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Two weeks in the past in Barcelona, I had the out of the ordinary opportunity to see the just-unveiled HP Multi Jet Fusion 3D printer in person. while my first glimpse of it turned into in a presentation, with the printer and processing station sitting vibrant and new of their respective corners of a room built more for PowerPoint than for industrial printing, the team at HP were additionally aware that the premiere solution to in fact learn about new tech is to see it in motion, and to hear from these at the back of it about its construction — and so the dozen journalists and analysts gathered in sunny Spain also had the exciting event of touring the inner most HP 3D printing labs, the place we noticed ten of the MJF machines in motion.
afterward, i was capable of sit down down and listen to without delay from one of the crucial executives at the back of the complete 3D printing business there at HP, and located out greater counsel at once from Stephen Nigro, President of HP Inc.’s 3D Printing enterprise, and from J Scott Schiller, vice president of Market construction. talking to those two pros who were with the technique of establishing the all-new MJF technology certainly helped to shed some light on the whole process. When HP got down to re-invent 3D printing, they in fact supposed it — and the greatest key to their method became taking note of valued clientele and discovering what the market desired. As a second powerhouse for decades, the enterprise had significant experience to attract from so far as product construction. 3D is, of path, its own box, and as a corporation stepping in to enter in a huge means, HP took step returned to definitely commit themselves to the R&D crucial to find everything obtainable to them so far as each shoppers and expertise are concerned. HP isn’t trying to simply enter the market; the plan is to lead the market.
Stephen Nigro, in a session at HP Barcelona, offered to us a scenario indicative of one of the opportunities and thought approaches amongst notion leaders within the tech neighborhood: at CES, a massive tradeshow and sizzling-spot for tech, on the end of the day, a large line forms on the conclusion of the lengthy, busy day of conference pastime. This line is on the taxi stand, as all and sundry seeks to return to the refuge of their resorts. As Nigro joined the road, which had an estimated wait time of 45 minutes, he realized he had yet another choice: he pulled out his mobilephone, referred to as an Uber driver, and become picked up within minutes. As he pulled away, he saw that the road at the cab stand had barely dwindled, full of excessive-powered consultants in plenty of high-tech fields. This example illustrated to him a major aspect: a decision must be made in adopting new solutions. In a lot the identical approach, the adoption of HP’s MJF 3D printing know-how will always be a call by using people who might improvement from the technology.
“soon satisfactory, I’ll be taking a look at stuff and pondering, was this 3D printed or no longer?” Nigro instructed me from throughout a table, holding up his pen (which was now not 3D printed). I requested when he concept that query can be requested greater generally. “Mainstream? I’d like it to be sooner than later. I don’t be aware of. To be honest, I don’t recognize the reply to that query. the realm will be embracing 3D and how it works, for certain, much more so. The big query is not if, it’s when. That’s really the wonderful component right here, you realize it’s going to occur, you see the opportunity. There’s a lot of items — behaviors ought to trade, it can also be surprising how lengthy it takes americans to alternate behaviors. You should make that aware alternative, people will have to make that conscious option to trade.”
And here’s the place his Uber analogy came in to play. What changed into it, I asked, that had made him pick up the phone that first time he called an Uber as opposed to look ahead to a cab?
“It’s form of who i am,” Nigro informed me. “i admire to are attempting new things. I suppose for me to be a high-tech govt I’m always analyzing about high-tech traits and need to try new things. I don’t always at all times get them, I don’t get Twitter. if you look at my Twitter account, I’m now not active, as a result of I haven’t gotten it. I’m very energetic on fb… I always wish to try the new issues. There’s that intellectual curiosity, actually — how do issues work? a part of it's, in case you’re going to be a pacesetter in high-tech, you’d more suitable be in my view experiencing it, because that helps you be a pacesetter. i will tell you, that entire open substances, open platform? it would were very easy to do what we now have performed in our current business. It become variety of pleasing. That resolution was made maybe a week earlier than our announcement in October . We were on a cellphone name getting in a position and that i’m like, ‘Guys, we’re going open’. They said, ‘Ahh, no, what, Steve, why’ and i instructed them, ‘the realm’s open, the area’s open. If we’re building a business for the next 10 years, 15 years, two decades, we enhanced be open.’ we will’t build our business like we've during the past. if you’re going to be leading, going to be considering, you need to definitely bear in mind how the area works versus how it labored.”
build up the brand new enterprise — as an open platform, no less, a new method for HP — required taking a huge step back and engaging the total team’s intellectual curiosity. talking with Scott Schiller supplied a fascinating point of view on simply how essential this curiosity turned into. no longer simply asking the right questions, however in asking them of the correct americans, on the right time. where are the alternatives, and the way are they foremost approached?
“I would say the element that we’ve turn into fairly first rate at as an organization this is both a material science company and a computer tech enterprise is understanding what we’re in reality decent at and making an attempt to take each the know-how out in addition to take the consumer view in, and kind of labor that from side to side except we identify areas where issues definitely seem to join,” Schiller defined to me. “That’s what drove us to the four purposes, the 4 verticals, that we identified. within those, then you need to in reality beginning drilling right down to use cases. I suppose one theme we see very certainly is there’s loads of probability in aftermarket, spare materials, and that’s variety of a theme that performs across the verticals, so that’s a neighborhood we’ll be paying lots of attention to. … That’s in reality the secret sauce in using know-how adoption. If we’ve realized anything over the last 15 years, it’s that you ought to remove the facets of friction. There’s a lot of americans who can say no when it comes to making these purchases, and you have to eradicate as a lot of those facets of friction to get the know-how in the door. once it’s in, then americans delivery to get truly creative with it and it actually blooms. loads of instances what individuals are attempting to do is focus on the tremendous-interesting, inventive software because the factor to get everybody focused on, however you under no circumstances get past the grownup who can say no. We’ve realized that it definitely comes all the way down to economics.”
A key part of HP’s approach to getting into the market is in doing so viably. To that conclusion, they recognized four key verticals, as Schiller referenced above, so as to kind the foundation of their center of attention upon entry. Aerospace/protection, automotive, medical/dental/lifestyles sciences (fitness care), and numerous customer purposes will kind the basis upon which this entry is constructed. A key component of each of those verticals lies within the price of utility- or affected person-certain creations which are indeed smartly-serviced by additive manufacturing technologies.
“All of those are — to call them a vertical is just a little of a misnomer, these are huge, huge industries,” Schiller instructed me. “And so we've a lot of work to definitely dig down. The procedure that we work through is we both have very systematic, McKinsey-esque sorts of strategies to market evaluation, very analytical. at the same time, we like to steadiness that with people who actually bear in mind the use circumstances. in the end, it’ll come all the way down to the elements, the use situations, the price that’s created. There’s somewhat of a simultaneous correct-down, backside-up approach and we’ve found that to be probably the most successful mechanism. The other factor i discussed that I suppose is critical is to all the time have a bit of variety on your approach, however no longer too much. focus is in fact important. To be clear, it’s nevertheless very early days when it comes to figuring out — the style we think about our firm is that we’ve received a superb neighborhood of americans who truly take note the average uses of 3D printing, for quick proto and things like that, but we additionally should have superior teams that are taking a look at intermediate functions, tooling, bridge production, and sooner or later to final part manufacturing.”
