliament dissolved the next day so that we didn't get any further in June but when we came back in September we began our debate on the issue of the bill and it's well I guess what we'd say fundamental reform of this area of corporate liability and it was substantially fundamental because it was really changing the way in which you looked at corporations. It isn't easy to do that because we know that corporations you can't imprison you're left with the reality of dealing primarily in fines and we did introduce in the bill the concept of probation so that a corporation could be effectively put into a probationary state. The officers and members of the corporation that had control obviously were going to be asked to meet the standard that was required to keep the workplace safe. Now once we started the debate it became fairly obvious that I think despite the fact that so many years had gone by I mean we're talking a decade basically I think that a parliament itself had established yes they had their picky concerns here and there but at the end of the day one was really struck with the fact that everyone was sympathetic to the cause yes concerned as to how far it reached but in reality the bottom line was it was something that was needed it was necessary and that because the hearings had been had the report had been available for a year and the bill had been worked on to get it to that stage where we thought as a government that it was an appropriate way to address the issue. It became obvious after the debate had started that the parliament was ready to go forward with this bill they felt that it was the best they could do at this point and so it was never voted upon on a voice vote or anything of that nature but rather just adopted by parliament at its second reading and then it went to the committee committee only had it for a day returned it following that reported back to the house the house again adopted the report and that was on October the 27th when it was adopted in the house which given third reading which means it's final subject to royal assent and on onward it went to the senate and it was introduced the senate on the same day October 27 and it was interesting because the senate needless to say appeared to agree fully with what had gone on in the house and again because of the passage of time I think everyone had pretty much accepted the willingness to make a change in the law they simply had I believe only one witness which was Don Pirgoff on behalf of the justice who came before them as a witness and basically explained the entire process that had been outlined in this new bill they immediately passed it and the law was in place in November of that same year so it was an extremely short period of time when you're really from September the 15th to I think about November the 7th I guess it was when it got a final approval a very short period of time and very for most part unusual in parliamentary process but I think everyone knew that it was needed and it was therefore adopted and became the law and from it becoming the law did you see or hear of any reactions of the families or the union you had mentioned the United Steelworkers yeah well the United Steelworkers were there to say they were thrilled and once it passed the House to be fair they were excited and families we'd see family members from time to time especially during the hearings which occurred they would come forward and tell us their stories and encourage us as parliamentarians to go forward and pass legislation that they hoped in the future would stop the potential or at least deter the potential for this type of outcome and the United Steelworkers sure I remember they were so excited that I remember we got our photographs taken together it was a time of celebration really when the bill was passed in the House of Commons knowing that the Senate was likely going to approve it was seen as the victory this long sought victory after as I say more than a decade from the event itself so I think that the one looking at it I mean you think a lot of people who were involved but I think that there is no question that the United Steelworkers really deserved a lot of credit for their lobbying and their friendly support and that they were working with the families as much as possible and making sure that parliamentarians understood the true nature of what had gone on parliamentarians may be wonderful people but they don't have the knowledge that the individuals who were front and center at the time have so it is important to make sure that they do get a chance to catch up all of the details in the background and possible suggestions for how we might remedy the situation and the industry throughout the process first of all how did they participate but were they seen more as positive or combative? there was an element of combativeness and I say that in a muted sense because they were concerned and they were concerned and maybe rightfully so that this would put them at a very high degree of risk especially with respect to their upper management and directors but I don't know where you find the balance and what we were trying to always extend was to them the concept that as long as you did what was reasonable in the circumstances and most people or the so-called reasonable man would see these actions that you took as reasonable to make sure the workplace was safe then we won't necessarily hold you responsible for things that were beyond your control or that in fact would have been applied by that reasonable man test but it was hard for them to accept that so when I say combative I mean it wasn't truly combative but it was certainly argumentative and trying to press their case but in the end we have seen that there haven't been that many situations that have attracted this law since it came into force maybe a dozen instances where it's been used and overall I think that most of the concerns that were originally expressed by the corporate side have been allayed but I'm not sure that all of the volunteer organizations have necessarily accepted it as well but by the same token I don't think that people are being necessarily killed as frequently or maimed in the volunteer sector as they certainly are in the corporate sector so I think the risk just from the beginning is much more minimized and especially when you're into natural resource areas as this was and other natural resource areas I mean there's a greater risk of danger and you just have to try your very best as a good corporate citizen to minimize that When I just interviewed last week Leo Gerard who's the international president of the United Steelworkers but originally from Sudbury he had mentioned as well the Westray bill and said that if you look today there haven't been a lot of there haven't been a lot of opportunities to I guess use this law or oppose the law because in a way it seems to have become a much safer environment Well I would only differ to this extent that I still see that most of the prosecutions that are occurring are provincial or health and safety prosecutions in these events it seems to be fairly rare that they resort to the criminal level of prosecution and I just noticed the sunrise the gas explosion in the last week there were a great number of fines and so forth that were brought forward but again all of those in the end seem to be based on provincial health and safety standards and being prosecuted provincially so again it's hard to know what the right answer is I think the only thing you can say is that if you look at the fatalities in the overall I guess now a couple of decades that you sort of see that the death rate in these situations has remained relatively constant and that being said I guess one would hope that this law Bill C-45 actually did in the end encourage people to be more careful to be more thoughtful and to actually keep workplaces safe I don't think anyone ever goes into any business thinking that they aren't going to try to keep things safe but people get sloppy, they get careless and they have to be reminded and that's