BrachEichler LLC Blog Feed Mar 2018firmwise Bitcoin Pave A New Career Path For You? 13 Mar 2018Blog<p><span style="font-family: Verdana;"><span style="font-size: medium;">Being as close to the financial trading sector as we are at Roy Talman &amp; Associates, we can see that a number of financial trading companies are jumping on the bandwagon of trading cryptocurrencies. The core of expertise of trading companies is, of course, trading. For these companies, it's often much more profitable to trade something with high volatility than little volatility. Despite the fact that there are lots of stories about how 2017 was one of the least volatile market years on record, that simply doesn't apply to cryptocurrencies. </span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">Therefore, to the degree that cryptocurrencies will be used and traded by these trading firms, it represents an extremely appealing product to trade. Many trading companies in Chicago are already trading cryptocurrencies or gearing up very quickly to trade them. To fully achieve that, you need a whole infrastructure with real exchanges. Thus far, in my observation, we are still very early on in that lifecycle. The futures exchanges, CME and CBOE have not really gained much value in this area. </span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">Nonetheless, in the future, we should see a point where, to some degree, various public or private cryptocurrencies will become ever more useful. That could have very positive career implications for people with a strong understanding of that technology.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">The progression I&rsquo;m speaking of reminds me a bit of how the Internet first burst upon the scene in the mid-'90's. At that time, very few people knew how to write code for this wonderful new thing called the Internet. As such, there were also few applications that were truly useful. Still, as time went on, we reached a point to where we are today &ndash; we see tens of millions, perhaps even <i>hundreds of millions</i> of people know how to write code continually. The code is much easier to write and from that development, there are tremendous libraries of information being created that others can, in turn, use and learn from.</span></span></p> <p>&nbsp;</p> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><b>So Is Bitcoin And Blockchain Here To Stay?</b></span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">As new forms of funding have emerged worldwide, what we&rsquo;re seeing are a very large number of ICOs (initial coin offerings). For the time being, you may have some spectacular successes &ndash; such as Ripple, a company that people can use to send money using blockchain &ndash; as well as a fair number of failures. It should be very interesting to see a variety of applications for these ICOs and the blockchains that underline them. It appears at this point that the cryptocurrencies that will garner the largest use will not only survive but also prosper.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">___________________________________________________________________________________</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><i>Advertisement</i></span></span></p> <span style="font-family: Verdana;"><span style="font-size: medium;"> <p><b><u>Talman Advantage #2:</u></b></p> </span></span> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><b>We See The Complete Picture Of Who You Are</b></span></span></p> <span style="font-family: Verdana;"><span style="font-size: medium;"> <p><b><i>At Roy Talman &amp; Associates, we don&rsquo;t just see you as a resume or even a candidate to fill an open job. Instead, we&rsquo;ll ask to meet you because we want to get to know you on a deeper level &ndash; that includes your current skills, your knowledge of certain subjects, your special expertise, your work style and the environments in which you believe you thrive.</i></b></p> </span></span> <span style="font-family: Verdana;"><span style="font-size: medium;"> <p><b><i>Compare that to others. But always talk to Talman first.</i></b></p> </span></span> <p><span style="font-family: Verdana;"><span style="font-size: medium;">___________________________________________________________________________________</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">Ripple's CEO is fond of pointing out that his transactions can be processed in three seconds and due to that, he's getting a lot of use out of his system whereas bitcoin transactions currently can take hours. And as far as transaction fees, it&rsquo;s easy to see where that&rsquo;s going to become a big issue for bitcoin &ndash; people are paying an average near $30 in order to make bitcoin transactions. Considering that the original premise was that bitcoin transactions were going to be a fraction of a penny, it seems we've migrated the wrong way &ndash; but the demand certainly appears to be there.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">Still, there are so few people with an understanding of what these tools are and what they can do from a technological standpoint that it may very well open the door to new, exciting potential opportunities for candidates.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">Case in point: A recent graduate with six months of experience writing code for GitHub in between classes is a highly desirable expert on a global basis. It is not a stretch to say that such a candidate, in Dublin, could attract a company in Montreal to want to hire him to work for a manager in Chicago.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">We can foresee the same development likely happening over and over again. As with so many relatively new areas of technology, there can be a great deal of ups and downs. There will be high profile success stories and yes, some headlines about this or that promising company that ultimately went nowhere. So if you move your career toward a company related to cryptocurrency, be prepared to stomach what could be a high level of volatility. Some candidates thrive upon riding this kind of roller coaster. Others run from it as fast as they can.</span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><b>We&rsquo;ve Been Here Before. </b></span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><b>And Ready For What Comes Next.