The following is a presentation of TFNN, the morning market kickoff with your host Tommy O'Brien. Good Friday morning everybody, I'm Tommy O'Brien, coming to you live from TFNN, 9.06 a.m. Friday morning. We got about 24 minutes to go until the start of trading. You have markets right now accelerating to negative prices. We got a hot CPI number, we'll get into that in a moment. Right now you got markets trading down S&Ps, negative by 1.4 percent right now, trading down 56 points at 39.61. Folks, we've almost given up 200 S&P points just from where we were yesterday morning. We have given up 200 S&P points from the highs we had earlier this morning. And as we're speaking, S&Ps basically sitting at pre-market session lows of 39.59. You get the NASDAQ 100, you're off 1.7 percent right now. The Dow off 1.3 percent, Russell off 1.4 percent. We jump over to crypto, Bitcoin trading a little bit lower as well. You just dropped below 30,000 on that CPI number. Crude holds up relatively well. You did get some negative action even for Crude on that number. We were up to almost 123. Crude contract sitting at 121.42, you got gold. There's some volatility for you on gold, man. Gold, we spike initially to 18.26, then you get quite a pop up to 18.44. That goes down $9 on the session right now. And we jump to notes and bonds. And we got a little bit of lower price. We got a little bit of higher yield. You jump over right now in terms of where we are. You're talking about a 10-year yield, 3.04 percent. Not too crazy when you think that's kind of where we were yesterday. The two-year treasury surging above 2.9 percent, I saw early this morning, on that inflation number. And let's get into it, man. Inflation, we got a headline number of 8.6 percent, folks. Number they were looking for, I think was like 8.2, right? Month over month, it exceeds the expectation as well. When you get into the core, okay? Core rising 0.6 percent from the prior month and 6 percent from a year ago, also above forecast. And there's your ramp up, folks. I mean, you think about it, right? Really remarkable when you think that February, even March, was the first real time we started to get an indication of the numbers rising. The black bars here are the headline number. The pink is the core, so you could make the estimate, you could make the guess that we have peaked in that March number of 6.5 percent on core. We've then come to 6.2 and now 6 percent on core. But headline number, we're talking about rising to 8.6 percent. That is a high print, folks, okay? So March, March was not the high. We got a new high in terms of a headline number on CPI of 8.6 percent. Commodity is a big part of it. Double digit paces, energy prices climbing 34.6 percent from a year earlier, the most since 2005, including a nearly 49 percent jump in gasoline prices, grocery prices rising at 11.9 percent annually, the most since 1979. Electricity, 12 percent, the most since August of 2006. Rent of primary residents climbed 5.2 percent from a year earlier, the most since 1987. The one thing I will say there is that that helps out the real estate market to some degree because it's not like in previous bull market real estate runs when housing prices were out of whack with rental prices. Yes, you can make that same argument, I'm sure, today that housing prices are out of whack with rental prices, but not to the same degree when you got rents rising 5.2 percent from a year earlier, the most since 1987. Was that 35 years? 35 years, man. Crazy. So we get that number at 8.30 and where do we have it? Let me get the number in terms of the 2.9 because that was an interesting one in terms of the 10-year pulling up the Treasury yields on that number right now. You get the 10-year at 2.92 percent. That's a jump of about one-tenth percent in a heartbeat, man, just like that. And you can see the 10-year not moving as much, right? That's where we pulled it up. You're sitting at 3.05, you're sitting at 3.04. On the short end of that curve, though, the two-year really accelerating higher. Yeah, and so we'll see how that goes in terms of the number they were looking for was 8.3 percent on the headline number. The core number they were looking for was 5.9. And I had made the argument earlier this week, folks, there's only so much the Fed can do to get inflation under control when you're dealing with supply chain issues, you're dealing with a war that is affecting energy prices. So we're in a very, very volatile period of time here where no matter what the Fed does, if we're still dealing with a war with oil prices sitting at $120 a barrel, very difficult in my mind to see that number coming down dramatically now year over year, okay, eventually we'll get to the point where I guess those oil prices started spiking in March. We're already three months into the year. So nine months from right now, okay, we'll have gas prices that'll be benchmarked against a comp that is at $120 a barrel, but that is a long way to go, man. We need some easing in some of those energy prices to put a dent in some of the headline numbers that we are getting, but it is not stopping yet, man, in this market. Let's jump around to some of the fang stocks as the market just continues to sell off right now. S&Ps down, what is it, 60 points right now, trading at $39.57. You got a low print there of $39.49, but we're right near that level. We were trading at $4,020 prior to that number, and that's after the sell-off we got yesterday. You jump around to some of the fang stocks. Amazon shares, you're gonna be down about $2 on the open. Microsoft shares, you're gonna be down about $4 on the open. It's gonna be an interesting one, folks, coming into a Friday, and it's just nonstop right now because we got CPI that just came out. We have another Fed decision coming out next week. This puts a little bit of fuel on that fire. He's gonna have some questions to answer. My expectation is that he's gonna say, we just started this, we're on a course, we're gonna wait for the data to play out, and we'll see how that works. That becomes a more difficult sentiment as time marches on and we get higher prints. Do you remember the conversation about March, folks? The conversation about March was all expectations are, we're probably gonna peak in March. The comps we'll be dealing with as we go further in the year will probably point to the fact that March will be the peak. It'll just matter how we wane from there. How quickly can we come down to 4 to 5%? How quickly can we come down to 3 to 4%? How quickly can we get to that elusive 2% right now? Well, we're at 8.6%, folks, all-time highs. Again, it's June. That was a main number. We march on.  Continuing to check around some of those stocks. We jump over to Google shares this morning. Yeah, you're all gonna be trading pretty dramatically lower right now. Google's gonna be off about 50 bucks from 2,300 to 2255. So far on the morning, we jump over to Tesla shares. Tesla trading down about 20 bucks to 702. Fan favorite Twitter, barely a haircut. That's an interesting one, man. Where would Twitter be without the saga going on with Elon Musk? 20 bucks? 30 bucks? It wouldn't be at 39.53. And I'm not sure that that is. Well, we'll see how that one plays out as well. Jumping back to some of the commodities. Gold pulling back a bit from that high it had. 18.39, you jumped to 18.26 real quick on that number. Jump over and see how the Euro, US dollars trading right now in that action. Yeah, we gotta move down. Euro, 105.33 after some action yesterday to 1077, man. You talk about some volatility. And there's your daily on the Euro, US dollar, man, but you're making a run back to the lows of 1034. And let's check out the yen too, because this thing's been on fire, man. Sitting right at about 134. No real pause in that action. Maybe just a pause, a brief consolidation. Basically sitting at the higher level at sea in 133.94 for the yen. All right, folks, it's 9.15. We got 15 minutes to go until the opening bell. We got markets, S&P down 1.6%. Stay tuned, folks. We'll be right back. At the time of booming inflation, we are purchasing powers eroded. There's no better place to protect your harder and money than ain't gold. This, the gold's flagship asset is the Monk Todd Gold Project in the Northern Territory of Australia. This is Australia's largest undeveloped gold project. We are talking a world-class gold project in a tail-one mining district. This is a large-scale, low-cost project with significant existing infrastructure in a politically safe and friendly mining jurisdiction. This, the gold just completed the Monk Todd Feasibility Study, which resulted in a 7 million-ounce gold reserve and a 16-year mine life. 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At tfnn, all our newsletters come with a 30-day money-back guarantee so you have absolutely nothing to worry about. Visit tfnn.com and try Mastering Probability 30 days risk-free today. TFNN, educating investors. Welcome back, folks. I got a chart here of the S&P. We're up, I have it up on a weekly basis. We are not up today. We're down 1.6% and I pull up this chart, sent a newsletter out to my subscribers earlier this week and what I was saying is be careful here because all we've had in these indices is that we've had a jump from one Fibonacci level to the next, okay? So I'm gonna go over it real quickly here. We have the S&P's up here. You trade from 21.74 to 48.08 during the pandemic, quite a run, quite a run to say the least, man. You trade back to a 3.82 of that number at about 3,800. The acceleration that we got to about 4,200, that's the 2.36 line. In the S&P, we touched that level. We've turned south, we're about 150 points away from 3,800. Seems like that might be the stop right now with the way these markets are trading. 