where you hope that inspections and provincial inspections will encourage corporations to maintain the highest standard and the threat that one can always lay before them is if you don't and anything happens do you realize what the risks are and point to the criminal law as well as the health and safety standards and I think all of us would like to be moral and upstanding but at the end of the day sometimes economics does funny things to the way in which people function and these things are not always positive and you have to have I think and all the law does is simply outline the boundaries where we think you shouldn't go and if you do go outside those boundaries then we will have an appropriate remedy for you and if you're going you can expect that the full force of the law will be brought to bear and that's the one problem about Westray I mean there were a lot of people scratching their heads and saying how could we have gone through this entire process and never ended up with anyone being successfully prosecuted when 26 people's lives were lost in a situation that was monitored and it was a new mind it was not an old mind it had historical impact I mean yes they were working on the old Ford scene which is a scene that had been mined before but this was a new proposal supposedly using good standards but I guess sometimes you can't anticipate everything and yet that's what the standard is that we expect corporate executives to follow they have to make sure that the people who are doing the day-to-day direction know the rules abide by the rules There was a case maybe a few weeks ago that came out in the paper about a man who was charged he was given jail time for the death of four workers on scaffolding Yes, yes that was metric or metric something of that nature, of that case, yes Would that apply? Would Westray build? Well, the same principles apply, yes but again, one can certainly get themselves into the full force of the law is open to anyone in those situations because that was clearly an occupational health and safety issue where in fact, number one, the individuals on that scaffolding weren't wearing appropriate protective gear, they weren't tied off the scaffolding obviously had some fundamental problem with the way in which it had been put together So that was clearly a situation that this law would have applied to, did apply to but those who prosecute make decisions on how they're going to prosecute and the there are lines of demarcation between provincial and federal prosecutions, so it just depends on, I guess, the nature of how serious is the event, what level of prosecution do they believe would be effective in sending the message to others because in some of these cases the message that you want to send is far better sent with a successful prosecution than it is trying to reach too far and have a failure of your prosecution, so in that regard again, messages are being sent yes, and the fact that you go to jail that does send the message and the problem though with finding is in some of these cases the whole purpose of having a limited company that does the work is because you're limiting the liability, so in terms of monetary fines and so forth there is a point where people will just simply walk away from the company if it doesn't have the asset value or doesn't have the amount of cash that would be required to meet the fines, then it's hard to find the right way to do it but placing a person in authority in jail who was within the corporate structure does bring home a really strong message, that's right Have you ever attempted to work on or have worked on any different laws or regulations that have to do with disasters or working conditions? Not really, no, this was likely the most important one that I dealt with and it was rewarding to see that in the end we did put a law in place that most people felt was going to be helpful in bringing public attention to those in authority, and so I think that's about all you can ever accomplish sometimes as a parliamentarian is trying to outline the boundaries of what is accepted and what is not accepted within our society Is there anything else you'd like to add today? No, well I guess at the end of the day you always say that in doing this and working through the process you learn so much as a parliamentarian and I believe that you hopefully have raised some degree of awareness within you as a parliamentarian that you will carry forward in the days when you're not in parliament and use in other ways and I will say that in looking at these human beings who lost their lives, I mean you realize that's the ultimate sacrifice that these folks have given up and for what you say and I think that's what gets you entangled in the concept of human rights generally and where you find that in going forward looking at every individual as being a valued person within society and trying to find ways to make sure that we do live up to our constitutional obligations because our charter of rights and freedoms which is entrenched within our constitution includes protecting that person and I think at the end of the day each of us really needs to be encouraged to look at every person as an extremely valuable and to do everything possible to let them live the fullest extent that they can within our country and part of that means protecting the person and I think that's if there was anything that you come away with from a parliamentary experience as we did in this Westeray Mine is we need to make sure that we don't have these disasters and that people do go home every night to their families and that they do have an economic base that's safe and secure so that they can support that family and unfortunately that's where these situations have led us into massive problems and yes they don't cease there's always someone out there seemingly making mistakes but I think that each of us should be trying to make sure that we do protect each other and simple message but I think that's really what we're trying to do and I think that Westeray at least was a huge reminder if nothing else


Hey guys, Shipper 1000 here, today I've got this McRib, now believe it or not this video is mostly for Ben because he said when he did his that I had probably had these before no, actually believe it or not Ben I've never had one of these, this is going to be my first one so actually you said they were good I got two of them now these I know you got the meal we just went down got three of them but these are I don't know so I don't know how much the meal is three forty nine a piece plus tax so I don't know why she got a medium fry with hers but she didn't get the meal I don't know why because hell that medium fry was two fifty nine so she should have got the meal I don't know why why she does things like that but anyway it's three forty nine a piece so there we go so I'm gonna give this a shot because I never had one before and my camera's crooked I'm sorry bear with me on that a little better I think okay so yeah first time never never had one before so it's a little messy but I'm gonna give it a shot here and see if it's any good here we go guys so we got pickles onions mm-hmm yeah let me get some of these onions here very good thanks for doing that review Ben because I would have never tried one I heard people talk about them can't wait till the McRib comes back and all that but um never had one I do like it two thumbs up I'm gonna I'm gonna rate that a seven and a half very good very nice yeah sorry about the traffic I'm outside because it's nice evening it's kind of gloomy it's been gloomy rainy off and on all day but it's nice how it's not really hot so I thought I'd just come out here and do my review besides monkey she went in kind of got half undressed and I didn't want her like walk out in her underwear you know and I'm still filming but so anyway yeah seven and a half very good sandwich I like it like I said it takes a lot to get me to go you know above seven I do like them so but I'll tell you what I'll tell you what I really miss about up north food wise is white castles man I'm missing so much there's there's one in Georgia it's about four hours from here Florida Georgia line right in that area when we went to the spook bridge in Georgia we on the way back we stopped at a white cast on I got I got like a shitload of them like a crave case they called it a crave case but it wasn't in the case that came in bags and they were pretty much gone by the time we got home I love them things I miss them I miss them a lot so Ben if you like white castle eat a couple for me we so there you go guys I like it it's not so much as a food review as it is my review since I never had one so but I appreciate it thanks again Ben appreciate it thanks everybody for watching keep an eye out for some some cool videos coming up so and we'll chat at you guys soon maybe I don't know maybe I might do a live stream this weekend I'm not sure I'm not sure what we're gonna do but do something right the myth man legend gone for now bye bye guys take care