In taking note of their clients and working to truly create a working AM answer that might deliver conclusion-to-conclusion solutions — some extent that every one HP presentations in Barcelona saved coming lower back to is that here is an entire method to an answer, and fashioned to maintain economics at its coronary heart — the building of the gadget modified from the initial announcement in October 2014 throughout the equipment being unveiled nowadays at fast, and considered in the labs in Barcelona in addition to in beta shoppers’ labs for some months now. I had for my part been shocked by way of both-computing device equipment represented in the MJF answer. How did that come to be? Nigro instructed me about some of his strategies on the predicted reaction upon its unveiling, and the way pre-saying their entry to market became out to be a improvement:
“I consider they’ll see that we’re designing more than a desktop, we’re designing an end-to-end adventure. It’ll take somewhat of training. Like for those who guys first saw it, you weren’t rather bound the way it all works collectively. but once you be aware it, that you can see — and you may additionally see the way it’s very plenty centered at scaling. And once more again to this studying. That become not a part of our plan once we first announced it lower back in 2014. I imply, we knew we essential something submit-processing, however not this type of solution — that changed into best through this agile client engagement system, interacting with purchasers precise time in our lab and we realized there changed into this pain element right here and we ended up developing this. It in reality got here on fairly early. It’s definitely the improvement of basically pre-asserting, we had nothing to lose in our case. The chance you run if you happen to pre-announce some thing new, everything that’s historic, you quit selling as a result of all and sundry’s going to look ahead to the brand new aspect — however 3D, we had nothing. We have been new to the market. Pre-announcing allow us to have interaction and learn a whole lot about the market.”
Schiller, as I spoke with him, also touched upon these facets in a method. Honing in on the essential nature of listening to customers, we noted how Shapeways become an outstanding checking out box for MJF expertise. Shapeways’ CEO, Peter Weijmarshausen, spoke to us in Barcelona as well, with some regular slides from his presentation at interior 3D Printing NYC remaining month, as he shared his imaginative and prescient of 3D printing’s region in the next industrial revolution. It became no accident that HP and Shapeways were working collectively, as Schiller noted that americans like Weijmarshausen stand out as beacons in the business.
“It’s a humorous factor,” Schiller referred to, “because there became some extent where we had the commentary that we had mind-blowing expertise essence. We had this modular thermal inkjet structure and we knew, we knew that it will observe to market spaces we had certainly not participated in earlier than. So the query is, what is the most efficient method to establish the way to participate in those markets? and that i believe historically what americans do is kind of by-product. They take an incremental step relative to what they’re doing right now and what they know at the moment. I think the issue that we did that turned into different is we stepped method back and tried to look on the greater photograph, and consider what is probably the most profound application of this know-how, and recognized actual concept leaders in the business. We try this in 3D, we did that in second, and these are the individuals — there’s simply a certain profile, you comprehend them when you see them. Peter is exemplary, he’s a true idea chief, he is aware of a way to simply make things happen. He has a imaginative and prescient and is aware of the way to get individuals at the back of that imaginative and prescient. I think one among issues that’s most important about what he does is everything he does is for the consumer, they take it to such extremes. I consider for us it became a similar method. We worked in fact, in reality carefully with the consumers and simply listened.”
In talking with valued clientele and with notion leaders like Weijmarshausen, HP was capable of draw from natural journey and spot how they might optimize future experiences.
“whatever that Peter begun hitting on is anything that we see is a very important fashion, and that is — we have been speaking with, we’ll say a extremely, definitely large appliances company,” Schiller referred to. “one of the vital things they shared with us is that historically they could’t entertain the theory of a brand new product until it’s going to promote a whole bunch of thousands. And the difficulty is, is that lots of times you don’t get to a whole lot of heaps of income of anything except you've got a duration of ramping it up. There’s been a big hole in between. What they see because the promise of 3D printing is to be in a position to support bridge that gap, and at the same time allow for greater creative processes in that hole, and out of that may still come a lot more edition of items which are provided after which as a derivative of that, what you’re going to see is that things should be less homogeneous, extra diverse. All of that's suitable for additive manufacturing.”
HP is already working with four substances businesses to improve powders with different capabilities, and these suppliers bring gigantic expertise to the desk that HP has been discovering valuable — and which they hope to see greater of as time rolls on. In discussing their open strategy to substances capabilities, I asked Nigro when he notion that platform could start attractive to even more suppliers.
“relatively brief. Two of the 4 have come on in precisely the final three months. Two months? It’s a further story behind a narrative. as soon as we introduced it, we needed to figure it out. For an open platform to work, americans ought to improvement from being on it. Why would they be on it in the event that they’re not making the most of it? We had to figure out the enterprise mannequin, reply loads of questions, be very agile in rolling it out, speakme with them. We realized plenty, we discovered a lot. doubtless the greatest factor we discovered in speakme with materials suppliers, these expert fabric agencies, is — here's what they do. likely the biggest gaining knowledge of for me is what they do is advance vertical functions. If I’m developing a cloth I have to then go and figure out a way to use it in aerospace or client products. They’re truly good at it. we now have a great deal to gain. by means of leveraging these fabric suppliers who're going to be on our open platform, we’re really going to advantage from that in a different way. probably the most four referred to to us one evening at dinner: ‘We need the area to understand that we’re partnered with you on your platform.’ We had been trying to determine this out, and noted, well, why? ‘smartly, we need to go tell all our shoppers that we’re partnered with HP on Multi Jet Fusion and that we are looking to advance new functions with our purchasers.’ That’s a extremely first rate cause. That became a learning for us — we didn’t be aware of that, we have been considering we were going to must build all these vertical capabilities and we still ought to increase some. I won’t get into numbers, but we checked out numbers on one industry and concept, my gosh, we’ll not ever have that many people in that industry. That become one business. So I feel the actual advantage to us turned into taking a look at that researching manner and leverage the world, leverage what individuals do well. I consider we’ll get more and more. i am hoping there's. There’s no other way we’ll get the breadth of cloth decisions crucial to really have this component in manufacturing creation.”
Nigro moreover filled me in on a few of his innovations concerning the capabilities and future of the software crucial for the way forward for 3D printing:
“smartly the software, we’ll in fact be delivery the up-front adventure with the client, truly hitting that conclusion-to-end answer, I think that’s a superb starting element for us. I think what’s interesting is the expertise for the software. What’s interesting is eventually it’s going to be a battle. How do you use the vigor of the cloud, compute, keep, come up with new designs and have assisted designs… I think that’s so nascent. It’s a little of this hen-and-egg. americans now are going to be capable of design parts in a method they’ve on no account been able to design earlier than, because you couldn’t make it. I believe the inventive element of utility is tremendous unique. I believe this is going to be a great probability for someone in the business to turn into a leader.”