150 points from where we are in terms of to the 3.82 line. Meanwhile, we've given up almost 200 points just in the last couple days of trading. Now the NASDAQ 100 did a similar thing, just different levels. NASDAQ 100 had made it all the way back to the 50% retracement. And then what you do, you bounce to the 3.82. And now we've given almost it all back. You get the NASDAQ 100, we're only 450 points away from where you're trading at right now to make it back to that 50% retracement in the NASDAQ 100. Dow, similar, different action. As in the Dow hasn't gotten to that 3.82. You're chopping around at the 2.36 right now. The Dow had been the laggard versus some of the other indices, percentage-wise. But it's also the laggard on the pullback. Did not get the run-up that the other indices had, but not getting the run-down as well still. You're down 1.5% today, though, on the Dow Jones industrial average. And how about the Russell accelerating off 1.6% right now? Let's take this off. Let's see how to curiosity where we are on the Russell. Yeah, so Russell pretty similar to the NASDAQ, actually, that you pull back a 50% of the full move and then it bounces to the 3.82. And we give it up from there, the Russell right now dating off 1.5%. All right, jumping around to what else we have going on. Let's jump around to some of the stocks with action. We'll kick it off with DocuSign. Talk about cratering, man. I think they were down 30% at one point. 25% revenue growth from a year earlier, but investors are increasingly concerned with profitability. My dad's made some great points about this, talking about, they got a lot of competitors in the market in terms of who you can deal with. But DocuSign comes out 38 cents a share versus 46, so they miss their revenue, 588 versus 581. Revenue increased 25% from a year earlier period, but as investors shift away from a focus on growth to profitability, the miss on the earnings overshadowed that revenue gain. Stock's down huge this year already. On Thursday, the company reported its net loss widened to 27.4 million from 8.3 million a year earlier. So those are adjusted earnings up there. They're actually losing money, but if you adjust it, 38 cents is what they made. Experienced strong growth during the early months of the pandemic, but that has waned. I'll finish that quote up there for the second quarter. They call for revenue of 6 to 604 million. The middle of the range 602 was just above estimates. And for all of 2023, they see 2.47 billion to 2.48 compared to 2.47. Folks, pay attention to these earnings because those are not that bad, okay? They're not great. They're not that bad for a company that's been pummeled. And you wanna talk about pummeled? If you haven't checked out DocuSign this morning, it was trading at 87 yesterday and you're gonna open at 65. That's a $22 hit, folks, okay? And $65 on this equity brings you back to September of 2019.  That might, yeah. You're talking about basically when this thing looks like when public. I only go back to June of 2018. So DocuSign is gonna be at basically $65 on the open. We'll pull up the 15 minute. There's your action, man. I mean, that's just pretty staggering when you look at what they did in terms of numbers, in terms of revenue. They still have growth. And the market said, no, no, no. We're anticipating much bigger than that. You're not supposed to be losing more money than we thought in this environment.  Man, what's that 25% hit? Yeah, crazy, man, crazy. Yeah, in this market, it's gonna be a steep one, folks. The narrative that inflation had peaked in March is gone. That's not a good narrative to disappear. Now, a lot of these numbers have to do with energy. The tough problem here is that the Fed cannot control oil prices, folks. Okay, they can't control energy prices. They can't control everything going on in there. And they can't control food prices when some of those issues have to do with supply chain issues. Supply and demand, as simple as that. And you're seeing those issues play out in dramatic fashion right now. I mean, the core number is still a big number. Okay, and month over month comes in at 0.6%. That's even if you take those numbers out, that is a number that the Fed can control, which is why the Fed loves the core number so much. Because the volatility in food and energy is something that they have difficulty controlling, because it is so volatile, that's why they flock to the core number. But boy, that is very difficult in times like this right now. When you have a war going on, you have energy prices spiking, you have food prices spiking to a degree that we haven't seen in a while. Yeah, so it is a tough one to say the least. Just jumping around, excuse me, folks. Okay, okay. Excuse me for that, just getting everything in sign. So there's DocuSign for you this morning. How about Stitch Tricks? Shares sync after company announces layoff offers weak guidance. Laying off 15% of their salaried workers, about 330 people. SFIX, I believe is their symbol. There it is, you're now from 778 to 618.  That's a crazy chart for you, man. I can't remember when. I'll have to look it up at one point. I had some type of an option chain at some point in the past in this equity, and it worked out well. I can't remember when. It could have been as far back as March of 2021 when things really got ahead of itself. I mean, this equity, folks, okay? Just for some context here, you're at seven bucks. You're still talking about an equity that's valued at, well, no, you're down to 700 million. When this thing was trading at 100 bucks, even trading at 10 times the value, okay? You're talking about a company that's valued at $7 billion and $8 billion. I remember the numbers that they were coming out with at that time, and I just said to myself, this isn't how a company becomes a behemoth, okay? The average customer was spending something like $400 to $500 a month almost on their clothing. Yes, that's a great sweet spot, man.  I mean, if you can get enough customers that are paying $400 to $500 a month for your clothing, that's great. But my goodness, man, that is not a recipe for broad customer base in terms of the amount of money that they were spending, the customers that they were trying to reach. And it's been a one-way trip, man. And I would not touch the equity at all. They're laying people off the stocks at $7, and it looks like it's a trip to negative prices. Once you're down at under a billion dollars, folks, and you are a public company, well, you have to keep in mind here, okay? And this is what I always say to myself at some point is that when an equity reaches that level, okay, there's a lot of brilliant people on Wall Street. And if this was an extreme opportunity at a price of $700 million for the whole company, well, shoot, you can go in there and you can put up $100 million, you can put up $200 million, maybe you get some financing, you buy the whole thing, right? They take it private. Realize that there's that element on a fundamental basis for some of these companies, man. It's not happening for Stitch Fix right now. Down big again to $6.30. Stay tuned, folks. It's gonna be an interesting open. We'll be right back. If you wanna take advantage of this sector, now is the time to subscribe to my Gold Report. The Gold Report is a comprehensive look at the metals sector, as well as the markets that move gold, which is the currency and bond markets. New subscribers get a 30-day money back guarantee so you have nothing to lose. 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In the Tiger's Den, you can look over the shoulders of Tom O'Brien and the other TFNN hosts while they analyze charts during their live Tiger TV programs and join an interactive trading community with hundreds of members exchanging ideas, interact with other Tigers and Tigresses as they share trading ideas, news analysis, and discuss the market action all trading day, even at night and on the weekends. The Tiger's Den at Discord is accessible on mobile or tablets as well. So it's always at your reach. To sign up today and become a part of this educational community of traders, just visit the front page of TFNN.com. TFNN is excited about our new software charting program, The Art of Timing the Trade Chart. In collaboration with Tom O'Brien and using his best-selling book, The Art of Timing the Trade, Your Ultimate Trading Mastery System, David White has programmed an outstanding piece of software that will complement any trader's methodology. Using this first-of-its-kind program, The Art of Timing the Trade Charts allows you to scan thousands of stocks for Fibonacci formation setups, including guardleafs, ABCs, butterflies, and much more. The Art of Timing the Trade Chart is designed to help you when scouring the markets for stocks just beginning to form the trading patterns that many investors spend days, weeks, or even months searching to find. And right now we're offering licenses available at only $79 a month. We are so confident that you're gonna love this new charting software that will even give you a 30-day unconditional money-back guarantee. Don't miss out on this incredible new piece of software. Get your copy of The Art of Timing the Trade Charts today by visiting TFNN.com. This segment is brought to you by Think or Swim. For more information, just click the Think or Swim banner on the front page of TFNN.com. Welcome back, folks. We got the opening bell. We got markets open, and you're looking at an S&P that currently opens down 67 points. That's one and two-thirds percent, folks. And man, you're talking about basically 200 points from where you were at 7.15 a.m. yesterday morning. We're trading at 39.50. We're almost at 41.50 yesterday. Nasdaq 100, you're continuing to drop.  