Category Archives: Automation

In a monthly series, menu trend analyst Nancy Kruse and NRN senior food editor Bret Thorn debate current trends in the restaurant industry. For this installment, the two discuss robots in restaurants.

Nancy Kruse on the rise of robots:

When it comes to research, Im stubbornly low tech. Im embarrassed to admit, Bret, that I keep old-fashioned subject files full of clippings on hot topics, a practice that I returned to after an early, unsuccessful attempt to go paperless. (Dont judge me, but I also prefer real books to Kindles and traditional newspapers to iPads.) Based on the burgeoning size of my file on the subject, it is ironic, then, that robotics and their impact on the restaurant industry is a major hot-button issue of the moment. Just consider this random sample of articles:

In June, Entrepreneur magazine asked the rhetorical question When Will Robots Finally Take Over the Fast-Food Business? and proceeded to forecast that quick-service dining is inevitably headed to a largely automated future.

Operators who have jumped into robotics have predictably grabbed headlines, like Zume, a pizza joint in Northern California that uses robots to make its pies. Down the coast a few hundred miles, Pasadena, Calif.-based CaliBurger uses a robot to flip hamburgers, and airport-concessions titan HMS Host has tested a robot at one of its pubs to engage consumers with its food and drink offerings. As an aside on these last two, there seems to be an attempt to humanize the bots; the former is dubbed Flippy and the latter is called Pepper.

Its not surprising that early digital adopters like Dominos Pizza, which blazed a trail and boosted its business with its sophisticated ordering app, are actively experimenting with robots. After its initial trial run in New Zealand, Dominos DRU delivery robot was dubbed cheeky and endearing in a press release, another example of anthropomorphism that suggests the little guy dispenses one-liners and hugs along with its pizza.

The topper, though, is surely KFCs H.A.R.L.A.N.D., a robotic Colonel Sanders that accosted unsuspecting customers at selected drive-thru locations and used technology to make the drive-thru operators voice sound just like Sanders Kentucky drawl. As a promotional gambit, it may have been superior to some of his white-wigged, real-life impersonators, like the unnaturally tanned, B-list actor George Hamilton, who portrayed him in a TV commercial sometime back.

At CaliBurger, a robot named Flippy flips hamburgers.

While theres obviously a great deal of interest in the subject, I think its a little early to say exactly how robotics will impact our business in the long term. Of course, that hasnt stopped legions of prognosticators and doomsayers, most of whom maintain that this all spells the end for low-income workers, especially those in the back of the house. But early results suggest otherwise. The Entrepreneur story quoted a scary statistic from consultants at McKinsey & Company that estimated that a hefty 73% of foodservice activities have the potential to be automated. However, theres a distinct disconnect so far between potential and actuality, as the article goes on to describe how Panera Breads ambitious 2.0 initiative to implement mobile and kiosk ordering has actually resulted in more employees per location. It turns out that digital ordering increases both the volume of orders and their size, which necessitates extra labor to handle the flow. And while Zume Pizza executives say that the operation does employ fewer people than comparably-sized competitors, the chairman of CaliBurger believes that Flippy wont replace workers, but will free them up for less repetitive tasks that add value to the patron experience.

It strikes me that a couple of things are worth keeping in mind as the debate revs up, which it certainly will. First, in all the piles of papers written on the technology, none has suggested that robots can or will replace the creative talents of the chefs who cook up innovative dishes in the kitchen, negate the continuing importance of the face-to-face factor that is the foundation of hospitality in the dining room, or displace the talented concept developers including those behind Zume Pizza and CaliBurger, who keep the industry vital and vibrant.

Theres also a sense of dj vu all over again, as the robotics uproar harks back a time maybe 25 years ago, when we found ourselves enmeshed in a similar controversy.

Computers were coming into their own and bringing with them dire predictions about the outlook for the foodservice sales function. Sales reps for distributors and manufacturers were put on the endangered species list, the futurists insisted, and slated to be replaced by the customers computer keypad.

Its evident that no such thing transpired. The computer didnt replace human interactions; rather it made them faster and more accurate, facilitated the flow of information and enhanced problem solving. As a bonus, it also relieved weary reps from having to lug around a 30-pound order book.

KFC has a robotic Colonel Sanders named H.A.R.L.A.N.D. that appeared at select drive-thru locations and used technology to make the operator's voice sound just like Sanders.

My hunch is that well see a similar dynamic here, as robotics ultimately helps foodservice employees rather than hindering them, and reorganizes them, but doesnt replace them. Having already confessed my Luddite use of clipping files, Bret, this discussion is a bit above my pay grade. So would you care to wade into the debate? Im interested in your thoughts on the subject, and just for the record, I dont believe you have anything to fear when it comes to man vs. the machine. In my humble opinion, youre way too cheeky and endearing to ever be replaced by a robot.