Of path, all of this is in response to the thought of economic viability; it’s no use having a very good product if it’s no longer going anyplace. a primary improvement of AM is its ability to do greater than injection molding can, when it comes to geometries, customization, and other creations that require no molding.
“We work a little bit with the Ellen MacArthur foundation, which is concentrated on the circular financial system,” Schiller instructed me. “The complete premise there with our technology is we have the option to make things that are fundamentally greater valued — personalized, custom-made, whatever thing. with the aid of virtue of it now not being homogeneous it is more prone to be valued and because of this is much less more likely to be thrown away or wasted. the world of homogeneity the place everyone receives the same factor is a pretty wasteful world. We see a fine possibility to force bigger value and fewer waste.”
Breaking the mold (pun supposed) and taking us faraway from a homogeneous place of work, the HP MJF equipment certainly sounds promising. And, sure, it looks awesome — gazing it in motion and maintaining printed items become somewhat an journey. In all, then, I had only one question left to ask:
what is your personal favorite thing in regards to the machine itself?
“I simply love gazing it work. I suppose anybody are a bit captivated in the theory that you should build things up rather than the average world of slicing things down and molding and milling away. The fact that now you get geometric complexity as an awful lot as you need — the possibilities there are profound and galvanizing.”
“i might say my favorite component concerning the new product is what it may well produce. I imply, the computing device and the product is all sort of cool and blah blah blah, but what concerns is what definitely it produces. it may possibly seem to be first rate, it will also be slick, it can also be attractive, but what can it in reality make? It’s the splendor that may be in seeing what comes off the machine. It’s about the output.”
That’s lots of exquisite counsel to soak in from HP! What are your techniques on the brand new technology? inform us within the HP Discusses New 3D Printing know-how with 3DPrint.com discussion board over at 3DPB.com.[All photos taken on-site at HP in Barcelona by Sarah Goehrke]
In 2011, Hewlett-Packard paid $11.1 billion for UK application company Autonomy – a sixty four% top rate for an organization with virtually $1 billion of 2010 revenues, and possessing “a constant track record of double-digit revenue growth, with 87 p.c gross margins and forty three p.c working margins.” in order that they idea. Little greater than a 12 months later, HP recorded an $eight.8 billion impairment charge, citing Autonomy’s accounting improprieties as the rationale. traders wondered how might HP have gotten it so incorrect before they plunked down $eleven.1 billion in money? and that they questioned what HP uncovered that resulted in the writedown.
Now we comprehend. In mid-November, the SEC ordered the previous CEO of Autonomy’s U.S. operations, Christopher Egan, to fork over $800,000 of compensation because of the takeover, during which HP relied on figures he had helped inflate. The information of the case at the moment are public. besides the fact that children this case involving existing IFRS revenue cognizance rules, it may well happen again, and to any business.
One fact truly stands out: in each of the ten quarters previous the acquisition, Autonomy’s revenues had been within four% of analyst expectations. That’s a level of precision that should still arouse suspicion. In hindsight, reaching income pursuits like clockwork looks awfully strange. right here’s how they did it.
Autonomy’s UK-primarily based senior managers directed a application swelling revenues by using pretty much $200 million. Autonomy bought its utility via “price-added” resellers, legit corporations featuring extra features and assist to product end users whereas also selling Autonomy’s application. just 5 resellers, in 30 transactions, provided capabilities to Autonomy that couldn’t be referred to as legit.
When Autonomy was negotiating a sale to an end user, however couldn’t close the sale by using quarter’s end, Egan would approach the resellers on or near the closing day of the quarter, saying the deal changed into nearly done. Egan coaxed the resellers to purchase Autonomy application by paying them hefty commissions. The resellers could then sell the application to a targeted conclusion consumer – however Autonomy maintained manage of the offers and handled negotiations with the conclusion user devoid of the resellers’ help. There’s no method these transactions may be income.
Autonomy retained hazards, rewards and possession of the goods – now not the resellers, and not the end users. Autonomy was nevertheless exercising carrying on with involvement to an abnormal degree for a real switch of ownership to turn up. And the benefits of the offers didn’t accrue to Autonomy unless they were sold to an conclusion person. These transactions “grew” Autonomy’s revenues through as plenty as 15% in some periods. They had been crucial: they enabled the firm to report monetary consequences inside the boundaries of analyst expectations.
Between 2009 and 2011, after a quarter’s shut, Autonomy’s most senior finance executive directed Egan to obtain backdated buy orders from resellers; once, the executive obtained the soiled documentation for my part. This resulted in profits “pulled” from a later quarter into the one just closed – on occasion just sufficient salary to let Autonomy hit its income goal. In anyone’s publication, backdating buy orders is a falsification of statistics. seen via an IFRS accounting lens, these transactions couldn’t be called revenues as a result of Autonomy didn’t transfer the risk and rewards of utility possession to the buyer, at quarter conclusion. That happened in a later quarter.
Autonomy necessary to get cash to the resellers in order that they could pay Autonomy for the sham income, making a paper path for the auditors demonstrating payments on the revenue – a quintessential optic, to stay away from arousing their suspicions. The illusion became created with round-trip reseller transactions. Autonomy purchased a variety of surplus items from the resellers, with practically simultaneous charge via the reseller again to Autonomy on debt owed to them. The circular-travel transactions had been improvised with the aid of Autonomy’s senior-most finance executive, and that they amounted to at the least $45 million of phony paybacks to Autonomy.
On the orders of essentially the most senior financial govt, Egan was concerned in some round-go back and forth transactions: he served because the conduit between Autonomy and the resellers, and knew, or should have typical, that they didn’t symbolize actual purchases via Autonomy. He knew Autonomy didn't fee the charge of such purchases with different carriers of the same items; he didn’t negotiate agreement phrases.What to make of these facts?
There’s more than one way to skin a cat
regularly, probably the most senior economic executive of Autonomy developed most of the illicit transactions; and being out the country, was now not at once in the SEC’s attain. Egan become greater of a pawn than a mastermind, and performed his boss’s plans – inner the U.S., where at the least one considerable investor relied on the doctored financial statements. Egan turned into reachable by using the SEC, and he offered them with suggestions in ferreting out the falsifications.
Would the sham transactions have been uncovered devoid of HP purchasing Autonomy – and devoid of Egan’s assistance? It likely wouldn’t had been uncovered. the unreal transactions have been designed to appear true and throw suspicious events off the trail. Backdated files don’t seem different from ones that aren’t backdated; the money paid from the circular-shuttle transactions became arranged to make dummy receivables seem to be real. that could probably satisfy auditors, if their suspicions had been unaroused in any other case.
should the Autonomy auditors have caught the false transactions? maybe. Had they investigated the reseller transactions to see if the preliminary earnings to resellers resulted in sales to conclusion users – not all of them did, remember – they could have probed extra. there were most effective 30 such transactions over a ten-quarter duration: the auditors would had been really fortunate to discover transactions that piqued their curiosity out of such a small population and over such a very long time body. If peculiar transactions all the time confirmed within the last few days main as much as the quarter end, besides the fact that children, they should still have seen – and dug further.