The Dow, nothing getting spared right now. Dow off 517 points. How about the Dow? You ready for this one? 1,500 points, man. We were trading at 33,100. I guess it's 1,400 points. Okay, I'm ballparking here. 1,400 points from where you were yesterday. Mammoth numbers across the board. We jump to Crude. Hold them relatively well. Yeah, Crude's got some volatility. You have dropped off with the markets in the last hour or so. You see Crude from 1.22 in change. You're trading at 1.2074 right now. Still, all things considered, right near highs. You got gold giving it up. You're off $19 net right now at 1,833 for the price of gold. And you jump to the notes and bonds. We got some higher yields coming at you, folks. Check out that 10-year right now. You got the 10-year down, what, 20 ticks now? Just put this on a minute. That was not the case when we came on the air, man. What time we get on the air? Yeah, we get on the air. 10 years giving up 15 ticks just since I've been on the air right now. So not all that action taking place on the initial inflation number. You see the initial move. You claw it all back. And then we've traded down a full point, folks, within an hour, can't overstate it. The 10-year yield now above 3.1%. We were at 3.04 when I started the show, I think. Six basis points in the span of a half hour. The 10-year, 3.1%. We'll jump over for a little bit of a rate conversation. Traders now fully pricing in three half-point rate hikes in the coming months with a 30-year treasury yield falling below its five-year counterpart for the first part in a month. We got a little inversion going on again. Money markets, you're talking about 50 basis point increase in June, July, and September. We find out June next Wednesday, folks. That's what the Fed swaps they're saying. That would add to 75 basis points of tightening delivered by the central bank since the start of this year. So remember, they started off with a quarter point. Boy, that was a mistake in hindsight, huh? Now they've gone for 50 basis points and it seems like they've got three more 50 basis point hikes factored in. So that would be what? Two and a quarter is what they'd get at the end of September. We'll have two and a quarter priced in, not priced in. We'll have hikes of two and a quarter percentage points by September if they go 50, 50, 50 from here. That would be four 50 basis point hikes following a 25 basis point hike. Now, as I say, every month it builds, folks. I think you'll see the Fed say, listen, we gotta give it some room. Okay, we're hiking 50 basis points here. We're hiking it there. Maybe there's a pause that that language kind of snuck into the conversation at one point. Seemed like some of the Fed governors decided to smack that down in terms of the vice chairman, Leo Brenner. She was out there saying, no pausing. We're gonna be aggressive, et cetera. I don't think they want the market anticipating a pause even if they think they might pause because that in itself will distort the effects of those hikes themselves. So they don't want that message out there even if that's something they're considering. You can't consider a pause as we continue to get record breaking numbers on inflation, folks. I can't overstate it. Just the fact that we were supposed to have a peak in March, that's not the case anymore. The peak is now in May, not from a core basis, okay? But in my opinion, core doesn't matter right now in terms of what's hitting this market when it talks about inflation, talking about supply chain, talking about food, talking about energy, talking about natural gas, electricity, et cetera. I'll try and find the article at this next break because I had a great article out here earlier in the week from Bloomberg talking about the three biggest factors in inflation right now are food, energy, and electricity in the same degree. And all of those are rising at double digit numbers for the first time in a long time. And it might get worse. And that's what we're seeing right here, folks, okay? That's what we're seeing in a big way. And yields are reflecting it as we got the tenure at 3.1%. My dad's been talking about it, man. He sees rates going up. I think he's got it right so far. We'll see if that's the trend that continues right now, but you're talking about a 10-year. Now, put this thing on a daily. So we make it down to 1,7707 today. That's the low. We did, we got there below the low. 1,7085 was the low. We got there by a tick. We break that recent low and you got a 10-year yield at 3.1%, man. Remarkable. All right, let's jump around to some of the other action we have going on today. So interesting yesterday. You had Peter Rice. He was some type of content, right? Was he chief executive? No, no. He was in charge of content, I believe. Let's see. Yeah, I should get his exact role here. But so he gets fired. This guy came over from Fox. Peter Rice, one of the longer resumes in entertainment, but he has done at Disney. So Chaypec fired the 50-year-old head of his TV division on Wednesday is what it was, a clash of styles at the world's largest entertainment company. He had been talked about maybe taken over as CEO before Chaypec, so I wonder if that had some of the lingering effects potentially of disagreements out there. Surprised to him and many others in Hollywood, underscores the unique culture at Disney, heavily reliant on group thinking and collaborative decision-making. I'm a big Disney bull folks, group thinking, horrible for almost anything, group think. Be very careful of group think across the board. But he's gone. We'll see how that plays out in the future. Disney's been a tough one, folks, to say the least. Let's see how it's trading today. Down 2% right now, Disney 101.29. Taking a look at some of the notation I have on this chart, you take a look at it, right? We pull back, we pull back a lighter volume, man, right into this area that you originally broke out. Disney, you back it up to May 4th of 2020, more than two years ago. Disney really accelerates out of the doldrums. You trade out with about 146 million shares. You trade back down the week of May 9th, the week of May 16th. You had 113 million originally. You had 62 million originally. Now even take a look at this week. Okay, this week right now, what are we pushing? 32 million is all we have folks, trade and lower.  You're pulling back on lighter volume. You do want to see a sign of strength folks, but I imagine, you know, the Disney streaming service is so far above what they thought it would be. The Disney parks are going to be busy and sold out for years. This company is going to make a lot of money again in the future folks. Netflix, man, they got some big problems though. Down 4.3% right now for Netflix shares. Think they got a downgrade this morning. Continuing to drop off $8 to 184. We put this thing on a daily. I mean, that's a tough area, man. The 162 is the low. You're sitting at 184. The one thing about Netflix that's so tough right now when you talk about valuations, they're trying to change their entire business plan, man. They're going to start selling advertising. They got growing problems. They're going to have cost issues that come with things and how are they ever going to make money, man? They're going to try and sell some ads. Well, that's an entire different business model. And that's the reason why you saw some of the companies that were big into this. Who was it? Pershing Square Capital.  Caught his ties instantly when this thing traded lower on their last earnings. And one of the reasons he said he did, it's David Einhorn, I think it was Pershing. And they couldn't basically base how this company was worth if they were changing their entire business model. And he said he had learned from his prior mistakes. We'll see if that's true. He didn't ride this one out to the graveyard. But yeah, I would agree that you can't really factor in how to value a company when they are entirely changing their business model, which is not what Netflix is doing. 700 to 183, remarkable on that equity in a big way. Let's check around some of the other growth stocks. See how they're doing. You got Zoom down about 2% right now. DraftKings down about 1.3%. We check in on Arc down 3.6%, sitting at 41.60. S&P's negative by 75. Stay tuned, folks. We've got a couple more segments of other equities to go over this morning. It's Friday. It's a negative action. The market will be right back for us. Are you in the market for buying or selling real estate in the Bay Area, including the surrounding St. Petersburg, Tampa and Clearwater markets? Tiger Real Estate, LLC is a firm that has extensive experience in the Tampa Bay area. Whether you're looking to sell your current property for maximum value or you're in the market for a second home or investment property, Tiger Realty has the experience across all areas of real estate in the Tampa Bay area to help buyers and sellers make the most informed decisions across all price levels. 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To obtain a fund's prospectus and summary prospectus call<PHONE_NUMBER> or visit directioninvestments.com. A fund's prospectus and summary prospectus should be read carefully before investing. An investment in the funds is subject to risk, including the possible loss of principal. The funds are designed to be utilized only by sophisticated investors such as traders and active investors. Distributor, foreside fund services, LLC. This program is brought to you by Vistagold, traded on the NYSE American and TSX under the symbol VGZ. Hi, welcome back folks. We got the S&P sitting down about 75 points right now, back to a five-minute chart. Really, no bid in action yet. You did make it down to 29.32, we're 10 points off of that low at 30. We did make it down to 39.32, excuse me, we're up 10 points from that low. But boy, you talk about an acceleration, man, 12 minutes in the day, and I'd be careful on this one, folks, because that data is gonna make a lot of people worried in terms of where we go in the future, because what happens, and I've been talking about it on my show, folks, and I don't have the answers, but you gotta have the available areas of what could happen, and then it's our job to try and assign a probability of those things occurring. You can't predict the future. If you can, good luck to you, and you'll make a lot of money in the market. If you can't, the way I look at things is you look at a set of possible outcomes, and then you assign a probability of each of those possibilities, okay? Well, you have a Fed that's on a hiking cycle. What's the probability that that hiking cycle diminishes the inflation that we're facing? Whatever you put that probability on, now you have to consider what is the possibility that Fed hikes 50 basis points, 50 basis points, 50 basis points, and meanwhile, we have, yes, some pullbacks, but has the price of oil waned? Have the price of food waned at all? Has the price of rent gone down in terms of people actually spending money on the things that matter? Rent, energy, oil, natural gas, electricity, food, et cetera? That's a scenario that I think is gonna get a more deserved waiting this morning than it was