Bret Thorn on the ongoing shift:

Nancy, I love technology. I love it! I love my Kindle that weighs less than a book, doesnt use paper and lets me look up the meanings of words just by touching them. I love my completely searchable computer files of old menu items that can tell me, for example, what chains used asparagus last spring. I like catching up on the news on my laptop or phone (I dont have an iPad; I love technology, but Im also cheap).

I dont have much use anymore for newspapers or magazines I dont miss their feel or smell or whatever people nostalgic for those things miss and although my desk is cluttered with cookbooks and other paraphernalia, theyre just there because I cant figure out who to give them away to.

I look forward to what new technology has to offer, in foodservice as much as in any other facet of life. Panera Bread and other chains have already seen success with people ordering and paying for their food online and then showing up to collect their order thats already waiting for them on a shelf. Its seamless and free of cumbersome interactions with humans.

I like humans, but on the transactional occasion that a limited-service restaurant experience generally is, I dont see a need for one to be between me and my sandwich.

And there are concepts like Eatsa, where guests order, customize and pay for everything via kiosk. Its then assembled behind closed doors (Eatsas founders indicate that theres some automation in the meal preparation, but they also insist that the details are secret) and appears in a window for the customer to collect, like magic.

Or like an automat from the 1950s.

At Eatsa, customers pick up their orders in a cubby.

People have been worried about robots taking our jobs since the term was coined, according to a National Public Radio story form 2011, in 1920 by Czech playwright Karel apec. According to science historian Howard Markel, the word was derived from rabota, an Old Church Slavonic term for forced labor, and apec used it in the play R.U.R. or Russums Universal Robots, to describe soulless people flesh-and-blood, not metallic who were mass-produced to do all of our work for us.

As robots almost always do in fiction, they eventually rebelled and killed most of the humans.

In 1952, Kurt Vonnegut Jr. wrote Player Piano, about a dystopian future in which humans are divided between scientists and such who have jobs, and everyone else, who has been essentially outsourced by machines.

Its an old, tired, but nonetheless terrifying plot that gets recycled with each generation, both in reality and in fiction.

I agree with you that restaurants will see more automation, and I also agree with you that the results will be that workers jobs will change. The Panera example that we both cited illustrates that beautifully.

As the chain becomes more efficient, more people are required to prepare the food, but also as technology shifts, as a Panera executive explained to me as their 2.0 system was being implemented, humans have to be available to help guests with the ordering kiosks.

Panera Bread's initiative to implement kiosk ordering has resulted in more employees per location.

Additionally, Panera has worked to make its service better, hiring people to deliver food to tables for those who dine in the restaurant.

I recall that a few years ago you coined a phrase high tech, high touch. The technology improves on clunky points of friction like ordering and payment, while human beings check in with customers to make sure theyre happy and to resolve any problems that come there way.

Another example is Pizza Hut, which is simultaneously improving its delivery algorithm to be more efficient, but also hiring 14,000 more drivers to carry out that more efficient delivery.

Pizza Hut is improving its delivery algorithm to be more efficient, but also hiring 14,000 more drivers to carry out that more efficient delivery.

Will self-driving cars eventually replace those drivers? Maybe, and that could well free up those drivers to fill some yet unforeseen role. I dont know what it would be, but here in the publishing world we have a whole team of people whose job is engagement or figuring out the best strategies to present our words in ways that will be efficient and enjoyable for our online readers

That wasnt a thing when I started this job 18 years ago, working for what at the time was a weekly news magazine.

Self-driving cars may eventually replace delivery people, freeing them up to fill some yet unforeseen role.

Ah, but what about the kitchen? Surely automation will cut labor there, you might say.

Perhaps, but it seems to me that just as human hospitality remains important in many front-of-the-house situations, culinary creativity is also at the heart of foodservice.

You probably have read about efforts by the IBM supercomputer Watson to develop menu items. Back in 2014 the machine that was able to win at Jeopardy and is reportedly being put to work to help cure cancer also was put to work in menu ideation at the Institute of Culinary Education in New York City.

The IBM supercomputer Watson has been put to work in menu ideation.

Watson was fed a huge database of recipes, nutritional information and data on the molecular composition of ingredients. Then it was instructed to come up with flavor combinations from different culinary traditions say, Baltic combined with Korean and North African combining them in a way that chefs wouldnt have thought of. The chefs could specify the protein or other key ingredients they wanted to use and Watson would spit out combinations that might not have gone together traditionally, but that ought to work from a molecular perspective.

But all Watson could do was list ingredients. It was still up to chefs to develop dishes from them, and I think it will stay that way for many years to come.

Oh, and thanks for valuing my cheekiness and endearing qualities over DRUs, but lets wait and see what the next round of artificial intelligence looks like.

Nancy Kruse, president of the Kruse Company, is a menu trends analyst based in Atlanta and a regular contributor to Nations Restaurant News.