</b></span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">If you&rsquo;re expecting the media to tell a consistent &ldquo;straight story&rdquo; on the future of cryptocurrency, good luck with that. We&rsquo;ve seen wide-ranging predictions that run the gamut from a &ldquo;bitcoin bubble&rdquo; about to burst to how bitcoin is going replace all forms of money as we know it. </span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;">For our part, we see a future somewhere in the middle: Cryptocurrency will have its winners, its losers and doesn&rsquo;t seem to be on the verge of suddenly disappearing. </span></span></p> <p><span style="font-family: Verdana;"><span style="font-size: medium;"><b><i>It&rsquo;s actually a cycle that we&rsquo;ve seen several times over the last 30 years at Roy Talman &amp; Associates. An emerging technology arrives, disrupting industries and bringing new questions with it. When those questions influence what your next career move could be, a degree of clarity is much needed. That&rsquo;s where Roy Talman&rsquo;s deep knowledge of where technology is headed next and what firms value most can be highly beneficial, providing you with keen insight on the opportunities that best align with your skills and goals.&nbsp;</i></b></span></span></p> Next Phase Of AI: Beyond The “Hype” 08 Mar 2018Blog<p><span style="font-size: medium;"><b>The Next Phase Of AI: Beyond The &ldquo;Hype&rdquo;</b></span></p> <p><span style="font-size: medium;">I was recently watching two luminaries in the area of artificial intelligence talk about where AI is at this point. It wasn&rsquo;t really presented from the point of view that &ldquo;<i>one algorithm is better than another algorithm</i>,&quot; but rather more in terms of how someone in business can make sense out of this new machine age we&rsquo;re entering.</span></p> <p><span style="font-size: medium;">One of the more surprising points came from a speaker named Andrew Ng, a former chief scientist at Baidu who ran the company&rsquo;s Artificial Intelligence Group and is now an adjunct professor at Stanford and a chairman of Coursera. Ng stated that 99% of the commercial uses of machine learning today come from what we call <b>supervised learning</b>.</span></p> <p><span style="font-size: medium;">Supervised learning represents one of three types of machine learning systems today. It&rsquo;s when you have an event or object and a machine is not only told what that event or object is but then <i>also learns to recognize it.</i> You might say that autonomous driving or medical image recognition is a good example of supervised learning. Ng himself and a group of his students at Stanford built a system to recognize whether a head of lettuce was ripe or not &ndash; a project that all started with his students walking around with their cellphones, taking pictures of heads of lettuce and labeling them accordingly for the benefit of a machine&rsquo;s understanding.</span></p> <p><span style="font-size: medium;">&nbsp;</span></p> <p><span style="font-size: medium;">Next, we have <b>reinforced learning</b>, a type of machine learning that became most famous when systems were built that could learn, by themselves, how to play games - from Space Invaders to the game Go to Chess. In fact, the only thing these systems ever really need are the rules of the game. Once a system has such a foundation of rules, it can essentially take it from there.</span></p> <p><span style="font-size: medium;">Finally, there is what&rsquo;s referred to as <b>unsupervised learning</b>. An example of this type of machine learning might be Google &ldquo;learning&rdquo; to work through millions of photos on its own in order to recognize and identify a particular image such as a cat.</span></p> <p><span style="font-size: medium;">The positive sentiment about supervised learning and its phenomenal progress over the last 5-7 years was echoed in this same presentation by Yann LeCun, a computer scientist who is the head AI scientist in Facebook&rsquo;s research division. LeCun claims that the progress supervised learning has achieved, in substantial degree, comes from essentially two components: One is the <b>ever-faster GPUs in auto specialized chips</b> that are good at running neural nets and the billions upon billions of computations it takes to train those networks. The other is an <b>ever-increasing availability of data to train these systems on</b>.</span></p> <p><span style="font-size: medium;">&nbsp;</span></p> <p><span style="font-size: medium;"><b>The Promise Of Things To Come</b></span></p> <p><span style="font-size: medium;">Ng and LeCun may see that supervised learning is where a vast majority of commercial applications are today. Beyond today, however, there are many exciting evolutions of machine learning for tomorrow &ndash; these are not &ldquo;experiments&rdquo; (as some admittedly can be), but rather practical applications that can shake up a variety of industries.</span></p> <p><span style="font-size: medium;">Let&rsquo;s take medical imaging recognition, for example. The current technological state of affairs is such that a system essentially has to be taught, &ldquo;<i>This image depicts cancer</i>&rdquo; and &ldquo;<i>This is not cancer</i>.&rdquo; Over time, the system is able to identify from a given photo whether a lesion is cancerous or not.</span></p> <p><span style="font-size: medium;">Yet, the real promise from here is that a person with a reasonably priced smartphone will be able to take a picture, upload it to the cloud, get it analyzed and receive the results of that analysis for a nominal cost.</span></p> <p><span style="font-size: medium;">As this technology progresses and becomes more widely distributed, the next true stage of machine learning could go a long way toward improving healthcare for more people in the world.</span></p> <p><span style="font-size: medium;">Are we there yet? No. It can take significant time for one system to analyze a variety of narrow problems to understand or rules to follow before it can solve a problem, play a game or perform analysis. My personal suspicion is that it might take billions of <i>those</i> systems, in turn, to build a system that we consistently recognize for its usefulness through the world.</span></p> <p><span style="font-size: medium;">Optimistically speaking, we will probably get to that point&hellip;even if we&rsquo;re not quite there yet.</span></p> <p><span style="font-size: medium;">What you could say we are experiencing in machine learning is a new phase. We have been through the &ldquo;hype&rdquo; phase. We have also seen a system&rsquo;s ability to learn and demonstrate broadly applicable tasks. From here, we will likely be <b>entering a phase in which we have more sensors on a widespread basis</b> &ndash; and in turn, as we are able to collect a large amount of data on a cost-effective basis, we should see exponential growth in a variety of useful systems. In addition, as a result of that exponential growth in computational capacity, we should also see systems built with the next layer of capabilities.</span></p> <p><span style="font-size: medium;"><b>What Tech Skills Today Are Needed For Tomorrow&rsquo;s Systems?</b></span></p> <p><span style="font-size: medium;">In practical terms, it may surprise you to learn that my expectation is that the technology skills that should be called upon to &ldquo;help&rdquo; these types of systems will actually be good old-fashioned <b>software development skills in areas such as Java, Python and C++. </b>I foresee a variety of candidates needing a solid familiarity with how to manage a large amount of data, including how to identify specific data in relation to a specific subject.