Welcome to lesson five in David Wong's wooden dummy course and remember this course is designed so that you can learn with or without a wooden dummy. So let's go. In the last lesson we ended up in here, the tan-sao and low-dijun. So now the next move I'll show you in sequence. One, two, three, four, five, six, seven. Do that one more time. So we hear one, two, three, four, five, six, seven. So those are the next moves in this lesson. You want to get more amazing awesome videos like this from me. Make sure you subscribe to this channel, click the bell and get notifications for new videos coming out. Also comment and like on this video and share with friends and help support this channel so we can make more content like this for you. Let's continue with the footwork. So from the last section we ended up here. Your toes are pointed 45 degrees. Right foot is here. Left foot is slightly behind the dummy arm. So your first step is going to step about here. So around one-third the way of the box and then the back feet follows and then you take a tiny step. Then you step to the corner of this box. Then you step here. You pivot and now you're 45 degrees facing the other direction and this foot is slightly behind this dummy arm. Then you're going to step to the middle of that box and then this feet follows. Now we're pointing this direction but we're going to rotate your right foot back into the bi-jong position. So from the starting position I'm here. So one, two, three, four, five, six. So you're back here. One more time starting from here.  Now let's work on the arms. So from Tan Sao and Dai Jiang we're going to do a double gan sao. There are one sao. Then we're going to switch Tan Sao and Dai Jiang. It's just the same on the left side where we ended up in the last section. Then we can do another double gan sao. Then we do a tau sao and then we do a huan sao and Dai Jiang. From Tan Sao and Dai Jiang, double gan sao, one sao. Step Tan Sao and Dai Jiang again and then you do a double gan sao and then do a huan sao also called a kao sao and do another gan sao atop. Now you do a huan sao with this hand and Dai Jiang like this. One hand at a time. Start with your right hand only. So we started here. We're going to go step and do a high gan sao. Tiny step, do a low ban sao. Then you step over here, you pivot and you do a tan sao and then we're going to go low gan sao and then we're going to pivot the right foot in and then do a high gan sao, do a kao sao and that's it. Right hand again. Step with high gan sao. Tiny step with a low ban sao. Step to the corner of the box and as you do the pivot, do the tan sao. Then you step in the middle of the box, do a low gan sao. Then you do a high gan sao and then you do a kao sao. Now let's show you the left hand. So here starts here. This is the low gan sao. Then a kuan sao or a tan sao. Then I step over here as I pivot. Then I do the low palm. Then I step to the middle high gan sao. Then do a kuan sao and do a low palm. One, two, three, four, five, six. Let's look at the hand positions in more detail. So from the last one we ended up like this. So the tan sao, many mistakes that people make are being it too close or too far away. So you want to have an elbow low and you want to have this about 135 degrees and also the palm should be fairly flat. Another mistake that people make is they have their tan sao like this or they hand their tan sao just straight but it should be almost flat parallel to the ground. And the germ, some mistakes that people make is they open their hand, their fingers, which is not a good idea because if your finger gets caught somewhere then you might hurt your finger. So keep your fingers together like this. And the pressure is not the middle of the palm. You want to use the pressure on the lower part of this palm here. The second position is the double gan sao. So the gan sao, you always want to hit somewhere in the middle of the dummy arm in both cases and you want to hit with this part, not the upper part. So you don't want to use the wrist so to speak. You want to use this section and you want to use this section in the form. And the next one we're flipping up and then we are doing the gan sao. So same position. The gan sao is basically a high tan sao and a low bong sao. Some important points about your body position is that you are facing 45 degrees in comparison to the dummy and you need to check it so that your arms are equal distance away. So one mistake that people make is they have one too far than the other. They need to be equal distance so you can measure your elbows need to be equal distance away from you. So what you need to be aware of is to have your hips square in that direction so that your arms are equal distance. Because if your hips are turned this way then one arm is going to be too long and one arm is too short. If you turn this way, one arm is too long and one arm is too short. So you make sure your hips are square towards the front here. So next position is the same on this side as the other side. Just now you have your tan sao up here and then your low bong down here. So because of how the weight is dummy structured in this case because you're attacking your left arm will be slightly extended further than your right arm. Some mistakes that people make are they is that they don't step further and they don't step farther enough this way. They're too centered so they end up crushing their collapsing their tan sao like this. So when you're stepping make sure you step further enough so that you have enough room so that your tan sao is not collapsed. But then in not so far away that you can't reach the dummy. So that's why it's important to measure out your guide according to your body size. And usually we go by the feet size. So if you're a taller person you may need to have bigger boxes so that you step further. Now coming back here we do another one except we just reversed. Now we have a gan sao on the left and a low gan sao on the right. A low gan sao is a little bit further towards the front whereas the tan sao is more in the middle of the dummy arm. Then the next one is a very important one is the new move is called the kao sao or the hoon sao. So look at this left hand. So what's happening is I'm going to center back with my body. At the same time I am doing a circular motion with the hand as if I was trying to go around the dummy arm with my hand. I'm going to show you what's the purpose of this in a little bit. So like this. So this and then like this. So that's what's happening with the left hand. With the right hand something similar is happening. So as we go up here we're doing this. Let's do one hand at a time. So when you hear the kao sao you want to kind of be sneaky and swim your way as if you're swimming. Swimming in so that your wrist clears this dummy and then fluidly turn it into a palm like that. So fluidly turn it into a palm. Now because if you don't bring this hand in you won't be able to do the palm because the dummy is in the way. So you got to clear your hand and then do the palm. And this one here we're just doing this. So some people call this a fuk sao. Some people call this a kao sao. A slight difference is fuk sao is just weighing it downwards whereas a kao sao is actually moving it sideways. So if there's actually pressure here the dummy is going to turn that way. If it's a zhao sao it's yanking it towards me. If it's a fuk sao it's just resting there. If it's a kao sao it's actually turning it that way. So I'll explain these differences in the demonstration in a bit. Let me show you a drill that you can use to practice the double gong sao to kwan sao.  