yesterday, because we have a high print in inflation right now. And yeah, all the talk was that March was supposed to be the peak. Well, March wasn't the peak, and March wasn't the peak at coming in at what? Like 8.5% headline number or something? So we're at 8.6% now on that number, and we'll see where we go from there. We got a Fed meeting next week. They're gonna bring it with 50 basis points. I'm sure they're gonna say, listen, we just started this. We were only, you know, they only hiked 50 basis points last meeting. This is the second 50 basis points. They're probably gonna say we're at least gonna go for another one. We'll see how things go from there. But boy, that was not supposed to be the number, folks. This was not supposed to be the number if all is going well. You talk about the jobs number that we got last Friday, right? That was Goldilocks. That was a lot of the term, right? Goldilocks was what I was hearing on Bloomberg. We just back things up to see where we were. What is last Friday, June 3rd? Yeah, June 3rd. Find a June 3rd on the chart. There is Friday action on June 3rd and we got action of negative action in the S&Ps for Goldilocks number, folks. Okay, didn't happen. There was no upside appreciation above 41.50. This market much more comfortable under 42.00 right now until we figure out what's going on. We're sitting at 39.50. I mean, they're talking about 32.00 in the den. You better believe it's possible, folks, when you see the types of moves that you're getting across the board in some of these strong, strong equities. Excuse me, Apple, for instance, down almost 2% today. I mean, Apple, what's that? They lose about 40, $45 billion in market cap overnight. You're trading at 140. I mean, just looking from where you were last Wednesday, folks, Apple has lost $170 billion in market cap from where you were last Wednesday. Jeez, from yesterday, no, from Wednesday alone, Apple's lost $160 billion in market cap. I mean, it's the biggest company in the world so the numbers are gonna be pretty ridiculous, but nonetheless, Microsoft down 2.3% right now. We jumped to Google shares off 2% right now. You basically have the NASDAQ 100 almost off 2%. You're just shy of that number right now as markets continue to stay basically right near the pre-market session lows. All right, we jump around to some of the other companies that are trading lower this morning. Some of them are trading higher. Vale resorts, they are higher after the resort operator posted better than expected results. They benefited from an easing of COVID related restrictions, noted successful efforts to attract visitors outside of its peak skiing season. Yeah, everybody wants to go away and do something, but they give it back with the market pullback. You're still up 2.7% when the market's getting clobbered this morning, so not that bad. Taking a look at a little longer term timeframe for them. Quite a pullback from 376 to 252. They are right back to pre-COVID levels, man. It's really remarkable. Everything got ahead of itself and then everything pulled back right to where we were prior to COVID. I'm exaggerating, it's not everything, folks, but so many equities came back to that price point that we were at prior. You take a look at Amazon shares, right? You get back to pre-pandemic levels. A company like Amazon, Amazon down 3.1% continuing the run lower today to 1,257. Amazon was trading at 129 earlier in the week. You got to multiply it times 20, folks. That's $17 to the downside. That is $340 Amazon would have traded from the peak on Monday to the low on Friday. That was quite a sell for anybody who would have got it on that spike acceleration to 129 post-split for Amazon shares. Amazon, the long run, folks, they're a great company. They're gonna be fine. You check out this company. I mean, you're almost back to where you were in 2018 prices for Amazon getting in at 2022. Yes, they spent way too much money building out their infrastructure, building out warehouses, et cetera. That is gonna wane tremendously on their earnings from last quarter, probably from this quarter is what they told us. But you fast forward things a couple years out. There's nobody that competes like Amazon, folks. I'll tell you a story. I was ordering products from Sam's, okay? And what did I need? So I'll tell you, I needed diapers, I needed paper towels, and I was buying a splash pad for the kids, right? So I got three items I need. Now on Amazon, you would buy those three items and they would tell you exactly what days those each individual item could be delivered. And you could say, put them together to save boxes or whatever, or you could say send them to me as quick as you can. They might say the first item's gonna get there Wednesday, the second item best you can do is Thursday, the next one's gonna be Friday. I say, okay, send them to me, bring them when they come. So I put all of those items, first I pull it up and I got diapers. And diapers can be here by Wednesday or something like that. So I say, okay, not bad. Diapers will be here by Wednesday. I say, ah, you know what? I'm gonna buy some paper towels. I throw paper towels in the cart, I hit go forward, they say those two items will be delivered to you on Saturday. Or something, I said, what the? I can't do that now, I need the diapers now. So then I think I added the splash pad at the same time originally and it said they'll be delivered like all together on Sunday. No option to separate them out. And I say, well, that doesn't work. Let me take out, excuse me, those items in particular, long story short, I had to take those items out and I had to, no matter, when you, if I did two items, it was like Friday. If I did one item, it was Wednesday. If I did all three items, it was Saturday. The thing that made no sense at all is if I did them all individually, they all got here by Friday. So what I did is I placed three separate orders. I ordered the diapers first.  I already got them. I ordered the paper towels next.  They showed up yesterday and then I ordered the splash pad which is gonna be delivered today.  How does that make sense, folks? Okay, and what it is, is it's a testament to the process that Amazon has and how they are leaps and bounds away from their competition, even when you're competing with a company like Walmart that's probably the next in line. I mean, part of the reason why Walmart's had such a pullback recently is they are spending a lot of money to try and compete with a company like Amazon. They are still very far away from that. And I think Walmart has some appreciation too. That's a great stock in the long run as well, man, because if there's one company that can do it, Walmart has the reach. I mean, I think 90% of Americans live within 10 miles of a Walmart right now. Walmart, down half a percent, you're sitting almost right near the 618 of the entire pullback of COVID from a price of 102 to 160. But folks, I was taking screenshots of my phone in disbelief saying, are you kidding me, man? I gotta go through and order them one at a time to get the option to get diapers Wednesday, paper towels Thursday.  They haven't spent the money on the process. Stay tuned, folks. We'll be right back to finish up the program. Sharpening your skills as an investor is like getting better at playing a musical instrument. You have to practice, sure, but you also need excellent instruction from experts. At TFNN, you'll get advice and guidance from the authority and technical market analysis. And it's not just dry tedious text either. TFNN airs live financial content streamed live on TFNN.com and TFNN's YouTube channel with Tiger TV, live every market day from 8.30 a.m. to 4.00 p.m. Eastern. For free, each host is an experienced trader and gives their take on the market while taking calls and questions live from around the world. 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The Chapman Wave up-down sequence gives you an edge in identifying price turns, finding the peaks and valleys in stock prices.  First-time subscribers also get a 30-day money-back guarantee. If you're not satisfied, let us know and you'll get a full refund within 30 days of signing up. TFNN.com, educating investors. Everything in the universe is governed by the Fibonacci sequence. This mathematical principle is responsible for everything from the most aesthetically pleasing artwork to patterns in the stock market. To stay on top of stock patterns you can take advantage of, sign up for the Fibonacci 24-7 newsletter at TFNN.com. When you subscribe, you'll get a weekly report from veteran day trader Larry Pezzavento on stocks you need to pay attention to and you can trust Larry's analysis. After all, he's got 45 years experience as a day trader. Larry will also provide daily charts, videos and data on the key markets that he's tracking. Expect notifications from Larry on market movement you need to act on at any time. First-time subscribers also get a 30-day money-back guarantee. If you're not satisfied, let us know and you'll get a full refund within 30 days of signing up. Subscribe to the Fibonacci 24-7 newsletter today. TFNN.com, educating investors. This segment is brought to you by Think or Swim. For more information, just click the Think or Swim banner on the front page of TFNN.com. Welcome back, folks. So we have the Biden administration. They're gonna be dropping COVID testing requirements for international travel. It's interesting to see how that plays out with the airlines. Let's jump over to some of those airlines. We've got markets falling off, man. I don't think you're gonna need to lift too much to any degree, but let's see. Delta airlines, yeah, you do get a little bit of a pop, but then a pullback. Delta's still negative by about 1%. On that news, you got United. That about 1%, they did catch a bid briefly as well. Maybe on that news for international, United, Hire, American. Yeah, they're all slightly in the red, but we got an S&P now down by 83 points, folks. This number's a little bit of a game changer, so be careful today. This could be a bigger move than you think. S&P's down 2.1%. You got a treat, folks. You got our man Basil Chapman coming up next for the Tiger Technicians Hour. Of course, we got our man Larry Pezzavento, fast