</span></p> <p><span style="font-size: medium;">Now, some may believe that learning certain company systems will take an enormous effort. There will be substantial effort required, to be sure. However, for all their complexities, an understanding of the developmental core algorithms behind these systems may be less of a challenge than you realize.</span></p> <p><span style="font-size: medium;">Why? A variety of companies appear to be so intent on accelerating the learning curve for their systems that they are willing to give away all kinds of tools in order to induce people to learn their platform. Consequently, an individual who has just learned their system will essentially get &ldquo;locked&rdquo; into using the platform for the foreseeable future. We&rsquo;re talking about companies like Amazon, Google, IBM and Microsoft.</span></p> <p><span style="font-size: medium;">As we pass from one phase of AI to the next, the idea that machines are &ldquo;coming to take our jobs&rdquo; is becoming ever more remote. If anything, machines will transform a number of roles and create new opportunities for those who are ready and eager to evolve with the times.</span></p> <p>&nbsp;</p> <p><span style="font-size: medium;"><b><i>Of course, recognizing such new opportunities isn&rsquo;t always obvious. That&rsquo;s why it makes sense to partner with a technical recruiter that has over 30 years of experience like Roy Talman &amp; Associates. Talking to us today about planning the next direction of your career path, especially as we&rsquo;re on the cusp of seeing a big leap in the development of systems, may make for the best kind of timing.</i></b></span></p> Your Company At The Speed Of Google 16 Jan 2018Blog<p>For as long as we can remember, Google is held up as a shining example of innovation in many respects. Yet, just as they admire Google, many people will say in the same breath, <i>&ldquo;Of course, I&rsquo;m not Google and I don&rsquo;t have Google resources.&rdquo;</i></p> <p>In a perfect world, you don't have to be Google to follow the model of what Google has done very well. Namely, Google is constantly in a state of change or planning on making change. Google is a search engine, yes. But as you know, it&rsquo;s also a phone. It&rsquo;s a photo album. It&rsquo;s a computer. It could soon be a self-driving car. It&rsquo;s a company that is intent on deploying various forms of machine learning.</p> <p>It&rsquo;s also a company committed to redefining the category they enter. For example, in the space of wireless headphones, was it Google&rsquo;s mission to deliver finer sound or deeper bass? Not really. Their headphones are designed to translate a wide variety of languages.</p> <p>They are also committed to evolving the innovations they&rsquo;ve had, including search. Make no mistake &ndash; the search you typed today on Google is much different than the one you did 5 years ago. The search you do on Google 5 years from now may be drastically different too.</p> <p>&nbsp;</p> <p><b>What Does This Mean For How You Innovate Today?</b></p> <p>As I&rsquo;ve written in another Tidbit (<i>&ldquo;When Did We Get So Satisfied With 10% Innovation?&rdquo;), </i>many large companies devote 90% of their technology spend on preserving the status quo and 10% toward true innovation. We should be thinking about how we can flip that equation because too many companies have it backwards. What if we could focus 90% of our technology spend on innovation and only 10% on maintaining our current place in the world? You&rsquo;d probably resemble a very different type of company in many ways, right?</p> <p>The truth is, <b>many large companies will have no choice but to explore this kind of 90/10 ratio for their own survival</b>. That&rsquo;s because the speed with which we're consuming technology is growing exponentially. You don&rsquo;t have to look far for a big example of this: It once took a large corporation to accommodate databases that were almost a gigabyte. Now, people can walk around with 256 gigabytes in their pocket, thanks to their smartphones.</p> <p>I believe that most successful companies such as Apple reinvest their product line essentially on their phones once a year. You can be sure that Google reinvents what they're offering us more than once a year. Still, you don't have to be a Google, Apple or have any kind of revenue approaching these companies in order to adopt their mindset. What I find is that the <b>nature of the organization&rsquo;s DNA could be described by its background, its culture, its history, its mission &ndash; not what it makes today.</b></p> <p>What you have embedded in the DNA of many of today's firms that are big successes is that they are essentially digital companies operating in a space where the cost of computing is collapsing every 11 months, according to the futurist Ray Kurzweil. These companies should expect to deliver twice the computing to their customers a year from now.</p> <p>A company could say, &ldquo;<i>I'm stamping steel</i>&quot; and that's one way to look at it, but the other one is, &quot;<i>I have digital forms that will be sent to this device that will stamp on steel</i>.&quot; So it&rsquo;s really not about stamping steel at all. It&rsquo;s about building tools that will allow a much faster way to design the parts that will then be shipped out.</p> <p>Apple doesn&rsquo;t manufacture their own chips. They <i>design</i> their own chips. And those chips are the core expertise of Apple. Because of it, Apple knows that they need to have at least <i>twice </i>the computing capacity in their chips a year from now that they currently have because that&rsquo;s what it takes to be competitive.</p> <p>Other organizations have marketing or sales at their core &ndash; Procter and Gamble is really a marketing organization, for example, not purely a manufacturer. Over the last 15 years, companies that became world-wide behemoths are the same ones who are digital at their core and appreciate how much value they can deliver to literally billions of their customers and still make a profit while actually having very little revenue coming in per person. In fact, until this century, we had no companies that had a billion simultaneous users. My, how times have changed in the age of Facebook.</p> <p>Remember the 90%-reinvention-to-10%-maintaining ratio. Consider the bigger picture beyond the product of today you offer. Realize that based on consumption, your primary product could look radically different or could be non-existent altogether in favor of another advanced product due to how your company has evolved. Think about how your culture and mission can drive innovation and profit. Finally, embrace the state of constant change that could move you toward redefining categories instead of making product tweaks for marginal impact.