So this comes up. So what you're learning is how to replace hand over hand while you're rotating your body and pivoting at the same time. So here's a drill that you can do with a partner. Now let's say that we have two kind of protection here. You have the low bong sao but we're not going to do it down here because he's not punching me here. He's got his arm here. So with this I can block his arm and also I have a tan sao up here so I can block his arm. So I have two blocks on this arm. The drill is that he punches with the other hand. I'm going to pivot and then switch so that I also have a bong sao on this arm and also a tan sao on this arm. So he punches again. So this is a drill. I pivot and I use both hands to guide or block his punch one more time. Okay so now when I pivot I don't want to pivot so much that I'm facing all the way over there. I want to keep this fairly directed to its center line. So even though I pivoted I can still reach out and punch him in the center line. Okay do it again. So even though I'm pivoted I can still reach out and punch him in the center line. So the mistake that you could make is you punch here and then we punch straight is missing him. Okay or if I do the other way turn too much I punch straight I'm actually missing him. Okay so when I pivot I want to pivot but actually I want to pivot just enough to guide his force away but also keep center so that I can still attack his center line. So the drill you can do with the partner is pretty simple like this. You want to keep it nice and tight like that and the key is to learn how to flip this underneath and bring it up and turn. Here's the next session we're going to show you how to do the part this one and then this one and then this one. So in section four we did the ton cell low diet journey. Basically we're stepping here do the ton cell low diet journey using the opposite direction. We'll show you how to apply that in the second and then we do the double gun cell high and low gun cell then we do a cal cell with another high gun cell then we do a jet cell or another cal cell and a low palm. So let's start here we did this in lesson four but now we're just moving towards the left so he's putting pressure in here right and what I'm doing is just doing ton cell and then low palm on this side. Okay so that's pretty self-explanatory same as lesson four except now we're on this side and do ton cell and then I do a low palm this side. Okay so now we do the gun cell again but here's what here's what we want to do so now when we pivot back in okay when we pivot back in this is I'm doing a cal cell so a cal cell is here that's the wooden dummy arm I'm bringing this in opening it up with my hand and then this comes out at the same time so in the dummy form is a actually a high gun cell you can call this a jam cell or a chopping hand so so what I'm doing is actually I want to open this up and then either chop in but it's hand blocking so I rather just punch straight here okay some more time the left hand is doing this okay left hand is doing this and make sure you don't go whoa like that just enough to here because the next move is I'm going to do a low palm here so and this combines with this and then let's say his hands in the way here then I do a jet cell and I do a low palm so in the form is like this cal cell right his hands in the way then I pull this down and I do a low palm or I can do another cal cell so I can bring this open again and do a low palm so either way so I remember I showed you when when this comes up here there's actually a few things you can do you can do a cal cell which is to open it up you can do just a foot cell just to keep control of it or you can do a jet cell which is to pull it actually down or snap it down so once again you do a cal cell or a human cell to open up all right and this can actually open up and open attack or you just do a foot cell so that's so it controls his arm or you can do a jet cell which is a snap down if your foot cell you don't want to do palm because then his hands gonna block you right so if you do foot cell actually you want to do a punch or you want to do jet cell you want to do a punch okay if you do cal cell you can do a punch or palm either way because his hands all the way up there so in the form once again it's like this you have this here you open it up you jump cell his hands in the way then you do a jet cell just to control it and then you do a low palm and then you can actually repeat the exercise on this side so you can go open up here and then his hands here you can some cell right and then controls hand here the low palm I control his hand and punch it another technique you can use is the cal cell into the palm right so this is something that you might use in a fight is let's say you end up here and then you want to clear this hand without using this hand so you can actually just bring it down like that okay so I'm like this can't quite reach him or he's somehow blocked it you can actually circle it and then use that same on this hand right let's say you kind of blocked it right I can bring it down and then use that so it's a bigger motion like in the dummy we're just doing this right in the dummy we're just doing this okay but you can make a motion a little bit bigger and then turn it into palm so I'm swimming into into the palm like this swimming cool a cal cell low palm right and this hand would be like cal cell low palm so it's good if you know somebody blocks you use that energy that he blocks you with somebody blocks you use that energy that you're blocking with and then now it's totally open here right and then in the form is like boom and they can set cell and then punch if it's this time he blocks me right open up right and then I can do a punch I can do a punch pull this down and punch so let me show you that again let's say I'm on the right side you punch this he blocks then I can actually open it up and then it uses use the sinking motion and the palm snap to to go into the ribs so it's less of a it's not really like a strike because you feel that how much does that go through a little bit but then you got padding but if I just press right so instead of the energy being dispersed as an impact it gets transferred deeper in actually through all this material and into his body I'm not gonna go for his ribs I'm gonna go lower so it doesn't hurt him you can go you can go feel that right you go for the ribs or diaphragm you can break some of these ribs I've done that before so on this one the same thing I'm punching but then he's blocking me with a lot of force I can bring this down and then you can use that right and then punch or I can punch and then this is underway then I snap this one oh shit sorry now is this side punch here bring in make sure this hand is guarding I do the little palm but then I can also punch here just nap this one down and do a punch up here thanks for watching David Wong's channel on Key Life Mastery hope you enjoyed this lesson you want more lessons make sure you click the playlist of wooden dummy Wing Chun training and you can get all the lessons for free make sure you subscribe to this channel and click the like and comment if you have questions about what I taught you today make sure you add them in the comment section so until next time use the chi and prosper