market at 12. Steve Verode, Steve White, Tom O'Brien this afternoon. He's doing his time of the trade webinar right now from nine till two. He's gonna get an hour break. He'll be back in the saddle from three till four. Where's the S&P's gonna be by three o'clock when he gets on the air, man? Time will tell to say the least. And I'm gonna jump over with one more that I wanna talk about for CPI. Great tweet out here. Not familiar who Heather Long is. Let's see. Post-economic colonist, okay? Check out these numbers, folks. Groceries, 11.9%. Biggest since 1979. How about chicken? Chicken, one of the healthiest things you can eat out there, man. 17.4%. I love chicken, but man, it's getting expensive. Restaurants, 9%. Fuel and oil, 107%. Electricity, 12%. Rent, 5.2%. Airfare, 37.8%. Services, 5.7%. Largest ever, largest ever. Largest since 87%. Largest since 1980. Largest since 1990. Largest since 1979. Inflation didn't peak in March, folks. And that was the narrative until an hour and 26 minutes ago when we got the CPI number. And who says it's gonna change when we get the June number, folks? Coming up in July. Who says it's gonna change in July when we get August? Yes, eventually you're gonna be dealing with comps against 8.2%. But boy, if we gotta wait six or 12 months, things are gonna get very dicey in this economy, folks. And yeah, always love a good ribeye, a little steak. I try and keep the red meat to a reasonable level, though. Maybe once, twice a week, something like that. I may have some hamburgers tonight, though. Folks, thanks so much for starting your trading day with me. Always a privilege to be here. Thank you so much. Couldn't do it without you. Stay tuned. We got our man Basil's up next. Live programming all day, folks. It's gonna be an interesting one. SP's session lows down to 2.1%. Have a great Friday, everybody.


Welcome to today's session on Predictably Agile by Carl Scotland. Carl, so happy you could join us here today. A little bit about Carl. He heads the TGS Agile Transformation Services practice in EMEA. Passionate about helping businesses become learning organizations. He was awarded the Honorary Brickle Community Contribution Award at the 2013 Lean Kanban North America Conference, founding member of the Lean System Society, limited with society as well, a pioneer of using Kanban systems and strategy development for product development. So Carl, without further ado, over to you. Okay, thanks very much, Isha. Let me share my screen. Welcome everybody. Thanks for joining this session. It's great for me to be back at Agile India again, even if I'm not there in person. I've not been able to travel in person. I was just looking back. I think it was 2013. I was last at the Agile India conference. So when we were able to travel internationally, which has like nine years seems to have been a long time. So hopefully one time one day we'll be able to travel again and I'll be able to come back and be there in person. As I said, I'm currently working for Tech Systems Global Services. We are, as it says in the name, we're a global organization. We work with organizations all over the world. I myself, I'm based in the UK, live down in Brighton on the South Coast. But the great thing of working with someone like Tech Systems is I do get to work with people all over the world. And I've actually just finished early this year an engagement where we did have a great team of Agile coaches that were based in India. So I really enjoyed that. So we're going to talk about predictably Agile today.  Let's do a Mentimeter. So I'm going to switch my share over to Mentimeter. And if you can either scan on that QR code or go to menti.com and use the code there 34112028. You should be able to, well, you probably just see these instructions. So I'll just hold this slide here for a minute just to allow people to get into Menti. And I'm going to ask a question. I'll give you the question now so you can start thinking about it. When I talk about predictably Agile, what kind of predictable? What does predictable mean to you when you think of the phrase predictably Agile? I'm going to flip over then. So you should be able to enter some text. So just add a bit of text, a few words, really short phrase. What comes to mind when you hear the phrase predictably Agile? What kind of predictably? So hopefully we'll start seeing some answers coming in soon. Great, thank you. Meeting goals consistently. I like the word consistent there. Assuming, yeah, interesting. Vision is clear. Deliverables, predictable deliverables, yeah. Dictly impediment as well as the goals for the future, great. Yeah, deliver goals of time. Forecasting, yes, interesting. At least the word forecasting. We might come back to that a little bit. No spillovers. That means delivering everything you said you do and nothing coming in late. Quality, yeah. Great, thanks. Keep on putting those in. I'm going to switch back to the slides now, but I'm always interested to find out what other people think. I think when we talk about predictability, it's important first to kind of understand what do we mean by predictability and what are the kinds of different ways of thinking about it. So this is the way I think about it. And I went and pulled out a definition from the Merriam-Webster dictionary. And I think what's interesting here is the two definitions it gives. The first one, the bit that jumps out to me in terms of the capability of being predicted, able to be known, seen or declared in advance. And I find a lot of organizations when they want to be more predictable, is they want to be able to declare in advance what they're going to get and when they're going to get it. That to me is the most common interpretation of the way about predictability. So the idea of forecasting, can we forecast and use the forecast to declare in advance? Somebody said no spillover, so we know to declare in advance what we're going to get and nothing spills over beyond that. But the other definition is the one that I find more interesting and behavior behaving in a way that is expected. And the things I'm going to talk about, when I talk about predictably agile, are more about predictability of the system in the terms of the system, where the system is our development system or organization as a system. Does our system behave in a way that is expected? And therefore we can have an understanding about what we're going to get out of it. So for me, it's more useful to think of predictability of agile is using agile techniques to help our organization behave in a way that is expected, less useful to think about agile in terms of helping us declare in advance what we're going to get. Because that kind of starts getting us back maybe into waterfall because we start trying to figure things out in advance and doing lots of analysis and lots of design in order to do that. So agile shifts us, I think, more towards definition of two here and trying to move us away from definition one. But why would I, you know, why be interested in predictability in the first place anyway? That the reason I kind of started digging into this and exploring it is because when I start working with organizations really, they want to go through an agile transformation because they want to have more business success. They're failing to deliver or they're delivering poor quality or some of these things you see on this slide are all elements of that they want to improve in order to deliver business success. So we can kind of talk about these six. And five of these six, I've always had a good answer. So if I go into an organization and I kind of talk about these business impacts, these impacts we want to have on the business in terms of helping the business be more successful, then for something like responsiveness and I define responsiveness as can the work be delivered quickly, then we can look at something like lead time. We can measure lead time as a responsiveness, nice easy measure. Sustainability, can we, can work be delivered in the long term? I can measure things like employee engagement, you know, the sort of HR measures we get, employee surveys that gives us a measure of sustainability or maybe we can look at some kind of technical measures around the quality of the code base and use some of those to look at is the code base is sustainable. Do we have a good architecture and a good design? Value, we can kind of get into, well, what's the business doing? You know, how do we define value for the business and hopefully a business has some way of thinking about value, whether it's number of sales, number of customers or some kind of market segmentation. But again, we can usually kind of figure out how to put a number on value. Quality, you know, we can measure escape defects or customer support calls or something like that. Productivity, you know, how much work we deliver and can we deliver work in quantity? It's typically throughput. So either the number of features we're delivering, the number of stories we're delivering or the number of releases we're making or how often we're able to make releases. And then I get to predictability and I've always struggled to be able to, well, actually how do we measure that? Why do you put a number on whether you're able to deliver work consistently and reliably? And it's kind of interesting somebody use the word consistently in the Mentimeter poll because that's trimming what it is. Can we deliver consistently and reliably? How do you measure that? And I never had a good answer. So the things I'm going to talk about are the results of my explorations and experiments in that area to maybe give you some ideas around how you might be thinking about predictability and measure predictability. A lot of this is a hypothesis. So some of these ideas, some of these ideas I have tried out and used and I kind of talk a little bit about the results there. Some of these ideas are still absolutely early days that, you know, I want to dig into a little bit more. I want to try and validate my hypothesis. So my hope is what you take away from this is some ideas that maybe you can go off and try some of these things out for yourself and take my hypothesis and test your hypothesis and maybe even let me know what you learn