</p> <p>It&rsquo;s not the domain of billion dollar companies alone.</p> <p><b><i>Roy Talman &amp; Associates has been able to identify the kind of talent that catapults companies to great success for over 30 years, helping businesses stay nimble in the face of consistently changing demands. If you&rsquo;re in the technology, financial trading or management consulting space, let&rsquo;s have a conversation about the next phase of your potential growth and how we can play a role in it today.</i></b></p> Machine Learning Is Heating Up Tech Opportunities In Financial Trading 09 Jan 2018Blog<p>I was recently part of a panel at the Global Derivatives Conference here in Chicago in which the topic was the application of <b>machine learning</b>. Interestingly, it became clear during our discussion that there are several people who believe machine learning is, basically, the be-all-end-all &ldquo;Holy Grail&rdquo; for success in quantitative finance.</p> <p>The real question is: Is it? Like most things, the answer isn&rsquo;t quite that simple. However, what we can say is that we&rsquo;re in a new phase in which machine learning is getting a supercharge. Machine learning encompasses a set of tools that are being developed at a dramatic pace. As part of this phase, people are trying to figure out how to apply new tools to the centralization of financial trading. To me, the interesting thing is that from everything I've seen, developing those applications is not necessarily going to be easy.</p> <p>Any time you approach a new tool or technology that&rsquo;s truly revolutionary, you&rsquo;re going to have a philosophical discussion that asks, <i>&ldquo;How will applying this tool to a variety of things yield new knowledge for us?&rdquo; </i></p> <p>&nbsp;</p> <p><b>The Current Landscape As We Know It</b></p> <p>Right now, you have large companies built on the central application of these technologies for financial trading. The most visible of those companies is called Sigma and a more prominent &ldquo;stealth&rdquo; company, Renaissance Technology, seems to have been applying all of these tools for a while, becoming one of the most successful of its kind. Beyond this tier of companies, more and more people are trying to get into this area. With almost any technology related to financial trading, there may be initial success followed by increased spending and ultimately, continued growth.</p> <p>We&rsquo;ve seen this pattern of initial success-spending-growth before many times, haven&rsquo;t we? Take computers, for example. Over time, computers got to be so powerful and expensive that I've been told that at one point, some of our clients were replacing their PCs <u>every three months</u> because the PC coming out three months later was that much faster. That kind of speed truly made a difference to them.</p> <p>So initial success leads to increased spending on technology, which eventually begs the question related to growth: <i>How much do you want to spend to get another one dollar of net expected revenue?</i> If we&rsquo;re talking about spending one dollar, that&rsquo;s an obvious decision. If it&rsquo;s spending $1000, however? Not so obvious. If it&rsquo;s $10,000, maybe it&rsquo;s not worth the trouble after all.</p> <p>As machine learning moves beyond the &ldquo;early adopter&rdquo; phase, we see quite a few companies seeking to continually invest in it that will probably shape the changes in the market. Surely this means we will see more companies succeed as others wither.</p> <p><b>With increased investment in this area, what implications are there for the types of candidates that might be working within these companies on machine learning on the software side?</b></p> <p>We&rsquo;re beginning to see a lot of possibilities on this front. For example, we&rsquo;re seeing the potential usage of image processing in analyzing satellite photos or photos taken by drones that, of all things, could be used in a financial trading capacity.</p> <p>How&rsquo;s that? Let&rsquo;s say you&rsquo;re a retail analyst and you want to know how much activity is happening on a particular day, like Black Friday, the day after Thanksgiving. In order to understand what the foot traffic might be to your store, you could analyze the number of cars that enter all the parking spots designated or near your store.</p> <p>What if the parking lot is full? Well, then you might analyze if the cars parked in those spots right now are the same cars that were parked in those spots one hour ago. So to the degree that you can figure out how much traffic a particular store generated in terms of people coming in and out, you might obtain some significant insight to help you in planning going forward. You can then potentially say, <i>&ldquo;Our store did really well on this particular day, which happened to be when we had a blowout sale&rdquo;</i> or even <i>&ldquo;Our parking lot was busier this year by 10% compared to last year &ndash; what did we do differently this year?&rdquo;</i></p> <p>As another example, we know that as it enters the retail grocery space, Amazon has been working on a prototypical store called &ldquo;Amazon Go&rdquo; without any cashiers. The customer walks in, is identified by an Amazon Go app, selects the items they need and then leaves &ndash; without ever going to a register. How are they charged upon leaving the store? The system keeps track of the entire experience based on machine learning and a variety of sensors.</p> <p>People are working on technologies just like this to provide greater financial insight so customers can get data that is ever-more quantifiable. However, here&rsquo;s where a lot of opportunities may arise for candidates &ndash; with so many rollouts of new technologies, <b>there is always a troubleshooting, testing, improving and evolving component that requires the human element.</b> Machine learning is very exciting but it&rsquo;s not perfect. What looks great on paper has to be executed flawlessly in the real world. As we know, that doesn&rsquo;t always happen, thus the opportunity that exists for candidates.</p> <p>What&rsquo;s also only to the candidate&rsquo;s benefit is that most forward-thinking firms in financial trading (and beyond) who will win in this highly competitive landscape will surely recognize that machine learning and its progression as it pertains to the company will require a lot of <b>sustained investment</b> over the long haul. They know it is a marathon, not a sprint. They also know that if they want to succeed and have a competitive advantage, the edge they want to achieve over other firms may be fully realized in <b>the long-term rather than overnight.</b></p> <p>If you find yourself interested in the opportunities that machine learning may present, pay attention to financial trading companies that are making such investments in these technologies. Yes, some are more secretive than others, but as more companies reveal themselves to be committed to achieving a long-term competitive advantage, it may be a good time to discover if their goals mesh with your own.