Hi, everyone. Welcome to this talk by myself, Aisha Ghaffar from the Product School on how to make the leap from being a data scientist to a PM. I'm really excited to show you the content today. So let's get started. So this is what we're going to cover in our talk today. I'm going to give you a quick introduction on myself. Then we're going to talk about how you can pivot your analytic skills to transition into becoming a PM. And then we're going to go over one of the data-driven frameworks that you can apply that leverage your analytic skills and your data science skills as a product manager. So who am I? My name is Aisha Ghaffar and I'm a technical product manager on the Azure portal. The Azure portal is the front end of our cloud services from Microsoft Azure. I work on the framework that is essentially used by our internal developers to put all of their front end experiences for their cloud services, like virtual machines, app services, storage in the Azure portal. I also work on a lot of experiences that new users see like a quick start center as well as our product catalog. So it's a great opportunity for me to have experience being both a feature PM and a platform PM. If those terms don't really make sense to you right now, don't worry, we're going to get into it. But I wasn't always a product manager at Microsoft. And so I want to tell you a little bit about my career journey because that's kind of how I, that's what's inspired this talk as well as giving me a lot of lessons on how to transition from what I used to do to what I do now. So I started at Belmont University, which is a small liberal arts school in Nashville, Tennessee. I studied journalism, but I hated it and I quit and then said I decided to switch my major to finance and accounting. And so throughout my college experience, I interned at a lot of financial institutions from private equity to investment banking to a hedge fund. I also added a minor in math to help me with my thesis at the time, which was around finance. So at that time, I was completely set on like going and working on Wall Street. I wasn't even thinking about tech at the time, but in my senior year of college, I had an opportunity to do a presentation with one of the clubs that I was in that gave that essentially was a club that helped students to create their own social enterprises. So our business was a mattress recycling business, where we used to take mattresses that would normally end up in landfills, and we would and we would recycle them working with people that were coming out of incarceration. And so it would both give people employment opportunities as well as being able for us to help recycle something that would normally end up just causing waste. And we were able to sell those recycled parts. That was one of the businesses I helped came up with with my colleagues in school and my professor. And because of that, we were able to present this at a competition. And Microsoft ended up sponsoring the competition. I was talking from the finance perspective, and long story short, one of the judges at the competition, one of the judges at the competition was a CDP at Microsoft. And so they basically reached out to me through LinkedIn and asked me to come and interview, which was such a surprise because one, I thought I was going to be working at an investment bank in Nashville, but I ended up getting an opportunity to fly out to Seattle to interview. But the thing is, I wasn't interviewing for what I thought was a fancy tech job. It was actually a very esoteric role at the time, which is called sales incentive compensation. And that is essentially where you design sales plans for people in the company that are selling things. So it was a complicated role. I was learning a lot, first job out of college. But from that, I got exposure to Microsoft Azure, because at the time, all of our salespeople were selling Azure based off of a revenue, based off of both size of the contract, not off of how much people were using Azure, how much our companies were using Azure. And so I helped change the incentive structure based off of Azure consumption, which was really important for how we sold Azure to our customers and how we got our salespeople to think about how to help their customers use Azure. From that, I started to love the enterprise cloud. I then transitioned into a data scientist role. So I was this data analyst, business analyst in the sales and marketing organization working on sales plans. And then I transitioned into a data science role in an engineering group. And essentially it was called growth hacking, which was kind of like marketing, kind of like analytics, kind of like data science, in that we helped teams run experiments to help optimize their funnels. So I worked on customer acquisition, optimizing the funnel from people that are trying out Azure as trial customers and converting to paid customers. From this, I learned a lot about how we can apply data science models to these types of problems, as well as how to run robust experiments and really think about how to use, how to leverage analytics essentially in order to to grow the business. And then this was basically my pivot point into becoming a product manager. One of the ideas that one of the problems that I saw that was going on with Azure at the time was that we were having a hard time onboarding customers. And I thought that a solution to that problem would be to create an onboarding platform in the portal itself. And so as a hackathon project, I didn't have any engineering skills on my own. So as a hackathon project, I sent an email to the entire company asking, telling them about this problem, telling them about my idea for the solution, and got 12 people to sign up to join my hackathon project, because Microsoft does this yearly hackathon where people can participate in working on something that's outside of the scope of their job. And so what we all worked on, the 12 of us, was the Azure Quick Start Center. You can see the logo for this here, which was the time it was called Azure Launchpad. But then it was essentially an onboarding platform within the Azure portal. And we were able to convince the leader of the portal team to actually build it. And I got to Moonlight as a PM working on the Azure Quick Start Center. And then I eventually joined that team full-time, and then was able to take this product to GA. So that's kind of how I was able to transition from being a data scientist to a PM. That was very quick, and I'm going to go into more of the specifics of what actually worked in there. But from there, I've been on the portal team, and I have since gotten my master's in applied mathematics. And yeah, and I've been working on various different products since. I actually now work on the experimentation platform for the Azure portal, which has been a great opportunity to leverage the work that I used to do when I was a data scientist on the growth hacking team. And so that was just a little overview of me. Now I'm going to talk about how you can pivot your skills to being on PM and the lessons that I learned from that transition. So let's take a quick look and understand what is a data scientist, because I think that's going to fundamentally help us to think about how can we take what the skills of a data scientist are and then transition it into what a PM would do. So fundamentally, a data scientist's job is to extract meaning from data to better understand their business and their customers to make better decisions. So really, like data scientists, typically, they need to lay a solid data foundation, which could mean anything from making sure that the data is clean, it's concise, a lot of data wranglers, as they would be called, in order to then perform the analytics on top of that. Then data scientists use analytics experimentation and machine learning to then extract meaning from data. And then they also build data products, such as those machine learning models, personalization tools, enhance the customer experiences. So there's two areas there, or three or rather, is really making sure that you have a solid grasp of like, how can we make sure that the data that we have is accurate, reliable, usable, reproducible in a sense that I can