and what you discover. My goal here, the more people are playing around with this and doing this and trying out different ideas, the more data, the more feedback, the more results we'll get and kind of see. Am I onto something here? Does this make sense? Am I gone down a rabbit hole and I should give up? So let's talk about some ideas then. And before maybe we get into some good ideas and thoughts to measure predictability, I want to just talk about some, one primary way of doing it, which is the idea of the say-do metric. Because this is the measure that I see most common when I talk about predictability. And I don't love it, to be honest. So I thought I should at least explain why and there's two main types I see. One is the idea of velocity predictability. So do teams deliver the number of stories or the number of story points they say they were going to in a sprint? You could argue that could be a measure of predictability. Can they predict what they can deliver in a sprint? So it's useful to agree, but I don't think it's really predictability. Or if it's predictability, it's more about what you're measuring is the idea of going back to the two definitions in the dictionary. Can a team declare in advance what they're going to do within a two-week period? Now a lot of teams, they can't. A lot of teams plan way too much into sprint. So I'm not saying this has no value at all, but I think it's a very limited value. You're kind of helping a team with their planning, but I don't think it gives you any certainly long-term predictability. Any predictability is over that two-week window. So it's a very short term. But the main thing I find with this is it's not really actionable and it sometimes kind of just leads into reactive behavior. So the screenshot here, and this is a screenshot from Microsoft DevOps as your, I just took it from their help page as a kind of interesting example. What I do like about this is it's, this is working on account of work items rather than a velocity. So at least we're not measuring predictably in terms of a made-up number. But you can see, let's take this sprint here. We planned 85, we completed slightly more, there are a few finished late, great. So what have we done the next sprint? We've said, well, maybe we can deliver even more. So we've planned even more, but now we've delivered a little bit less. So the next sprint, we plan a little bit less and deliver less again, plan the same, don't deliver less. So there's always going to be some variation in there. I think with this you can end up maybe overreacting to what you've done in the past. And actually potentially you'll kind of tinkering and tampering with the system almost rather than kind of thinking actually, long-term, what does the business need and what's that long-term predictability. So useful in some situations, but to me, I don't think it's a great measure of predictability. The other one that's common at the moment is the idea from SafeScale Digital Framework on what they call program predictability. So here, for those of you not familiar with Safe, I'll describe how it works. At the end of a PI, PI is a program increment, which is typically a number of sprints, typically around about three months, two or three months' worth of sprints. You say what your objectives are to that sprint. So the plus point here and the thing I like about it is it's more objective-based rather than just did we deliver stories. So it's getting more towards the value that we're delivering. You put a number on that value, but it's a fairly arbitrary scale of one to 10. So it's a bit of a made-up number for value. And then at the end of the PI, you track what you actually delivered in terms of that objective. So we can see this top objective here. We said it's had a business value of seven, and we think we've actually delivered seven, whereas the fourth one down, we thought it had a business value of 10, and we think we've only delivered a five. You can then calculate this percentage. So what percentage of the actual, of the planned objectives do you actually deliver and chart that over the PIs? And the idea is that you're probably not going to be delivering 100%, but you should be delivering about 80%. You can track it by individual teams and then look at the overall. Again, it's kind of made-up numbers again, which I don't like. And I think all you're doing is measuring how well you are at planning what you're going to do within the PI. And again, a lot of organizations, there's value in doing that because they clearly have no idea about how much to plan and they over-commit and they over-plan. But I'm not entirely sure it really gives the business any long-term predictability. It may be a step towards it. So I wouldn't say don't do this, it's bad. But to me, this is another example of this idea of say-do, not really what I think of predictability. And I kind of like this cartoon as a way of summing this up. Quite often we're just making up numbers to try and prove a point. But they're not really telling us anything meaningful and they're not telling us anything actionable. It's just, hey, it looks like we're saying what we said we were going to do using this set of numbers that we've made up. I'm not a fan, as you've probably picked up by now. Okay, so if I'm not a fan of that, what else can we use? So I'm going to introduce the idea of lead time variation, because this is where I started and I think there's some value in this. So I'll talk about lead time variation and introduce how we might be able to use the idea of lead time and variation in lead time to give us a better feel for how predictable we are. And this is getting into and starting pulling some ideas for Deming. So by measuring lead time and the variation of lead time, we're looking at the process as a whole rather than just our ability to plan. So this quite here, a process that is not in statistical control has not a definable capability. So what's the capability of the system? And then if we can say that that capability is in control, then we can say the performance of the system is predictable. And this is moving into the idea of more probabilistic thinking and probabilistic forecasting and less deterministic planning. So those say do measures to me are more deterministic. They were just trying to, what do we plan? Did we do that versus what's the probability of us delivering a bunch of things by a certain date and the risks around that? So much more kind of system thinking based. So here's my hypothesis. And this is a lead time or a cycle time. And I personally, I use those teams fairly interchangeably. But what this shows us, the horizontal axis, we have time. And you can see dates along there. On the vertical axis, we have cycle time or the lead time. So that's the number of days it takes to complete something. Each dot represents a piece of work. And what we can see where the dot is horizontally tells us the date that piece of work was completed when it was moved to done and how high up that dot is tells us how long it took to complete the work, the elapsed time from starting the piece of work to finishing it. And by looking at a range, a time range and all the pieces of work over that time range, we see this, the behavior of the system. And I've got to kind of split the data set in two halves here. On this left hand side, you can see there's a wider variability. So when I talk about lead time variation, there's a wider variation or a wider variability of lead time cycle times for the completed work. And then on the right hand side, you can see it's much narrower. There are fewer items that had a longer cycle time. The wrong button. So this was my hypothesis that the data on the left or using the data on the left, the system on the left is less predictable than the data on the right, which is more predictable. And the reason for that is because there's less variation in there. So that's the basic hypothesis. The less variation you have within your system using lead time to measure it, the more predictable you are. Now, actually, Deming would say, if I'm going to jump back to the Deming quote, Deming would say that a system either is predictable or it's not predictable. I think he'd say that he's not around to tell us anymore, but that I think that's my understanding of his work and chatting with people like Dan Vakanti, who knows a lot more about this than I do, that's his view as well. And the idea of becoming more predictable doesn't make sense in the way Deming describes it. And I kind of struggle with this because whoever might argue with Deming, he clearly is much clever and brighter and knows much more about this to me, but I have this hunch. And the conclusion I came to is that while both of these actually are equally predictable, what we mean by less predictable here is this predictability is less useful and this predictability on the right is more useful. And when we talk about helping organizations to be more predictable, what we're really saying is we want the data to be more useful in helping an organization make predictions and do their planning. So I'll dig into that a little bit more. What do I mean by more useful and less useful? So the other thing we can do with this chart here, this cycle time chart, is look at centiles. And this screenshot here is from a tool called Actionable Agile. And I'm just using a sample data set that they have in their demo version. But it's a really nice tool for visualizing this data and starting to pull some of this information out. So this shows us that 85% of the work, which is 85% of the dots are below this line, which means that there's an 85% chance of work being completed in 16 days or less. And that's based on having this idea of a stable system. In the past, this data set has delivered 85% of work in 16 days or less. Therefore, assuming the system behavior stays the same and the mix of work stays the same, there's going to be an 85% chance in the future. The other thing we can take from this is that there's a 20% chance of work being completed in two days or less. So there's a very small chance, a fifth of the work gets completed in two days or less. So we've got that 85% chance and the 25%, 20% chance. And I've picked, so 85% is a fairly