</p> <p><b><i>Roy Talman &amp; Associates can supplement this process of discovery by shedding light on financial trading firms that are making significant headway on the technological front today and where they&rsquo;re headed tomorrow. It&rsquo;s what our over 30 years of building relationships in the financial trading space can provide you. Together, we can pave a more well-informed path for your career, even when the field and its associated technologies are in a state of constant change.&nbsp;</i></b></p> <p>&nbsp;</p> Did We Get So Satisfied With 10% Innovation? 20 Dec 2017Blog<p>I came across a research study recently that, frankly, surprised even this industry veteran with deep knowledge of the tech space. The study found that of a large business&rsquo; typical technology spend, 90% is devoted to preserving the existing state of technology at the company while only 10% is spent on doing something new.</p> <p>10%! In the past, some of us may have looked at a tech company with this type of spend breakdown and thought, &ldquo;Wow, isn&rsquo;t it innovative that a company is devoting a portion of their funds to work on something totally different than what they do now?&rdquo;</p> <p>Let&rsquo;s take a closer look at what we&rsquo;re really talking about, though. The reality is that a company that is only 10% innovative can&rsquo;t be considered good enough.</p> <p>Yes, they can continue to devote 90% of their finances to staying current and &ldquo;getting by&rdquo; but at some point, new technologies do come along. If the company hasn&rsquo;t evolved by then, it&rsquo;s a company that&rsquo;s going to be seen as a dinosaur.</p> <p><strong>Expect, Anticipate And Act &ndash; There Is No Choice</strong></p> <p>I&rsquo;ve been reading a very good book called &quot;What To Do When Machines Do Everything&quot; by Malcolm Frank, in which the author points out that as automation and various forms of machine intelligence become more capable, they will permeate our business lives and at some point, our personal lives.</p> <p>For a variety of companies wondering what machine learning may mean for their business in both the short-term and long-term, Frank advises them to expect a trend so they can better anticipate that trend rather than wait for it to arrive and then wonder what they do next. With better expectations in advance, a company has a much better chance of taking advantage of the trend when tools become available that are used for particular business problems and processes.</p> <p>What follows in his line of thinking is particularly important &ndash; he urges large, established companies not to cling to the old way they've done it for the last 50 years, but to try to figure out how to re-engineer their business to be built around more digital trends. This way, they can collect more information and figure out how their business relates to this new technology about to be used.</p> <p>Now, I don&rsquo;t believe automation will fully displace human intelligence and analytics. There's still great value for companies to use automation technologies to look at vast data sets, but we also have to account for the human factor in helping machine learning technologies continue to progress.</p> <p><strong>Do We Have All The Data We Could Ever Want? Not Quite.</strong></p> <p>Some think we have all the data we could ever want, but I take issue with that. Suddenly, the amount of data created for day-to-day things like smart watches means there's always data that could be analyzed and consumed. And even within all of this consumption and analysis, do machines know how to place the data in the proper context of what the organization is striving to accomplish and make meaningful suggestions? Sometimes yes, sometimes no.</p> <p>Let me give you an example of what I mean.</p> <p>The other day, I received a notification from Google Maps that said, &quot;Here's what you've done for the month of November.&quot; It could identify when I left my house, parked my car and so forth. Google Photos can tell me that it just organized all of my photos for me so that I can look at all the appropriate people I&rsquo;d like to. So there&rsquo;s certainly a fair amount of data and organizational capability, but when it comes to connecting the dots from data to insight, there is still room for continual improvement.</p> <p>Instead of hoarding data and trying to save it all for analysis at some later time and having people drown in that data trying to analyze it, there are a variety of applications related to machine learning pointing toward a smarter way such as subscribing to a thousand news feeds, then having an intelligent assistant scan through those and figure out what you need to consume most.</p> <p><strong>How Do We Get More Than 10% Innovative?</strong></p> <p>Within your company, you should be continually looking at your technology stack and saying, &quot;Which technology is still producing the best returns for me,&rdquo; and &ldquo;Which technologies I should get rid of and replace?&quot;</p> <p>Perhaps that&rsquo;s a complex question to answer, but that doesn&rsquo;t mean the status quo is perfectly acceptable either. Consider that a great many of the largest financial institutions have never figured out how to get rid of old technology that, for whatever reason, they&rsquo;ve grown to depend on.</p> <p>In fact, I know some of the largest brokerages still have mainframes circa 30 years ago as the core of their technology. These same brokerages are also still using Cobal and CICS because after these technologies and others like them were built, nobody invested in a mission of keeping up with the times and planning for the future from a technological standpoint. Consequently, you still have technology in some of these brokerages that was popular in the late 1970's and early 1980's.</p> <p>What this essentially says to me is that you have technological progress creeping along that many organizations have somehow managed to more or less avoid. Unfortunately, they can&rsquo;t figure out how it&rsquo;s probably easier to jettison certain technologies. They also can&rsquo;t figure out what progress really looks like because the people running the company didn't appreciate how fast technology is changing or</p> <p>should be changing. As such, they didn't build into their business (and their business perception) the fact that technology will be ever-changing and that it will be getting continually cheaper and more capable. Consequently, these organizations may be just fine for quite a while. They can even be leading the way &ndash; until a new type of disruption comes along.</p> <p>When that disruption occurs, how easy will it be for a large organization to be quickly adaptable? Can your company go from a 30-year-old system at its core to a system that&rsquo;s 3 months old? That might be very difficult. Organizationally, some people in place likely don't have the skill for making this type of transformation as they&rsquo;re already top-heavy on maintaining things &ldquo;as is.