easily get the data again to be able to run or whatever I want to do on it. Then the second aspect is being able to then use the tools that a data scientist would have in their tool belt, which is like statistics, experimentation, machine learning models, more data science, more and more it's machine learning models, but there's different tools that people can use to extract meaning from the data. One of the areas where I work with data scientists a lot, and that's what I used to do, is extract meaning from data, and then also to building data products on top of that, which are ML models. But if we think about all of that, it really boils down to creating meaning from chaos and generating actionable outcomes. I want you to remember that, that creating meaning from chaos and generating actionable outcomes, because that's going to be key into what a PM does. So now we're switching to what is a product manager. So fundamentally, a product manager's job is to make decisions and execute. So before we're talking about creating meaning from chaos and creating actionable outcomes, the similar thing here is being able to then make decisions and execute. So a product manager's job is they're responsible for understanding customers' desires, needs, and problems, and working with the different disciplines to turn an idea for a solution into a reality. The ones that are the best are the ones that can make the best decisions and execute. How do you make the best decisions? You make the best decisions with having a clear understanding of all these things, customer desires, needs, problems, what's going on in the market. A data scientist is the one that extracts the meaning from data. A lot of times, it's customer data. So you can see how both of these roles very much complement each other, and that usually a product manager, they're not able to do all of the analysts on their own. They usually work on data scientists in order to figure out what is the meaning there. And so together, they can work on making the best decisions and executing and having the actionable outcomes. So you can see it's really about empowering the product management team to make those best decisions and executing on an idea that is going to have an impact on the customers, on the business, and on the ecosystem. Usually a product manager is called the CEO of the product. A lot of leadership without authority because unless you get to a really high level, you're an individual contributor. And so you're working with all of these different disciplines, UX, engineering, design, research, marketing, data science, without any authority over them. And that's why you have to use impact or influence, influencing people that you know what you're talking about or that you can make good decisions. And then people say that PMs are problem solvers. Everyone in the product management team, everyone in the tech company are problem solvers. Everyone solves problems. PMs are just responsible for this problem end to end. This is one of the distinct things about a product manager is that they are responsible end to end for the delivery and execution and success of the product. So we talked about it in high levels about what is a data scientist, what is a PM? Let's look at the similarities between the two goals. So data scientists usually works with data engineers to ship data. Basically, they need to make sure that there's a solid reliable data foundation and that there's dependable, reliable, scalable data systems. A PM slightly different works with engineers to ship features to ship software features, essentially. A data scientist has end to end ownership of model development, where a PM has end to end ownership of product development, so the entire product versus perhaps an machine learning model. A data scientist needs technical skills to be able to design reliable, scalable, understandable data science models, machine learning models. A PM needs technical skills to be able to design reliable systems. A system could be anything from like the Uber application or the experimentation platform that I work on. These are all systems and a PM needs technical skills in order to be able to work with the engineers to develop the appropriate solutions that are not going to be having too much technical overhead or not infeasible to be able to design. A data scientist has general knowledge of statistics, experimentation, machine learning models, but they can also be specialized in certain topics. For instance, lots of companies are hiring for specific skills in something with natural language processing. A PM is also a generalist, but of a much broader skill set. They are a generalist of statistics, experimentation, machine learning models, and UX principles, technology stacks, go-to-market strategy, pricing, marketing. They need to know a little bit about everything, and they need to be the person in the team that can use that, what they know, to empower other people to make, to do their best as well, so the whole product development team is successful. A lot of the field in data science, you can be called different things based off of your education.  If you have your master's or maybe your undergrad, you'd be a data scientist. If you do not have a lot of that experience in machine learning models or statistics, perhaps you start out as a data analyst, or if you have more experience with data systems, such as Spark, Hadoop, even SQL, maybe it'd be a data or BI engineer. As a PM, there's also different flavors. This can get a little confusing, and we will talk about it a little bit, but there's regular product manager, technical product manager, platform product manager, product manager, and then a data scientist makes trade-offs between the performance and precision of their models. A PM makes trade-offs in general between the feasibility of their solution and the ideal solution. For instance, what is the ideal solution that a customer would want, but what is feasible with the engineering budget that we have and the time we have and the number of engineers we have. The commonalities between the two are commonalities between probably most disciplines in tech, but in particular, both have to manage stakeholders. We work with people all the time, and the people that can work the best with all their stakeholders usually do pretty well. Being able to communicate clearly and concisely, this is really important because each of these disciplines is important for being able to generate actionable outcomes and execute. You cannot do that if you're not able to communicate your ideas clearly. Working well with ambiguity, data can be super ambiguous, people and customers can be super ambiguous, and the problems that we're solving are ambiguous. Working well with ambiguity, this is something that both disciplines have in common. You also need project management skills because you're working with people, and you're also managing yourself, and you need to be able to manage projects really well. Then this is something that's very important, and this is something that is going to be critical in being able to pivot from being a data scientist to being MPM, is understanding customer needs and behaviors using analytics. This is something that both disciplines do. Data scientists do it to a higher degree, but PMs also need to be able to do it too. This is going to be critical to differentiate you as a data scientist into becoming a product manager. Then the other part is understanding the needs of the business. It's not just about understanding customers, you also have to understand how it is a business operating, what our competitor is doing, how do we want to differentiate ourselves, how do we make money? Then very small, but very critical is knowing how to run queries. This can be something, this is something that I actually was able to do before my transition into being MPM, and that's essentially what gave me a bit of an advantage. On my team, everyone is very excellent at running queries, so that is something that is kind of expected in our organization in