standard number. I've picked 20% just because that was the easiest thing with the data. What I'm really trying to get at is, there's now a gap between the 20% and the 85%, which is 65%. So there's a 65% chance of work being completed between two and 16 days. So when we go to a business and they say, when's work going to be done? We can say 85% chance, most likely it can get done in 16 days. But you know what? We might deliver it in two days. To me, yes, that's predictable, but is that useful? Because that 16 days could be 160 days or 16 weeks. It could be a really, really long time. And if the business wants to plan, okay, knowing that you might do something in 16 days is great. But what happens if it turns up in two days? You've kind of wasted those 16 days, haven't you? So to me, that's not so useful. If that gap of 16 days is a much bigger gap, yes, it's predictable, but it's not so useful. Whereas if we reduce that gap, maybe it's more useful. So what I did was I took the data set and basically reduced the cycle time of every single, the lead time, cycle time of every single work item by a half, plugged it back in. And so now we can see there's an 85% chance of work being completed in eight days or less. 20% chance of work being completed in one day or less, which means that 64-hink gap is now eight days. Equally predictable, but more useful. Because now there's that narrow window when the work might be completed, and therefore the business can plan around that much better. So that was my hypothesis, that narrowing this variation gives us a better system is more useful predictably. Can we measure that? Now, obviously, the simple way is just kind of go 16 days down to eight days. That's numbers come down. That's the obvious answer. I tried, and I thought there's got to be a clever, more statistical way of doing this. So I tried a couple of ways. One is the notion of cycle time inequality. So I kind of got this from the idea of income inequality where they compare the P90 and the P10. So that's the 90th percentile and the 10th percentile for income. So 90% of income is this or 90% of the population has this income. 10% of the population has this income. If that gap is narrower, that's then there is more equality for income. So we could do that for cycle time. Just divide the two. So in my data set one, my P85 was 16. My P20 was two. So I can say my cycle time inequality is eight. Calculated the same for data set two. And this is kind of surprised me, but shouldn't have done in hindsight, my P85 is eight. My P20 is one. My cycle time inequality is exactly the same. So this was a kind of a big, you know, my hypothesis has failed. Cycle time inequality may be not a good measure. I still think there's the variability is something interesting, but cycle time inequality, not a good way of measuring it. Hypothesis two maybe then is look at the coefficient of variation. That's the ratio of the standard deviation to the mean. Don't too worry about all the kind of the detail maths in here. I probably should have warned people at the start of the talk that I'm kind of get into a bit of maths and statistics. I'm not a mathematician myself. So I'm trying to keep this as simple as possible, but we're looking at the ratio here. You can go online, figure out standard deviation mean trust me on these numbers. I'll have double checked them. But in that data set one standard deviation 7.33 mean 9.37. So the cycle times coefficient of variation is 0.7 eight. What if we do the same for data set two? You end up with a cycle time coefficient of variation of 0.76. No, it's basically the same. I think the difference is just to do with the way some of the things got rounded when I when I halved the cycle times. But again. Okay, turns out cycle type coefficient of variation didn't work. So I'm kind of a bit stuck now because I've still got this hunch. My I still have kind of clinging on to this hypothesis, but I've not found a good way of measuring it. So that led me to the idea of, well, okay, if we can't measure it. So well, two things. One is why is why why why have those numbers turned out to be the same even though my hunch is correct. My I still have this hypothesis. And what I came to the idea is what I really want to do is is reduce the upper items, but not necessarily that the items that have a long cycle time, but not necessarily reduce the items that have a short cycle time. So what can we do to tell us when things are taking a long time and worry about those things rather than worry about the things that are already flowing through the system quickly. So that brought me to the idea of leading indicators. So the idea of a leading indicator and a lagging indicator, the lag measure is the trailing measure. So that's that's our ultimate goal. So the lag measure might be something around actual predictability that might be measuring that variability. The lead measure are the ones that actually impact on the lag measure. So the lead measures give us an indication of things that we can measure that we think will predict that we achieve the goal and things that we can influence. So these definitions come from a book for disciplines of execution that I really like and it kind of takes that idea of the lag measure being the overall goal, but you can't always influence those. The lead measures are things that you can influence and you think are worthwhile working on. So what would the lead measures be if we wanted to measure and improve predictability. So go back to our cycle time chart. As I said, what we want to do is make these items, these items that have a long cycle time shorter, we're not necessarily worrying about making these longer or even making these any shorter because we're kind of quite happy to get something in two days. So the focus is on understanding the things that are taking a long time and working on those and maybe if we can do those then that brings down the variability but doesn't and does it in a way that that's more meaningful. So that means we need to pay attention to aging whips. So this is another chart from Action Volagile and I'll kind of just step through this to explain how this works. And this is using the same data set. So we can see that when something's done, we already know that 85% work is done within 16 days. What we can do is take that and step back through the process and work out that actually 85% of the work is in testing in 14 days. 85% of the work gets into dev done in 13 days. 85% of the work gets into dev active in 10 days. 85% of the work gets into analysis done in five days. So we can see not just the percentage of the work that gets to the end of the system but the percentage of the work and how long it takes to go through the various stages in our workflow. And this is a, you know, a major workflow. The actual workflow doesn't make any sense. So we can look at the actual work in progress and compare it to the historical aging of work. So how is work aged historically? What's the current work? So we've got three items. So this little three on this dot here means there's actually three that single dot is representing three pieces of work. So these items already have a more than 85% chance of taking longer than 16 days because they're already slower than the most of the work that has typically flowed through the system at the typical pace. So this gives us an early indication that if we want to start bringing down our lead times, these three are already going to have a long lead time. So we should pay attention to these three. So looking at aging whip and starting to measure the age of whip and looking at reducing the age of whip gives us a way of maybe a leading measure towards predictability. So we can look at things like again, another screenshot from Axiom Lajal. What's the whip age today? And this is looking at average whip age compared to last week, compared to last month. I'd love Axiom Lajal to kind of just give us a better chart to visualize this. We can see here that last week our average whip age was lower and before it was even lower. So we can see here with this data set, our system is becoming less predictable and not more predictable. So whip age, looking at whip age, I was chatting with Dan Vikandi and his critique saying what would it look like if you measured total whip age? You took all the dots of all this work in process and just aggregated together and used that as a single metric and used that as a single metric. So we can see here that the whip age is now and over time might be another way of looking at it. The other way of looking at it then is looking at blockers. So what are the things that cause a piece of work to age to stay in progress for a long time? Typically it's because things get blocked and maybe there are some things that are that is kind of taking this notion of actually maybe if we start tracking blockers and managing and doing some analysis on our blockers better then we can start reducing those blockers and therefore we start reducing the age of work in progress, work flows through the system more quickly, the system becomes more predictable or the predictably the system becomes more useful. So you've got a number of blockers but it's colour coded by how long that those pieces of work have been blocked by. So here you can see there's about 25 pieces of work that have been blocked for more than 30 days. We want that to be coming down and we can see that here trending over time where down here we've now got less than 10 pieces of work that have been blocked for over 30 days and you can see the number of pieces of work with blockers going up. So this gives us an indication that we're managing our blockers. And then blocker flow this is the net flow of are we creating more blockers than we're resolving so it's basically the number of blockers raised minus the number of blockers resolved gives you the net flow and ideally you want to get to a point where this is hovering around zero probably maybe you know if you've got a lot of blockers then you want to be resolving more of them but once you kind of get into that steady state blocker should be coming and going fairly smoothly. So measuring blockers is another way of looking at how do we reduce those long cycle time pieces