&rdquo;</p> <p>Being more than 10% innovative also extends to the way you hire. Instead of matching people to job descriptions, truly innovative companies factor in for a range of complexities that include culture, work style and many other pieces in addition to the individual&rsquo;s skill set.</p> <p><em>At Roy Talman &amp; Associates, we help tech companies develop a hiring strategy that doesn&rsquo;t merely identify the best people for current roles of need today but the best people to help lead a company through the potential changes and disruptors we foresee later on. Because the more people who are nimble and proactive in the face of impending change, the more likely a company can commit to innovation at much higher than a 10% level.</em></p> Are Some Jobs Open Forever And What Can We Do About It? 11 Dec 2017Blog<p>Company A has a job that needs to be filled. After the opening becomes available, one month passes. Then another month and another. Before long, it&rsquo;s well over six months, which begs the question: <b>Why isn't this job getting filled?</b></p> <p>On the surface of it, it would look like the company can&rsquo;t find a qualified candidate. However, my take is that it's probably something else.</p> <p>As certain industries &ndash; financial trading, for example &ndash; have been challenged by various business conditions, some companies are saying,&nbsp;<i>&quot;OK, we&rsquo;ve got some serious work to do. We can&rsquo;t just bring aboard a solid candidate to fill a role. We need somebody who will make a difference and help us compete extraordinarily better.&quot;</i></p> <p>Welcome to a whole new ballgame. Suddenly, someone meeting the criteria of being very well competent in their skill set may actually be insufficient. That&rsquo;s because a variety of companies are seeking the kind of candidate will give&nbsp;<b>their business</b>&nbsp;<b>a competitive edge</b>. That's a&nbsp;<i>much</i>&nbsp;higher standard versus matching talent to a position. In this kind of situation, it's often understood that companies will look for a long time because bringing in someone who can&rsquo;t enhance their competitive position just won't do them any good. Patience comes to those who wait and these companies are frequently willing to do so.</p> <p>This might explain why some of these coveted positions seem to be open for what seems like, well, forever.</p> <p>The rationale reminds me of how a music company decides whether they&rsquo;re going to sign an artist or not: Do they need to sign new artists? Of course. But the real question for them during an evaluation period is:&nbsp;<i>&ldquo;If we sign this artist, is he or she going to put our label on the map as a bonafide superstar? Are they going to have one hit after another, win a bundle of Grammy awards, sell millions upon millions of albums and have a die-hard loyal fan base? Is this the next Taylor Swift, Beyonce, etc.?&rdquo;</i></p> <p>They&rsquo;re looking at the artist they sign and evaluating their impact on a generation over the next decade or more. If they&rsquo;re a &ldquo;one hit wonder&rdquo; at best, will signing that artist do the record label any good? Questionable.</p> <p>In another example, look at any Olympic team in track and field, swimming, gymnastics, etc. Are these slots to be &ldquo;permanently&rdquo; filled? No. All you have to do as an athlete is compete at a higher level than a person already on the team and you&rsquo;ll knock them off the team.</p> <p>It&rsquo;s why a hiring manager can view their team through a lens we refer to as &ldquo;<b>Evergreen</b>&rdquo;: Their current team has a strong skill set for the time being but if and when they find a candidate who is even stronger, anything is possible and nothing is set in stone.</p> <p><b>Another reason jobs go unfilled forever? Too narrow of a focus.</b></p> <p>Picture a manager who has a very specific problem they need solved right now. With that specificity in mind, they look for the perfect candidate who has a&nbsp;<u>very particular skill set</u>&nbsp;to solve&nbsp;<u>that very particular challenge.</u></p> <p>You can see where this is headed, can&rsquo;t you?</p> <p>It&rsquo;s great if it works out, but all too often, the definition of the candidate is so narrow that the list of potential candidates who might be an ideal fit also narrows down dramatically.</p> <p>Along these same lines, certain companies insist on using a&nbsp;<b>test</b>&nbsp;to effectively identify the very best candidate possible. There&rsquo;s nothing wrong with that. However, if only a very finite number of people can legitimately&nbsp;<i>take</i>&nbsp;that test &ndash; the candidate pool can get awfully limited in a hurry and yes, perhaps too limited.</p> <p>For example, let&rsquo;s say that a company requires that all candidates for a particular role be required to take a test but they insist that only five percent of all candidates ultimately have access to the test.</p> <p>One of the primary skills of the position, in a given metropolitan area, is held by 10,000 people. Seems like a large number, doesn&rsquo;t it?</p> <p>However, we need to narrow the list down to a particular industry, which might take our once large pool of 10,000 people down to 1,000.</p> <p>Here&rsquo;s where the pool can become quite tiny: If the company insists that only five percent of candidates be able to take the test, 1,000 candidates remaining will dwindle down to no more than 50 candidates total.</p> <p>50 candidates would still appear to be a lot - but wait. We&rsquo;ve only identified these 50 people by virtue of them having a matching skill set. We still don&rsquo;t know&nbsp;<u>if they&rsquo;re interested in the position, if they&rsquo;re available for an interview or if they are affordable based on salary!</u></p> <p>Consequently, the hiring manager could be looking at a situation where that job could go unfilled for a while because the candidate pool is&nbsp;<i>too small.</i>&nbsp;They may have all the urgency in the world to fill a job, but it&rsquo;s tough to fill a job when the selection criteria of candidates is already so narrow and the expectation of them making a long-term positive contribution is already so great.</p> <p>It&rsquo;s a combination that can bring a lot of uncertainty.</p> <p>Even doing well on the test is no &ldquo;sure thing.&rdquo; In fact, we were recently aiming to place a candidate and the initial signs were very positive. The candidate excelled on technical test portion of the company&rsquo;s hiring process but it was during the interview that there were issues because the answers he gave weren&rsquo;t quite to the company&rsquo;s satisfaction.