This befell below IFRS guidelines. might it have took place below GAAP? little doubt. The difficulty right here isn’t with the necessities: the issue is the intent of the avid gamers involved.
Accounting requirements can’t keep away from the advent of false files or backdated purchase orders. No set of rules, now not even the brand new profits focus average, can keep away from mischief with the aid of managers anticipated to play via the suggestions.
Jack T. Ciesielski is president of R.G. friends, Inc., an asset administration and analysis enterprise in Baltimore that publishes The Analyst’s Accounting Observer, a research carrier for institutional buyers. Neither Hewlett Packard nor Autonomy are valued clientele of R.G. pals Inc.
starting in 2008, Jeff Hammerbacher (@hackingdata) and that i sat right down to share our experiences building the information and analytics groups at fb and LinkedIn. in many techniques, that meeting changed into the delivery of facts science as a distinct professional specialization (see the“What makes an information scientist” part of this record for the story on how we got here up with the title “information Scientist”). due to the fact that then, records science has taken on a life of its personal. The vastly superb response to “what is statistics Science?,” a superb introduction to the that means of facts science in these days’s world, showed that we have been at first of a circulation. There are now common meetups, smartly-based startups, and even school curricula focusing on statistics science. As McKinsey’s large facts research record and LinkedIn’s statistics suggests, statistics science ability is in high demand.
This enhance within the demand for statistics scientists has been driven by the success of the main information superhighway corporations. Google, facebook, LinkedIn, and Amazon have all made their marks through the use of data creatively: no longer just warehousing records, but turning it into whatever of price. even if that price is a search outcome, a focused advertisement, or a list of feasible neighbors, statistics science is producing items that individuals need and cost. And it’s no longer simply web companies: Walmart doesn’t produce “facts products” as such, but they’re neatly wide-spread for using facts to optimize every element of their retail operations.
Given how crucial statistics science has grown, it’s important to consider about what statistics scientists add to a company, how they slot in, and how to rent and build constructive facts science teams.
Courtesy LinkedIn Corp.Being statistics pushed
everyone wants to build an information-pushed company. It’s a well-liked phrase and there are lots of books, journals, and technical blogs on the topic. however what does it truly suggest to be “facts pushed”? My definition is:
a knowledge-driven firm acquires, techniques, and leverages statistics in a well timed fashion to create efficiencies, iterate on and improve new items, and navigate the competitive panorama.
there are lots of methods to investigate whether a company is records driven. Some want to discuss how plenty records they generate. Others want to speak about the sophistication of facts they use, or the process of internalizing records. I prefer to delivery with the aid of highlighting agencies that use data without problems.
Ecommerce agencies have a long background of using facts to benefit their agencies. Any good salesman instinctively knows the way to suggest additional purchases to a client. With “americans who viewed this merchandise also considered …,” Amazon moved this approach on-line. This simple implementation of collaborative filtering is one in all their most used elements; it is a powerful mechanism for serendipity outdoor of common search. This feature has turn into so regularly occurring that there at the moment are editions corresponding to “americans who considered this item bought … .” If a consumer isn’t quite convinced with the product he’s , suggest whatever equivalent that might possibly be extra to his style. The price to a grasp retailer is evident: close the deal if in any respect possible, and as a substitute of a single purchase, get consumers to make two or extra purchases via suggesting issues they’re more likely to want. Amazon revolutionized electronic commerce through bringing these options online.
statistics items are at the coronary heart of social networks. in any case, what is a social network if not an important dataset of users with connections to every other, forming a graph? perhaps the most critical product for a social network is whatever thing to support users connect with others. Any new user needs to discover chums, neighbors, or contacts. It’s now not a great person experience to drive clients to look for his or her pals, which is commonly a surprisingly elaborate assignment. At LinkedIn, we invented people You might also comprehend (PYMK) to solve this problem. It’s handy for software to predict that if James is aware of Mary, and Mary is aware of John Smith, then James may additionally comprehend John Smith. (neatly, conceptually easy. finding connections in graphs gets tough instantly because the endpoints get farther aside. but fixing that difficulty is what information scientists are for.) however think about searching for John Smith via identify on a network with a whole bunch of millions of clients!
however PYMK was novel at the time, it has become a vital part of every social community’s offering. facebook no longer most effective helps its own version of PYMK, they display screen the time it takes for users to purchase pals. the use of subtle monitoring and evaluation technologies, they have recognized the time and number of connections it takes to get a consumer to long-time period engagement. in case you join with just a few pals, or add chums slowly, you received’t stick around for lengthy. by way of discovering the pastime degrees that cause dedication, they have got designed the site to decrease the time it takes for brand spanking new users to connect with the essential variety of pals.
Netflix does anything similar in their on-line movie enterprise. when you sign up, they strongly inspire you to add to the queue of motion pictures you plan to watch. Their data team has discovered that when you add more than than a certain variety of motion pictures, the chance you will be an extended-time period client is significantly bigger. With this facts, Netflix can assemble, examine, and monitor product flows to maximise the number of new users who exceed the magic number and develop into long-time period valued clientele. They’ve developed a tremendously optimized registration/trial provider that leverages this advice to engage the user directly and effectively.
Netflix, LinkedIn, and fb aren’t alone in the use of consumer statistics to motivate lengthy-term engagement — Zynga isn’t nearly games. Zynga invariably displays who their users are and what they are doing, producing a fantastic quantity of facts in the method. by using inspecting how individuals engage with a video game over time, they've recognized tipping elements that result in a a hit video game. They know how the likelihood that users will develop into long-time period alterations in response to the variety of interactions they have with others, the number of structures they construct within the first n days, the variety of mobsters they kill within the first m hours, and many others. they have got discovered the keys to the engagement challenge and have developed their product to motivate users to reach these dreams. via continued checking out and monitoring, they sophisticated their realizing of those key metrics.
Google and Amazon pioneered the use of A/B trying out to optimize the layout of a web web page. For tons of the internet’s historical past, internet designers labored by means of instinct and intuition. There’s nothing wrong with that, but when you're making a transformation to a page, you owe it to your self to make certain that the trade is constructive. Do you sell extra product? How lengthy does it take for clients to discover the influence they’re looking for? how many users surrender and go to a different website? These questions can only be answered by means of experimenting, amassing the facts, and doing the analysis, all of which might be second nature to an information-driven business.