of work in progress so we can start narrowing the variation of our lead time our cycle time and therefore that makes the predictability of our system more useful and we can start doing really good forecasting with that. So this is my kind of current hypothesis that I'm currently working with and testing so I believe that measuring blockers will result in less aged work in progress which result in fewer long lead time work items which will make the system more consistent and by consistent I'm kind of saying that that variation is the variation is narrower and that will make the predictability of the system more useful and we'll have confidence in that hypothesis when we start seeing stakeholders place more trust in the plans and forecasts it's not that going back to our definition it's not that they know exactly what they're going to get it's not that we can declare in advance but we have more confidence in the plans and forecast we kind of can trust them more because we have a better understanding of the behaviour of the system and therefore we have a more useful data to make those plans and forecasts. So that's kind of where I am so I've just kind of done a fairly quick go through I'm kind of interested in people's reactions to that so I'm going to go back to another Mentimeter poll so it's kind of go back to this one here and just go on to the next one so if you go back into the Mentimeter same one the codes at the top if you close the window go back to 34112028 how do you feel about that these ideas that I've just talked about because some people kind of the idea of predictability makes them nervous so I'm kind of curious do people still think it's a terrible idea and we shouldn't worry about predictability people curious about it curious to learn more about it or do people kind of think they really want to go out and try this I'll just let it look like we had about nine people respond last time so I'll just give a bit of time to people result to submit their answers and then I'll show the results we'll see what people feel about this Carl speaking of curiosity there are two questions from people when do you want to take those so let me just kind of finish this poll and then I think I've done so yeah we should have five or six minister to answer some questions at the end so let me do this oh great nobody thinks it's a terrible idea that's always reassuring those people are curious to learn more ask some questions now at the end I'll come to the hangout that I'll be going to straight after that I'd love it if people were trying out some of these ideas testing the hypothesis and let's share what we learn so I'm going to go back to the just quickly go back to the slides then I think that was yeah so I guess there's something I'm kind of always nervous and this is this idea that people worry about predictability is they worry that sometimes we would we're trying to be too precise and we're not kind of allowing for deviation so I just want to kind of emphasize that that's not what I'm talking about when I'm talking about predictability it's not that idea about being able to declare in advance because there's no deviation there's no variety there's no variation in value we do have that and that's why I kind of shift towards more that behaviour based definition of predictability so a couple of quotes which I kind of think are interesting and amusing the one is the Frank Zapper quote without deviation I can't see the full quote because I've got the zoom power bar is in the middle but you know progress isn't possible without deviation and then the one that always kind of comes around every Christmas deviation from the tone will be punished unless it's exploitable so Ruda for the red nose reindeer deviation from the norm but actually a lot of value in there so it was exploited so we need deviation because we don't make progress and that's a lot where the value is but we can still be predictable if we understand that deviation we just kind of manage it and make sure that it doesn't get out of control great so thank you so I think as she said if there's some questions in there let's take those questions and I'll I shall share the slides later I think there's a way of sharing them within the conference system I'll try and figure that one out I'll probably put them on Twitter as well so let's stop that and yeah let's take some questions the first one is from Joel Rosario he says or he asks I love the second definition of predictability however how does this relate to story points or t-shirt sizing in which historical measurements of the team's execution is used to predict what will fit in the next print yeah so I hopefully I maybe answered that when I started talking about the say do measures but yeah that's why I think using story points and my preference is always to you know just do story counting I'm not a big fan of estimation so yeah great so Joel just kind of put a comment that we've answered it so yeah I just kind of just summarise yeah that idea of story using story points gives you an idea of how you're good at planning in the short term not necessarily useful for long-term predictability the second question is from Gayatri Ishwaran she asks can you help us with the tool used to achieve the reports shown in the slides yeah let me can I type let me it I'll type the answer into the sure sorry into the the zoom answer so it's a tool called Action of Agile so if you google for Action of Agile then that's what I was showing there's I think I put a link to it in the slides as well let me just go and double check whether I did that or not yeah so it's actionofagile.com and actually the other thing I can do maybe I'll just put this in the chat there's a there's a URL so let me you can put it from the chat otherwise yeah so there's a URL and this is on one of the slides to a blog post so one it will take you to the Action of Agile website so you can find out more about the tool but they have a blog so it talks a little bit about predictability as well but it is kind of where I got that idea of the screenshot from as well so hopefully that answers the question on the tool itself it's there's a number of variations but one of the things it does nicely so I mentioned a client we were working with recently with some coaches in India we used Actionofagile and they have a Jira plugin so if you're using Jira you can get a Jira plugin it's not free but then basically those reports get generated directly from your Jira configuration so it's pretty powerful okay are there any other questions in the chats generally none so far anyone has any please put them out on the chat I had one call predictable and thing about blockers so I was wondering is there is it something about trying to predict which of the work items might run into blockers not necessarily but I think one of the things you can sometimes ask in terms of a definition ready I think teams often start a piece of work knowing that it's going to get blocked so it's not about predicting that it's going to go but sometimes teams know that we have a dependency here that dependency is not resolved but they start the work anyway so there's sometimes the idea of don't start a piece of work unless you have confidence that you can finish it without it being blocked now that's not a guarantee and sometimes work gets blocked for reasons that are out of our control so there's kind of the anticipation of blockers and not starting work but I think the way I was describing blockers is just as well that's one way of reducing the number of work items getting blocked because if you start a piece of work now it's going to get blocked you're kind of asking for it to have a long lead time okay thanks everyone Kaal thanks so much for this session new insight and I'm sure we got a lot of information by joining the session


Emma Raducanu, who has been under fire over the last couple of days by former players, including Daniela Hanchakova, who came out saying that Raducanu's losing the respect of other players. Let's start with some of the comments that Hanchakova had to say about Raducanu. So this is what she said. That was a tough one for Emma. I think it's going to hurt big time because of the chances she had. She was the better player for most of it. But the thing is now with Emma, everyone wants to beat her. Everyone is trying to figure out how to play against her. All the locker room respect she had after the US Open is now kind of going away, which is a shame. It is going to be important now for Emma to regroup, rethink what she has to change, and get out there on the practice court. At that age, you want to be fit. You want to show everyone that you are out there no matter how long it takes. It was humid and it wasn't easy out there. But this is where you have to be tough and if you want to win matches like this, if you want to win tournaments like this, and I believe Emma has the level, she just has to find a way to get it out of her. So those were the comments from Handja Kober in after the match on Amazon Prime, I'm assuming. It doesn't seem like she's overly critical, but again, maybe the choice of words, saying that losing respect and all that kind of stuff, I already kind of actually came out and defended herself against those comments. And I think people are going to put one and two and two together and be like, okay, well, yeah, she has all these sponsorships and she's too busy driving Porsches and taking, at photo shoots and premieres. She's not on the practice court. She's not even practicing anymore. She's just too busy doing other stuff. And that's not true. She just doesn't publicize that she's in the gym every day. You know, she doesn't, you know, she puts the sponsorships on because it's probably part of her sponsorship deal that she has to promote the products, right? On her social media.


White shirt, now tippy toes creeping Down along the creek, I remember something Who then first preached that I was a name? This ain't for the best, my reputation's never been worse off You must like me for me, you can't make Any promises now, can we baby? You can make me a drink Roses on both my knees, where you don't say I'm the bad type, your girlfriend mad type Might seduce your dad type I'm the bad type Duh