</p> <p>Now, perhaps the interviewer had a very detailed and systematic approach to asking questions in that he wanted a&nbsp;<i>precise</i>&nbsp;answer to address each question rather than an answer that remotely veered off course a bit. In that type of situation, some candidates can have difficulty even though, at the same time, they may perform well during a test that requires them to solve problems.</p> <p>On the positive side, although it&rsquo;s becoming even more challenging to fill certain technology jobs, what that also tells me is that&nbsp;<b>technology jobs are becoming even more valuable to an organization</b>. It&rsquo;s a changing world in which the companies that are hiring tend to emphasize the kind of technology that is less than five years old.</p> <p>Candidates may find themselves with a higher bar to clear these days, but there&rsquo;s good news in that development too &ndash; regardless of whether a person has five years of experience or 25 years of experience,&nbsp;<b>candidates who are driven to get ahead and heavily invest the time in training for the interview process (including tests) can excel.</b>&nbsp;No longer can a candidate purely rely on what they already know. Those who push themselves to be proficient in new technologies while elevating their interviewing skills for technical jobs may be at the top of what is becoming an increasingly narrow list.</p> <p><b><i>Jobs can be open for an infinite period of time in some cases, but make no mistake &ndash; those conditions can change. At Roy Talman &amp; Associates, we understand the balance that must occur between being highly selective and highly attractive. If a company is selective and the candidate pool is tiny, that business will have a difficult time finding the diamond-in-the-rough talent they&rsquo;re seeking. So we work closely with those businesses to ensure their focus isn&rsquo;t so narrow that it limits their opportunities to identify a promising talent.</i></b></p> <p><b><i>Meanwhile, we also work with candidates to steer them in the proper direction as they strive to stand out in an increasingly competitive crowd. When you have over 30 years of recruiting experience as we do, even the most narrow windows of opportunity can open up quite a bit more.</i></b></p>, Not Imagining, The Candidate Is Believing 30 Nov 2017Blog<p>It&rsquo;s natural to assume that finding a new role can take a while, especially if the candidate has been with the same company for a very long time. There may be many resumes sent out, a number of interviews with various firms until an ideal match is found and &ndash; let&rsquo;s face it &ndash; in cases where a company values youth over experience, being over 40 years old doesn&rsquo;t necessarily make the job search any easier either.</p> <p>However, we were pleasantly surprised at Roy Talman &amp; Associates to encounter two situations that bucked this trend. Two candidates we were placing who were with their respective employers for over 10 years&hellip;received offers after interviewing with just <u>one</u> firm each.</p> <p><i>How does something like that happen? </i></p> <p>For one, <b>calling the right recruiter FIRST</b> is the critical first step. When you&rsquo;re working with a recruiter who has less credibility with a client and lacking knowledge of the recruiting process to come associated with that client, your resume can tend to fall into a black hole. In that event, the silence can be deafening! In contrast, if you can connect with a highly experienced recruiter who has a deep knowledge of the client&rsquo;s priorities, you can potentially avoid wasting a lot of valuable time with a company that isn&rsquo;t a clear fit.</p> <p>Next, <b>do you understand everything possible about the firm you&rsquo;re about to interview with?</b> What do you know about their history? What sort of culture do they have? Where does the leadership seem to want to direct the company tomorrow? If you come into an interview without this depth of knowledge, it could lead to an uncomfortable situation where it looks like you want the job at all costs but haven&rsquo;t taken the time to know the company in the process.</p> <p>There&rsquo;s also <b>no such thing as preparing too much for the interview.</b> Interviewing is a potential minefield in which you could step in the wrong direction and &ldquo;blow up&rdquo; based on your answer. While we can&rsquo;t predict every question an interviewer may ask, we can certainly plan for many possible scenarios and tests. Simply having a partial road map of where the interview process could go will give you the game plan you need to go into the interview with greater confidence &ndash; which matters a tremendous amount.</p> <p>Another crucial piece of the equation: A <b><i>personal interaction</i> with the candidate</b> can dramatically change any preconceived notions about that individual a hiring manager might have.</p> <p>This is to say that in the real world, a hiring authority will know they want to hire the person after they meet the person. But the person they actually end up hiring <i>isn&rsquo;t exactly the same person they envisioned they would hire for the role.</i></p> <p>Two of the most successful people in the last 100 years express this sentiment well:</p> <p><i>&ldquo;If I had asked people what they wanted, they would have said faster horses.&rdquo;</i> &ndash; Henry Ford</p> <p><i>&ldquo;A lot of times, people don&rsquo;t know what they want until you show it to them.&quot;</i> &ndash; Steve Jobs</p> <p><b>With this in mind, what does it mean if the person ultimately hired is going to wind up being so different from the candidate &ldquo;on paper&rdquo;?</b></p> <p>Let&rsquo;s recognize a fatal flaw in trying to identify a fit <u>based purely on a job description</u>. Many job descriptions are recycled because they&rsquo;re easy to dash off quickly with a lot of HR &ldquo;boilerplate&rdquo; language inserted in like &ldquo;<i>progressive organization</i>,&rdquo; &ldquo;<i>team-oriented environment</i>,&rdquo; and &ldquo;<i>self-starter</i>.&rdquo; Or you could see the reverse in which every possible responsibility is stuffed into the description because the person writing the job description assumes the person looking at the job only reads the job title. Everything else underneath that title is too much information.</p> <p>From the candidate&rsquo;s perspective, you want somebody to sit down and understand your story. Your recruiter is going to be, essentially, your marketer. So they need to be able to figure out what's marketable about your skills, how to present it and who to present it to. If you're a job seeker, it's nice to have a really competent, knowledgeable person putting out a one-of-a-kind, unique infomercial about you to some of the more selective companies around.</p> <p><b><i>If you&rsquo;re going to hire a person based on the actual interaction you have versus the image of that candidate in your mind, it demands a more personalized approach from the beginning with a specialized recruiter like Roy Talman &amp; Associates. It&rsquo;s a more intelligent, focused approach to recruitment that both candidates and the companies considering them deserve.