Azure. Which role maps to which type of work? You saw on the Venn diagram that I highlighted growth PM, that's just because I'm going to dive deeper into that, but there's four different types of product work in general. There's feature work, which is generally what most PMs do, I'm developing a software feature, this is a person that creates and captures value by extending a product functionality. So I'm sending a product functionality to add incremental, to incrementally capture a new market or new set of customers. Growth work is essentially, it says creates and captures value by capturing more of the existing market, but growth PM is essentially someone that is thinking about how to optimize certain funnels. So like customer acquisition, retention, making sure that I'm reducing churn, making sure that I'm able to, with the current customers I have, I'm able to increase their usage of the product. And so in Azure's example, it's all about usage. And so what we want to do is get our customers that are using virtual machines use more virtual machines or use them for a longer period of time, because virtual machines are built on hour. The third one is scaling the work. This is mostly aligned to feature PM, core PM, growth PM, growth PM. And then this is platform PM. This is the work that I said I did. I was a feature PM and a platform PM on the Azure portal. Think about these teams as the ones that are creating platforms for other people to build on. So for instance, the Azure portal, we actually release an SDK, an SDK that different teams within Azure can then use in order to create their experiences. Similarly, Azure itself is a platform. It's a platform that people use to build their products and they use as their technology stack in order to create their products that they sell to their end customers. And so a platform PM really needs to make sure that the product is able to grow across new features and that it makes sense in terms of the platform strategy. And so this is a little bit more nuanced than just releasing a new feature. It's releasing a new feature and making sure that it makes sense for the ecosystem, making sure that it's sustainable, making sure that it's not going to have any adverse consequences. And so it's very much, it's very much, and it's a lot more technical too. And there's product market fit expansion. This one, I haven't encountered as much, but what most people call this an innovation PM. So it's someone that works on more like rune shop projects or projects that like there hasn't been like more what I don't want to use buzzwords, but green field opportunities. So this is someone that would work on something where there's not as much proven, there's not as much proven in the space. And the company is making like a big bet on innovation in this space. And maybe there is not necessarily a market for this right now, but we're creating a market for it and we're seeing a market for it. This is still a core PM, but it's a core PM that has that leans more into ambiguity, leans more into customer discovery, leans more into understanding what the customer needs without them even saying that they need it. So that's similar skills, but much more risk, much more ambiguity. I'm going to run through a typical PM workday very quickly because I want to focus on one of the aspects that is common with data science about you think that's which one. So a PM, you know, you have to communicate ideas, they gather information. Here, there it is. One of the ways that they gather information is through data analytics, as well as technical understanding, technical limitations, they brainstorm ideas with UX researchers and designers with their engineers and architects and with their go-to market team and leadership and sales and in marketing, they plan strategies and they execute and they plan managing through scrums and meetings. But as you can see, this is not, this would not be a typical day for a data scientist at all. They would do something really different. If you're a data scientist, you probably know that. But the common thing is data analytics. So I wanted to, so previously we said, you know, data scientists and the PM, they do have quite a bit in common through that Venn diagram. But when you look at the day-to-day, it can differ quite a bit. I want to point that out because you can leverage your data science skills into being a PM, but you'll have to like really learn all these other skills as well. The good news is that these are fairly, as you build a product, these are fairly easy to learn or reasonable to learn. A quick run through of like the different types of PMs that there are, the product manager, technical program manager, platform PM and growth PM. I want to focus more on the growth PM because that's what I was. And I think that's probably the easiest way to transition from a data scientist role into a type of PM role. I've obviously people have transitioned from being a data scientist or even a data analyst into four product management roles, technical program management roles or platform roles. But I think the growth PM is a lot easier because this is the role that aligns the closest with data analytics, science and marketing, growth marketing. Because they're focused on driving business outcomes. Remember what we said about data science? They drive actionable outcomes by creating meaning out of chaos and meaning out of data. Similarly, the growth PM is focusing on driving new business outcomes, such as acquisition, retention, usage, and revenue. And they usually work with additional core product managers to drive these outcomes via growth hacks, like experimentation or product optimizations. So they are using the growth of business. So this is a great role that leverages both the great skills of a data scientist as well as PMs and understanding the customers and creating actionable outcomes and delivering in order to be able to move the business. This is how I transitioned from being a pure data scientist into being a PM because I was also working in my role as a data scientist also as a growth PM. And so I was able to leverage those skills that I had learned, but also get more of those PM skills that we talked about are important to learn here that you do in your everyday activity. Really quickly, for those of you that may not know, a traditional product manager focuses on the what and the why. They're usually customer facing. They set the product and go to market strategy. They're most often technical, but they can also work with non-technical teams. Sometimes you'll see someone say, this is product manager, technical, it's just product manager. The key difference is how technical are they, and if the product that they're working on is a technical product like AWS or Azure or a non-technical product. A technical program manager is more execution oriented. They are responsible for the planning and development of a solution. They usually work on when and how. We have a strong technical background because they work with engineers more closely. Many companies combine one and two, like Microsoft, product managers, and TPMs are the same role. And then we talked about platform PM, so I'm not going to get into it too much, but they are responsible for toolings or platforms like just APIs, operating system SDKs. They need to consider developers who are usually their primary audience because they're usually working building for developers as well as their developer's customers. So they're customers' customers. And they need to balance the short-term trade-offs for long-term platform success. So this is kind of where I was saying, it's like a feature of PM, but it's a lot more nuanced because you have to make types of trade-offs. Okay, so the core question is, how can I demonstrate these products built? How can I get someone to hire me as a product manager as a data scientist? And it's going to sound a little bit trite, but it's quite simple. You build a product. That's what I did when I was working on the Quick Start Center is I saw a problem, and I came up with