Yahoo has made many critical contributions to data science. After observing Google’s use of MapReduce to investigate massive datasets, they realized that they crucial similar equipment for their personal company. The outcomes become Hadoop, now probably the most essential tools in any facts scientist’s repertoire. Hadoop has due to the fact been commercialized by using Cloudera, Hortonworks (a Yahoo spin-off), MapR, and several different groups. Yahoo didn’t cease with Hadoop; they've observed the magnitude of streaming statistics, an software that Hadoop doesn’t handle smartly, and are engaged on an open supply device called S4 (nonetheless within the early tiers) to address streams readily.
fee services, equivalent to PayPal, Visa, American specific, and rectangular, are living and die by means of their competencies to dwell one step forward of the unhealthy guys. To do so, they use subtle fraud detection systems to seek irregular patterns in incoming facts. These techniques need to be able to react in milliseconds, and their fashions deserve to be updated in real time as extra records turns into attainable. It amounts to attempting to find a needle in a haystack whereas the employees retain piling on extra hay. We’ll go into greater particulars about fraud and safety later listed here.
Google and different serps at all times monitor search relevance metrics to establish areas the place individuals are trying to game the system or the place tuning is required to give a more robust person event. The challenge of moving and processing statistics on Google’s scale is significant, possibly better than another business nowadays. To support this challenge, they've needed to invent novel technical options that range from hardware (e.g., custom computer systems) to utility (e.g., MapReduce) to algorithms (PageRank), an awful lot of which has now percolated into open source application tasks.
I’ve discovered that the strongest facts-pushed businesses all are living by way of the motto “in case you can’t measure it, that you may’t fix it” (a motto I learned from some of the top-quality operations people I’ve worked with). This mind-set offers you a good looking capacity to deliver price to your enterprise by means of:
It’s convenient to fake that you simply’re facts pushed. but if you get into the approach to compile and measure everything which you could, and think about what the facts you’ve amassed capability, you’ll be forward of many of the businesses that claim to be information pushed. And while I actually have plenty to say about knowledgeable data scientists later in this submit, bear in mind that facts isn’t just for the authorities. each person may still be looking at the facts.The roles of an information scientist
In each firm I’ve labored with or recommended, I’ve always discovered that statistics scientists have an affect out of percentage to their numbers. the many roles that information scientists can play fall into here domains.decision sciences and company intelligence
facts has long played a role in advising and assisting operational and strategic pondering. One crucial element of resolution-making support is defining, monitoring, and reporting on key metrics. whereas that might also sound easy, there's a true art to defining metrics that assist a enterprise more advantageous be aware its “levers and control knobs.” Poorly-chosen metrics can result in blind spots. furthermore, metrics must always be utilized in context with every different. for instance, when looking at percentages, it continues to be crucial to peer the uncooked numbers. it's also primary that metrics evolve as the sophistication of the business raises. As an analogy, imagine a meteorologist who can most effective measure temperature. This adult’s forecast is all the time going to be of lower great than the meteorologist who is aware of the way to measure air drive. And the meteorologist who knows a way to use humidity will do even more suitable, etc.
as soon as metrics and reporting are established, the dissemination of data is elementary. There’s a wide array of equipment for publishing information, starting from simple spreadsheets and web types, to greater refined business intelligence items. As equipment get extra sophisticated, they customarily add the capability to annotate and manipulate (e.g., pivot with different facts facets) to provide extra insights.
extra sophisticated statistics-pushed organizations thrive on the “democratization” of information. records isn’t simply the property of an analytics neighborhood or senior administration. everybody should have entry to as a great deal information as legally feasible. fb has been a pioneer in this enviornment. They permit any individual to question the enterprise’s massive Hadoop-based facts save the usage of a language known as Hive. this way, just about any one can create a personal dashboard by using operating scripts at regular intervals. Zynga has constructed whatever equivalent, the usage of a completely diverse set of applied sciences. they have two copies of their statistics warehouses. One copy is used for operations the place there are strict service-degree agreements (SLA) in location to make sure stories and key metrics are at all times attainable. The different data shop can be accessed via many americans in the business, with the knowing that efficiency might also now not be at all times optimum. A more typical model is used by means of eBay, which makes use of applied sciences like Teradata to create cubes of statistics for each team. These cubes act like self-contained datasets and information retailers that the teams can have interaction with.
As groups have turn into more and more adept with reporting and analysis, there has been increased demand for strategic choice-making the use of records. we now have been calling this new area “resolution sciences.” These groups delve into current facts sources and meld them with exterior statistics sources to remember the aggressive landscape, prioritize strategy and strategies, and supply readability about hypotheses that may additionally arise right through strategic planning. a call sciences team might tackle a problem, like which country to expand into subsequent, or it could investigate no matter if a selected market is saturated. This evaluation may, as an example, require mixing census information with inner records after which building predictive fashions that may also be tested against present data or facts that needs to be got.
One note of caution: individuals new to records science often seek a “silver bullet,” some magic number round which they can build their whole equipment. in case you find it, superb, however few are so lucky. The most beneficial agencies search for levers that they could lean on to maximise utility, after which move on to find extra levers that boost the cost of their company.What makes a data scientist?
When Jeff Hammerbacher and i talked about our information science groups, we realized that as our corporations grew, we both had to determine what to call the people on our teams. “company analyst” appeared too limiting. “facts analyst” changed into a contender, however we felt that title could limit what people might do. after all, many of the people on our teams had deep engineering potential. “analysis scientist” was a reasonable job title used via businesses like solar, HP, Xerox, Yahoo, and IBM. despite the fact, we felt that most analysis scientists labored on initiatives that have been futuristic and summary, and the work changed into accomplished in labs that had been isolated from the product development teams. It might take years for lab research to have an effect on key products, if it ever did. as a substitute, the center of attention of our groups changed into to work on statistics functions that might have an immediate and massive impact on the company. The term that gave the impression to fit most appropriate changed into records scientist: those who use each statistics and science to create some thing new.
(word: besides the fact that children the term “information science” has a protracted background — continually relating to enterprise intelligence — “statistics scientist” looks to be new. Jeff and that i had been asking if anybody else has used this term before we coined it, however we’ve yet to find any one who has.)
however how do you discover information scientists? every time somebody asks that question, I refer them back to a extra fundamental query: what makes a superb information scientist? here's what I look for:
individuals frequently count on that data scientists want a heritage in computer science. In my experience, that hasn’t been the case: my gold standard information scientists have come from very distinctive backgrounds. The inventor of LinkedIn’s people You can also comprehend changed into an experimental physicist. A computational chemist on my choice sciences crew had solved a a hundred-yr-historical difficulty on power states of water. An oceanographer made important influences on the style we identify fraud. possibly most surprising became the neurosurgeon who grew to become out to be a wizard at settling on wealthy underlying tendencies in the information.
the entire top statistics scientists share an innate sense of curiosity. Their curiosity is vast, and extends well beyond their everyday actions. They are interested in figuring out various areas of the company, company, industry, and expertise. as a result, they are often capable of bring disparate areas collectively in a novel way. as an instance, I’ve considered records scientists study earnings approaches and know that by using records in new approaches they can make the revenue team far more effective. I’ve seen information scientists practice novel DNA sequencing innovations to locate patterns of fraud.