</i></b></p> <p>&nbsp;</p> Recruiting, Personalization Beats “Blasting” Any Day 10 Nov 2017Blog<p>From where I sit, having an inside view of what's going on in the recruiting space, traditional contingency recruiters have expressed how they&rsquo;re having a hard time in their line of work in recent years.</p> <p>Between online tools such as LinkedIn and internal referrals, the competition for placing people in &quot;regular jobs&quot; is more challenging than ever. Why? For one, since it's so easy to apply, certain jobs will get a very large number of applications. Modern systems will then automatically shoot out a polite message that sounds something like, &ldquo;Thank you, we received your message. If we're interested, we'll get back to you.&quot; In the vast majority of the cases, only a very small percentage of these inquiries will actually get a response.</p> <p>Consequently, more recruiters are being pushed toward finding some really hard-to-find people in a tight window of time. However, where they could afford to rely on more of a templated approach to candidate communication with that audience, they can&rsquo;t do the same among more sophisticated roles that demand a more personalized approach. If the message from the recruiter feels impersonal, the candidate for a highly specialized position will know it and move on.</p> <h3>Many Tools Out There To &ldquo;Make It Easy&rdquo; Aren&rsquo;t Helping</h3> <p>Recruiting also continues to go down a path that&rsquo;s quite impersonal in part due to the tools in the marketplace that make it easy to do so. Take ZipRecruiter, for example, with a pitch that they&rsquo;ll get your job seen on a large number of websites. Or do a search on Google for Java-based jobs in Chicago and you&rsquo;ll not only see there are over 2,000 of those jobs that aren&rsquo;t listed separately but you can go to and see an ocean of them.</p> <p>This begs the question: With that kind of saturation, why do we need to create 200 versions of an ad to describe the same or similar job posting? Does it really add much value?</p> <p>With tools that favor &ldquo;blasting&rdquo; out job postings, companies become spammers and candidates quite often either don&rsquo;t read the job or don&rsquo;t find there's enough information in each job. None of these outcomes are desirable.</p> <p>Now, a hiring manager could write a five-page job description that spells out in excruciating detail everything the person will be doing, might be doing, should have done, could be able to do, the essential skills required and more. But there are some downsides to this:</p> <p>&middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Who's going to read all that?</p> <p>&middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The description of the role may change five minutes after the posting is sent</p> <p>&middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; It&rsquo;s all negotiable anyway</p> <p>Here&rsquo;s an example of what we mean by that third point: One of our clients told us about the type of candidate they were looking for &ndash; all core Java developers of a certain type.</p> <p>Well, wouldn't you know it? The person they wound up hiring doesn't really do Java! He does C Sharp. As it turns out, he's a superb software developer and there are enough similarities between C Sharp and Java that the client discovered it was going to take this hire a fairly short time to go through the learning curve to learn what he does now.</p> <p>From this point of view, insisting that you need to have so many years of experience with this or that particular technology quite often turns out to be less critical than you originally thought. Whenever we try to describe what we need and want, what we&rsquo;re really doing is envisioning an idealized future of what the job probably will have and the probable skills the person needs to have.</p> <h3>Seeing &ndash; Not Imagining &ndash; The Candidate Is Believing</h3> <p>Two of the most successful people in the last 100 years express it well:</p> <p>&ldquo;If I had asked people what they wanted, they would have said faster horses.&rdquo; &ndash; Henry Ford</p> <p>&ldquo;A lot of times, people don&rsquo;t know what they want until you show it to them.&quot; &ndash; Steve Jobs</p> <p>This is to say that in the real world, a hiring authority will know they want to hire the person after they meet the person. But the person they actually end up hiring isn&rsquo;t exactly the same person they envisioned they would hire for the role.</p> <p>With this in mind, what does it mean if the person ultimately hired is going to wind up being so different from the candidate &ldquo;on paper&rdquo;?</p> <p>For one, let&rsquo;s recognize a fatal flaw in trying to identify a fit based purely on a job description. Many job descriptions are recycled because they&rsquo;re easy to dash off quickly with a lot of HR &ldquo;boilerplate&rdquo; language inserted in like &ldquo;progressive organization,&rdquo; &ldquo;team-oriented environment,&rdquo; and &ldquo;self-starter.&rdquo; Or you could see the reverse in which every possible responsibility is stuffed into the description because the person writing the job description assumes the person looking at the job only reads the job title. Everything else underneath that title is too much information.</p> <p>Companies may not absolutely know who&rsquo;s really in the market for a job, but that doesn&rsquo;t mean &ldquo;blasting&rdquo; a job out there across the online spectrum is a great approach. Yes, you still need to reach out to a certain number of people &ndash; the key phrase being &ldquo;certain&rdquo; number of people. Not all of them.</p> <p>If you&rsquo;re going to hire a person based on the actual interaction you have versus the image of that candidate in your mind, it demands a more personalized approach from the beginning with a specialized recruiter like Roy Talman &amp; Associates.</p> <p>From the candidate&rsquo;s perspective, you want somebody to sit down and understand your story. Your recruiter is going to be, essentially, your marketer. So they need to be able to figure out what's marketable about your skills, how to present it and who to present it to. If you're a job seeker, it's nice to have a really competent, knowledgeable person putting out a one-of-a-kind, unique infomercial about you to some of the more selective companies around.</p> <p>In that moment, it&rsquo;s our job to be the first phone call the candidate makes. That&rsquo;s the advantage of going to Roy Talman &amp; Associates as opposed to distributing their information far and wide. It&rsquo;s a more intelligent, focused approach to recruitment that both candidates and the companies considering them deserve.</p> <p>&nbsp;</p> <p>&nbsp;</p> <h3>&nbsp;</h3> You Need To Be Unhappy To Leave Your Job? Oct 2017Blog Hiring Managers Respect Online Education Anytime Soon? Oct 2017Blog