a solution that I thought would meet the need, and that proved to be successful. So that is essentially the core of it. And because a product manager needs to demonstrate that they can see a problem, they see a customer need, they can understand and make a good decision on what to build for that customer based off of their judgment. It's very important to have good judgment as a product manager, and then they can execute and make it a reality. This is something that not everyone will be able to do in their current role as a data scientist. Maybe your team won't allow you to stretch into that. Maybe there is not really a scenario where you can build a product. That's okay. This is something where you could do even in your time away from work. Moonlighting as a volunteer in a particular area where you can, or for an on-profit, where you can build a product using your data science skills. You can understand how I can use my skills as a data scientist to understand what the customer needs. Maybe I can't and then essentially use that to build something. Basically, you need to build something and demonstrate that. But remember your competitive advantage. Remember the things that you can do that perhaps other roles that are transitioning into product management can't do. You have excellent skills in terms of extracting meaning from data. That's what's going to enable you to make better decisions. The difference is you've got to take that and you've got to drive it end-to-end. I think that's one of the joys of being a product manager. That's what I wanted to switch from being a data scientist into a product manager is I get to drive the end-to-end outcomes working with a ton of people that are amazing, but I get to drive the end-to-end. I think that gives so much satisfaction and so much opportunity to make an impact on customers. I'm going to run through the data-driven frameworks for product management that I think there's lots of frameworks that people use or they don't use frameworks and they just build something. I'm going to talk about this because I think this is super relevant to you as a data scientist and it's based off of the scientific method. As scientists, we know that what would we do for us in the scientific method is we observe and we ask a question. We make an observation and we ask a question. Oh, I noticed that this customer is doing something like this. I wonder what would happen if they did this instead. We would research the topic area. We would search for existing solutions or answers. This is just basically doing your homework. Once we've done our homework, we would hypothesize. We would form a hypothesis. This is very clear how we would think about something. If I did this for this customer, then this would happen as a result. I'm saying it in customer terms, but obviously the scientific method is used for scientific problems, but we're going to apply it broadly. They form a hypothesis based off of their observations and their research, and then they design an experiment. They design an experiment to test their hypothesis. After they run that experiment, they analyze data and they draw conclusions. It's very simple. People have been using the scientific method for hundreds and hundreds of years. Now we're going to take this and we're going to turn it into our product development framework. Remember, I said a product manager owns the end-to-end product development process, but it's a virtualist cycle. It's a flywheel. What we start out with is building a problem hypothesis. This is inspired from the first three phases of the scientific method, where we understand what is a problem that we notice something. We notice someone doing something, but then we say, ask ourselves, what is a problem we're trying to solve? Who are we solving it for? Is there a large market for the problem? What are the characteristics of this problem and what are competitors doing? From then, we come up with a hypothesis. We say, hey, we believe that if we do this, then this is going to happen. What do we build to meet customers' needs? How will we know we're successful? How will we measure that we're successful? Then we design an experiment to validate and execute, to validate the solution hypothesis, and then execute it if we're trying to help. Here, we ask ourselves questions like, did we successfully deliver the ideal customer experience? Did we solve the customer problem, both short-term and long-term? As you can see, I'm showing you what are the types of activities we would do at each stage. Notice that in the first stage, we're usually working with data science and analytics and user research, as well as business strategy, compete analysis, and telemetry analysis. Here, we're really doing our homework. We're really trying to understand what is the customer need. We're also extracting meaning from data. Usually, we do that with working with a data scientist. This is really where, for me, when I was a data scientist transitioning into a PM, I realized that there was a problem. I knew that there was because I had done my homework. I had done the analysis on customers. I understood where were they dropping off. What was the gap? They came up with a solution, a solution hypothesis. This is where, in order to actually run an experiment, we have to build something to test. This is where the PM would work with the designers to design the UX, the UX product, and engineers to develop a roadmap of features to build. It also defines success metrics. This is very important for all PMs to be able to do well. This is something that a data scientist, as a PM, can do really well, because it's about understanding the different metrics that make sense. It is an art and science in itself. We don't have time to get into it today, but this is something that where data scientists can really shine. Then also testing the designs in user research studies. User research studies are essentially where you bring mock-ups, usually, or a lightweight prototype. You see how they use it. Basically, there's more to it than that, but you see how they use it. Before you go into code development. Then once you ship the product, you make sure that the feature ships on time. There's an asterisk there as software. You think it would be easy, but almost nothing's on time unless you're having your people work overtime, which you can do, but not recommended, unless you really have to. Then you run the feature through an experiment. This is where designing an experiment, designing who you're going to expose the feature to, what are you going to manage, what's the rollout schedule. This is really important. This is the experiment design execution phase that a PM would need to do. Sometimes when we're thinking about those broken up rolls, this might be something that a TPM does, a technical program manager, but usually it's TPM slash PM that would be responsible for this. We analyze the long-term impacts of the feature. Is it going to have the impact that we want long-term, or is it just going to be a temporary flip? These are the types of things that a product manager would think about when they're using this type of framework, and it's really a hypothesis-driven framework. We're thinking about, is this the right problem? Okay, we've done our homework, and then is this the right solution? Okay, we'll validate an experiment. If it's successful, we'll ship it, and then we'll continually iterate and we'll learn. I believe that is the end of my content today. I want to thank you all for your time and listening to me talking about how to make the leap from being a data scientist to a PM. If you would like to reach out to me, you can find me, please go to the first slide. My name again is, oh my gosh, I have to do this. Okay, one second. My name again is Isha Ghafar, and you can find me on LinkedIn. You can also find me on Twitter. Thank you so much for joining again, and I hope that you are successful as you make your transition from being a data scientist to a product manager. Thank you so much, and have a great rest of your day.