What unifies all these people? all of them have amazing technical backgrounds. Most have superior levels (besides the fact that children I’ve labored with several incredible records scientists who haven’t graduated from college). however the true unifying thread is that each one have had to work with a big volume of facts before starting to work on the “true” problem. When i used to be a first-yr graduate pupil, i was interested in climate forecasting. I had an idea about how to take into account the complexity of climate, but needed loads of statistics. most of the records become accessible on-line, however because of its measurement, the statistics was in particular codecs and spread out over many different methods. To make that statistics effective for my research, I created a gadget that took over every desktop in the branch from 1 AM to 8 AM. right through that time, it acquired, cleaned, and processed that records. as soon as achieved, my last dataset may conveniently fit in a single laptop’s RAM. And that’s the complete aspect. The heavy lifting changed into required before I might birth my research. respectable statistics scientists understand, in a deep approach, that the heavy lifting of cleanup and education isn’t whatever that receives in the means of solving the issue: it's the problem.
These are some examples of coaching that hone the capabilities a knowledge scientist has to be a success:
one of the vital challenges of determining facts scientists is that there aren’t a lot of them (yet). There are a number of courses that are assisting train individuals, however the demand outstrips the provide. And experiences like my very own suggest that the most reliable strategy to turn into a data scientist isn’t to be knowledgeable as a data scientist, however to do serious, facts-intensive work in another discipline.
Hiring information scientists changed into one of these problem at each area I’ve worked that I’ve adopted two fashions for building and training new hires. First, employ americans with diverse backgrounds who've histories of twiddling with statistics to create whatever thing novel. 2nd, take tremendously vivid and creative americans right out of faculty and put them via a extremely robust internship application.
one more method to locate first rate facts scientists is to run a contest, like Netflix did. The Netflix Prize become a contest organized to improve their skill to predict how plenty a customer would delight in a movie. if you don’t wish to arrange your personal competitors, that you could study people who've carried out smartly in competitions run via others. Kaggle and Topcoder are great materials when attempting to find this form of talent. Kaggle has discovered its own correct skill by using hiring the most desirable performers from its personal competitions.Hiring and skill
Many people focus on hiring fantastic facts scientists, but they leave out the want for continued highbrow and profession increase. These key facets of growth are what I name skill boom. within the three years that I led LinkedIn’s analytics and records teams, we developed a philosophy around three principles for hiring and talent boom.
Would we be willing to do a startup with you?
here's the primary query we ask ourselves as a crew when we meet to consider a candidate. It sums up a number of key standards:
can you “knock the socks off” of the enterprise in ninety days?
once the primary criteria has been met, it’s crucial to establish mechanisms to make certain that the candidate will succeed. We do that by using atmosphere expectations for the great of the candidate’s work, and through atmosphere expectations for the velocity of his or her progress.
First, the “knock the socks off” half: by surroundings the purpose high, we’re asking whether you have got the mettle to be a part of an elite team. greater importantly, it's a way of building a handshake for making certain success. That’s the place the ninety days comes in. a new employ received’t get a hold of whatever thing mind blowing if the group doesn’t deliver the brand new employ up to speed instantly. The group should orient new hires around present systems and techniques. similarly, the brand new rent should make the effort to progress, promptly. Does this person ask questions when they get stuck? There are no dumb questions, and toughing it out because you’re too proud or insecure to ask is counterproductive. Can the brand new rent carry a brand new system up in a day, or does it take every week or extra? It’s essential to keep in mind that doing something surprising in 90 days is a team intention, as tons as a person aim. it's elementary to pair the brand new rent with a successful member of the team. Success is shared.
This criterion sets new hires up for long-term success. as soon as they’ve handed the primary milestone, they’ve performed whatever thing that others in the company can admire, and that they have the self belief in an effort to result in future achievements. I’ve viewed everybody from interns all the option to seasoned executives meet this criterion. and a lot of of my right individuals have had varied successes of their first 90 days.
In four to six years, will you be doing whatever thing spectacular?
What does it mean to do something spectacular? You could be working the team or the business. You may be doing whatever thing in a totally diverse discipline. You may additionally have started a new enterprise that’s changing the business. It’s complicated to talk concretely as a result of we’re speaking about abilities and long-term futures. however we all want success to breed success, and i agree with we can appreciate the individuals who will support us to develop into collectively a success.
I don’t always predict a brand new hire to do whatever thing remarkable while he or she works for me. The four- to six-yr horizon permits members of the team to construct lengthy-time period street maps. Many companies make the time dedication amorphous with the aid of talking about vague, not ever-ending career ladders. but experts no longer commit themselves to a single company for the majority of their careers. With each and every new era of professionals, the variety of corporations and even careers has increased. So in preference to combat it, embrace the fact that people will leave, so long as they depart to do something wonderful. What I’m attracted to is the knowledge: in case you have that competencies, all of us win and we all develop together, whether your largest successes include my crew or somewhere else.
at last, this standards is mutual. a new employ gained’t do whatever astounding, now or in the future, if the corporation he or she works for doesn’t grasp up its conclusion of the discount. The organization need to provide a platform and opportunities for the particular person to be a success. Throwing a new rent into the deep end and expecting success doesn’t reduce it. in a similar fashion, the particular person need to make the company successful to increase the platform that she or he will launch from.building the LinkedIn records science team
I’m happy with what we’ve completed in constructing the LinkedIn data group. youngsters, when we begun, it didn’t seem to be anything else like the firm this is there nowadays. We all started with 1.5 engineers (who would later go on to invent Voldemort, Kafka, and the real-time recommendation engine techniques), no information services team (there wasn’t even a data warehouse), and five analysts (who would later become the core of LinkedIn’s statistics science neighborhood) who supported everyone from the CFO to the product managers.
when we began to build the group, the first element I did changed into go to many different technical businesses (the likes of Yahoo, eBay, Google, facebook, solar, and many others.) to get their thoughts and opinions. What I discovered in fact stunned me. The companies all had mind-blowing sets of personnel who may well be considered “information scientists.” however, they had been uniformly discouraged. They did first-expense work that they considered important, however that had very little have an effect on on the organization. They’d finish some evaluation or come up with some ideas, and the product managers would say “that’s first-rate, but it’s now not on our roadmap.” subsequently, the information scientists developing these ideas were frustrated, and their organizations had concern capitalizing on what they were in a position to doing.
Our solution was to make the records group a full product team responsible for designing, imposing, and retaining products. As a product team, information scientists might experiment, build, and add price at once to the company. This resulted now not handiest in additional building of LinkedIn products like PYMK and Who’s viewed My Profile, but also in aspects like knowledge, which tracks quite a few abilities and assembles an image of what’s mandatory to be successful in any given area, and career Explorer, which helps you explore distinct profession trajectories.
It’s essential that our information team wasn’t comprised completely of mathematicians and other “information people.” It’s a completely integrated product community that contains americans working in design, net development, engineering, product advertising, and operations. all of them bear in mind and work with facts, and i consider all of them statistics scientists. We intentionally kept the difference between distinctive roles in the neighborhood blurry. frequently, an engineer can have the perception that makes it clear how the product’s design may still work, or vice-versa — a clothier can have the insight that helps the engineers remember how to stronger use the information. Or it will probably take someone from advertising to understand what a customer truly desires to accomplish.
The silos that have traditionally separated facts individuals from engineering, from design, and from marketing, don’t work in the event you’re constructing data items. i might contend that it is questionable even if these silos work for any kind of product construction. however with information, it in no way works to have a waterfall method during which one community defines the product, an additional builds visual mock-ups, a data scientist preps the facts, and finally a set of engineers builds it to a few specification doc. We’re no longer building Microsoft office, or some other product the place there’s 20-plus years of shared knowledge about how interfaces should still work. each information challenge is a brand new scan, and design is a critical a part of that test. It’s equivalent for operations: statistics items present wholly distinctive stresses on a community and storage infrastructure than common sites. They trap a great deal greater information: petabytes and even exabytes. They carry results that mash up facts from many sources, some interior, some now not. You’re not going to create an information product this is respectable and that performs fairly well if the product group doesn’t contain operations from the birth. This isn’t an easy be counted of pushing the prototype out of your computer to a server farm.
at last, great assurance (QA) of statistics items requires a radically distinctive strategy. building test datasets is nontrivial, and it is usually impossible to verify all the use cases. As distinctive data streams come collectively into a last product, all types of relevance and precision concerns become apparent. To increase this kind of product easily, the means to adapt and iterate right now all over the product existence cycle is simple. To ensure agility, we build small businesses to work on specific items, initiatives, or analyses. When we will, i like to seat any person with a dependency with one more adult in the identical area.
an information science group isn’t just individuals: it’s tooling, approaches, the interaction between the team and the leisure of the company, and greater. At LinkedIn, we couldn’t have succeeded if it weren’t for the equipment we used. should you’re working with petabytes of information, you want serious energy tools to do the heavy lifting. Some, akin to Kafka and Voldemort (now open source initiatives) had been homegrown, not as a result of we concept we should still have our personal technology, however as a result of we didn’t have a decision. Our items couldn’t scale with out them. moreover these technologies, we use different open source technologies equivalent to Hadoop and a lot of dealer-supported solutions as well. lots of these are for facts warehousing, and standard company intelligence.
tools are essential because they will let you automate. Automation frees up time, and makes it possible to do the inventive work that ends up in superb products. whatever thing as simple as reducing the turnaround time on a fancy query from “get the outcomes within the morning” to “get the outcomes after a cup of espresso” represents an important boost in productiveness. If queries run in a single day, you could simplest have the funds for to ask questions should you already consider you comprehend the answer. If queries run in minutes, you could scan and be inventive.
interplay between the facts science teams and the leisure of corporate subculture is an additional key component. It’s effortless for a knowledge group (any team, in fact) to be bombarded via questions and requests. however no longer all requests are equally vital. How do you make sure there’s time to feel in regards to the big questions and the huge problems? How do you balance incoming requests (most of that are tagged “as soon as possible”) with lengthy-time period dreams and initiatives? It’s critical to have a tradition of prioritization: everyone within the group must be in a position to ask in regards to the precedence of incoming requests. everything can’t be urgent.
The outcomes of constructing a knowledge group is, sarcastically, that you see statistics items being in-built all constituents of the business. When the company sees what can also be created with statistics, when it sees the power of being records enabled, you’ll see data products acting all over the place. That’s how you recognize in the event you’ve gained.Reinvention
organizations are all the time seeking to reinvent themselves. There’s under no circumstances been a higher time: from economic pressures that demand superior effectivity, to new forms of products that weren’t conceivable a couple of years ago, the alternatives offered by using records are giant.
however’s a mistake to treat statistics science groups like every old product community. (it's probably a mistake to treat any old product neighborhood like several ancient product community, however that’s an extra difficulty.) To construct teams that create notable facts products, you must locate people with the abilities and the curiosity to ask the large questions. you have build move-disciplinary agencies with people who're at ease creating collectively, who have faith each other, and who are inclined to aid each and every different be spectacular. It’s not convenient, but if it were easy, it wouldn’t be as a great deal fun.
DJ discusses records-driven corporations and the empowerment of records science groups in here interview:
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In an effort to enable other high growth companies to embrace and realize the potential of Selling Through Curiosity™, SalesHood is hosting a much sought after in-person Selling Through Curiosity Workshop with Barry Rhein in San FranciscoOct 9-11, 2018: https://saleshood.com/events/sales-training-workshop-2018/
"It's no secret, companies are wasting billions of dollars every year on sales training that's costly, ineffective and inefficient. 95% of what is trained in a workshop is forgotten because of poor reinforcement, certification and best practice sharing," says Elay Cohen CEO of SalesHood and former SVP Sales Productivity at Salesforce.
Selling Through Curiosity™ delivers revenue results in days and weeks versus months and years by leveraging the SalesHood platform to deliver just-in-time collaborative coaching huddles, content rich best practice videos, deal coaching exercises, peer to peer collaboration and certifications. High growth companies such as RingCentral, Yext, Sage Intacct, United Way, Bluewolf, Bloom Energy and many more have embraced Selling Through Curiosity to accelerate growth and dramatically outperform their peers. Some customer quotes of the effectiveness of the program.
"Selling Through Curiosity is one of these sales training programs that only comes around once a millennium. It gets our salespeople into a much more powerful conversation with their client. Part of our incredible success reflects the usability and success of SalesHood and Selling Through Curiosity" Sheevaun Thatcher, Head of Global Enablement at RingCentral
This next generation sales training is delivered on-demand exclusively in the SalesHood platform by front-line managers or trainers to quickly increase win-rates and increase rep quota attainment. Through video and social reinforcement on web and mobile, salespeople have a personal sales coach and team of mentors supporting them all the time, wherever they go.
Praised by tens of thousands of sales professionals, Selling Through Curiosity™ is credited for producing billions of dollars of revenue and shareholder value. The program includes: discovery, effective note taking, qualification, decision making process, advanced questioning, creating custom presentations, mutual plans, closing, objection handling, negotiating, prospecting, and advanced relationship building.
"Transforming a sales organization to obtain short-term and long-term measurable selling results is a complicated process. It's why the majority of sales training programs fail. SalesHood provides the ongoing practice that is missing in all other sales training programs. It's why our customers see immediate and long-term measurable results. I'm excited to partner with SalesHood to offer Selling Through Curiosity™ to every company, team and salesperson on the planet," says Barry Rhein.
About Barry Rhein & AssociatesFor more than 30+ years, Barry Rhein & Associates is the most sought after sales consulting organization in Silicon Valley. The highly acclaimed Selling Through Curiosity™ program is praised in delivering immediate and measurable sales results, accomplishing in days what would normally take years. Barry Rhein's curiosity-based methodology is widely appreciated for moving far beyond theory and into simple, practical steps that immediately impact attitudes, skills, effectiveness, and earnings of the participants.
About SalesHoodSalesHood is a leading enablement platform created to help teams improve sales productivity and revenue results. We help teams learn and share best practices in a modern way through video storytelling and social learning. Engagement is high and proven to impact outcomes. Revenue results are fast. SalesHood's customers are doubling win rates, exceeding quota attainment, and improving time to ramp. Join the SalesHood Community today. For more information about SalesHood and a free trial, visit us at https://saleshood.com
More resources:Learn More about why curiosity matters: https://saleshood.com/blog/always-be-curious-with-sales-training-on-demand-by-barry-rhein/To register fo the Selling Through Curiosity Workshop Oct 9-11, 2018: https://saleshood.com/events/sales-training-workshop-2018/To see Selling Through Curiosity in action On Demand, visit us at https://www.saleshood.com/selling-through-curiosity/.See video of Sheevaun Thatcher at RingCentral describing the value: https://youtu.be/uwxASvLnC34
Southwest Airlines CEO Gary Kelly piqued investor curiosity recently when he said new ways to generate revenue are "under construction.''
The discounter barely has a toe in the big pool of money that rivals collect from so-called ancillary fees for, say, food bought on board or preferred seating. And Kelly has ruled out some of the juiciest mainstays at other airlines, such as charges for checked bags, assigned seats and reservation changes.
"That's not what we do," he said on an earnings call. Southwest has "better opportunities that fit our brand.''
Kelly won't go into specifics just yet, and Southwest declined to provide additional comment. That's fueling a guessing game on Wall Street about what he has up his sleeve to boost revenue as Southwest grapples with an increase in costs. Here are three likely options:
More perks: While Southwest flies just coach cabins and has no assigned seats, it does have several fare categories, including Business Select, which comes with a free drink, a spot among the first 15 passengers to board and expedited security screening in some locations.
Southwest could provide additional perks at higher prices, said Adam Hackel, an Imperial Capital analyst. A passenger might pay extra to gain access to priority screening, for example, or to get her bag in the first wave off the luggage carousel. The extras could be sold separately, like Southwest's Early Bird boarding option, or built into fare categories along the lines of Business Select.
The Dallas-based airline spent $500 million to replace its 30-year-old reservation system in 2017, in part to build new revenue options like those. The updated platform also made it easier for Southwest to change fares, seat inventories and flight schedules.
Forward seating: Southwest could also take Business Select a step further — think business-class lite. The carrier always has dismissed the idea of offering a first- or business-class cabin, so isn't expected to add seats with more legroom for a higher fare.
It could, however, charge more for guaranteed access to as many as four rows near the front of the plane, said Jamie Baker, an analyst at JPMorgan Chase.
Those 24 seats might appeal to business travelers who would avoid standing in boarding lines yet be assured a spot toward the front of the plane, with last-on/first-off benefits and dedicated bin space. Such a system could add from 10 cents to $1 a share in annual earnings, depending on the pricing, Baker said in a report.
"The concept checks four important boxes: ease of execution, ease of passenger understanding, profits, and the broader preservation of the existing Southwest experience," he wrote.
Up-selling opportunities: Instead of — or in addition to — adding perks on the high end, Southwest could reduce benefits in cheaper fare categories. One possibility, for example, would be not allowing a passenger who cancels a ticket to use the amount paid toward another flight.
This plan would take a page from the many rivals who offer basic-economy fares. Those bare-bones tickets often entice travelers to buy more-expensive options. While Southwest has said basic economy per se is off the table, a few changes could have the same up-selling effect.Seller beware
Ancillary fees accounted for just 3.1 percent of Southwest's passenger revenue through the first nine months of last year, lagging well behind Delta Air Lines and United Airlines. U.S. carriers as a whole took in more than $3.6 billion in checked-bag fees alone during the period, according to the U.S. Transportation Department.
When it comes to industry competition, executives at Delta Air Lines have never been accused of jabbing with soft elbows. That ferocity was on full display Thursday as the carrier launched its first Airbus A220 flights from Boston, Dallas and New York, deploying the technologically advanced aircraft...
Southwest will have to tread carefully, though, to avoid damaging the brand it has cultivated for transparency in fares and not peppering passengers with a slew of fees.
"As long as Southwest offers these as add-ons and the consumer sees they are appealing, and Southwest doesn't take anything from its core value proposition, they have a reasonable chance of success," said Henry Harteveldt, founder of Atmosphere Research Group, which focuses on the travel industry.
Southwest's intention to find new revenue sources makes sense, he said. "It's been timid and allowed itself to be held hostage by its legacy, as opposed to being innovative and saying, 'We can keep our legacy and still innovate and add products that would appeal to customers.'"
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It may still be winter in many parts of the country, but MLB spring training is almost here, and Fantasy baseball owners everywhere are starting to prepare for their upcoming drafts. Whether you're playing in a redraft, keeper or dynasty league, there's value in finding that next big prospect. Who should you target? Who should you fade? And what hidden gem is the key to victory in Fantasy baseball this season? The key to finding the best prospects is using a reliable set of Fantasy baseball dynasty rankings. SportsLine's resident Fantasy baseball expert, Scott White, has sifted through scouting reports across the entire MLB farm system to identify the best 2019 Fantasy baseball prospects at every position, including second base. You should take a look before preparing for your Fantasy baseball draft.
White has spent over a decade as CBS Sports' Fantasy Baseball analyst and has been named the FSWA Baseball Writer of the Year. He was the 2017 runner-up in the famous Tout Wars league -- the most prestigious league for Fantasy Baseball experts from around the country.
Now he has studied the upcoming crop of prospects and has identified the top 10 Fantasy Baseball second basemen you need to know about heading into the 2019 MLB season. We'll give away three second base Fantasy baseball prospects with White's analysis for each.
Vidal Brujan, Rays
Brujan is more of the long-term bet, and an exciting one at that, combining an exceptional batting eye with transcendent speed. The switch-hitter might just develop power, too, judging by his numbers from the left side of the plate and the fact four of his homers came after his August promotion to high Class A.
Nick Senzel, Reds
Between a torn tendon in his finger, bone spurs in his elbow and another bout with vertigo, Senzel basically lost a year of development, but the good news is he's more or less developed already. The second pick of the 2016 draft is a natural with the bat and should arrive as soon as the Reds figure out where he best fits, looking to try him in the outfield after already shifting him from third base to second.
Cavan Biggio, Blue Jays
While Vladimir Guerrero and Bo Bichette were already established as prospects, Biggio entered 2018 as more of a curiosity, yet another son of a big-league star on the same Double-A New Hampshire team. By lowering his hands to add more loft to his swing, he emerged as a prospect in his own right, selling out for power in a way that confines his batting average but making up for it with a patient approach.
White is revealing the rest of top 10 over at SportsLine, and it includes a young second baseman whose career "closely parallels Jose Altuve's." This is a prospect who could pay dividends for Fantasy Baseball players for years to come.
Who are the top 10 second base prospects that Fantasy Baseball players need to know about? And which rookie is on the fast track for success? Visit SportsLine to see Scott White's complete breakdown of the 10 best second base prospects, all from an-award winning Fantasy Baseball analyst who can give you a huge edge in your league.
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