E-mail her [emailprotected]

Contact Bret Thorn [emailprotected]

Follow him on Twitter:@foodwriterdiary

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Will automation supplant the restaurant worker? - Nation's Restaurant News

I was amused reading the recent back and forth between Facebook's (NASDAQ:FB) Mark Zuckerberg and Tesla's (NASDAQ:TSLA) Elon Musk. It is funny when two heavy hitters, both of whom arguably should have a good understanding about a given piece of technology, fall on such opposite ends of the spectrum about its capabilities. Essentially it all started when someone asked Zuckerberg what he thought of Musk and his warnings about AI being an existential threat to humanity. He responded saying it was very irresponsible, to which Elon Musk replied on Twitter that Mark has limited knowledge about the subject. Is one of them wrong and the other right? Yes, I believe so, but more about that later. This exchange also got me thinking, is this belief the source of the lot of claims Musk has made about the capabilities and development of Tesla's Autopilot system? In this article, I will look into this a little more and show you some of the challenges faced in computer vision that illustrate the difficulties faced by a primarily vision-based fully autonomous driving system like Tesla's Autopilot 2.0.

It was just over six months back that Elon Musk promised customers would start seeing FSD features in Tesla's AP2 system over the next six months at the latest. However, customers haven't even seen their "Enhanced" Autopilot match the performance of the previous version of Autopilot let alone see any unique FSD features.

Now for anyone familiar with the technology, the fact that Tesla is facing a lot of challenges comes as no surprise. Unless Tesla makes significant strides beyond the current, state-of-the-art computer vision, I do not believe there is any way it can truly have a competent fully autonomous driving system under its current Autopilot 2.0 configuration. However, this is exactly what Tesla has been "promising" going as far as to hint that it would have details on a fully autonomous ride-sharing platform before the end of this year. By the way, that text hasn't changed since last year, so I guess we should now expect these details by end of 2018?

Source: Tesla

For a long time now, I had said Elon Musk and Tesla have been making knowingly misleading statements about the potential future capabilities of their system. However, as I hear his views more and more, I am starting to question if he really understands the technology and how it works. Before I go into this, let me take a step back and talk a bit about what has caused the recent revolution in the field of AI.

People have been using computers to automate a lot of work that humans have traditionally had to do manually. Indeed computers now encompass all aspects of human life. However, there were some problems that computer programmers found hard to write solutions for. One of the best examples of this is pattern recognition for example in the form of computer vision.

I can easily spot my wife in a large crowd of people, but if someone asks me how I do it, I will find it hard to describe what features I rely on to identify her. This is also one of the reasons witnesses find it hard to describe a potential suspect without the help of a sketch artist. It is generally hard to codify how the human brain interprets patterns from such visual data. This is where the idea of deep learning with large Convolutional Neural Networks comes in handy. The basic idea is that rather than trying to identify what features the system should look for, you instead just feed the system lots of data and have it learn the features that will help it identify similar objects.

The only problem here was that it took an excruciatingly long time to train a complex "Deep" network using large training datasets. With the advent of the use of GPU processing in training these systems, we are now able to use large amounts of data to train them in a reasonable amount of time. A job that would take weeks to months of running on a large CPU cluster earlier is now possible in a few hours to a few days, and this vastly expands the practical applications of these kinds of systems in pattern recognition. Over at FundamentalSpeculation, our price action based Momentum model is a result of harnessing this power of GPU processing in training.

However, at the end of the day, it is important to understand that pattern recognition is all that these systems are doing. It is not that they suddenly have a deeper understanding of what the objects in the picture represent. This is well illustrated for example by the work of Papernot, et al. in a recent paper where they used an adversarial system to trick a classifier that identifies road signs from MetaMind. This is an instance where there is an adversarial system being used specifically to target the classifier. But also consider edge cases where there is graffiti or a sticker or something similar on the sign and you realize there can be more benign instances where this can become a problem.

Source: Papernot, et al. The image on the left is an original image of a stop sign. The image on the right is a perturbed image that causes the classifier to mis-classify it as a yield sign even though it looks the same to the human eye.

To perform a real-world and properly-blinded evaluation, we attack a DNN hosted by MetaMind, an online deep learning API. We find that their DNN misclassifies 84.24% of the adversarial examples crafted with our substitute. -Papernot, et al.

The same concept also applies to achievements in the field of deep reinforcement learning. A lot of people including me celebrated when DeepMind's AlphaGo beat the world's best Go player earlier this year. However, even in this example, if the size of the board was any different than what the system was trained on, it would have failed miserably.

Humans have a tendency to see a machine perform a particular task and think of it as having a similar level of competency to a human capable of performing the same task. This generalization cannot be applied to the field of Machine Learning/AI. To be clear, I am not saying automation will not cause massive disruption to the economy. It has the potential to displace a lot of jobs. However, the idea that applications of "Narrow" AI that are becoming prevalent today are an existential risk and need to be regulated is silly. It is also the reason why "billions of autopilot miles" is a silly metric to gauge any potential advantage Tesla may have over its competition.

Driving a car is a very complex task. The reason the average human is reasonably good at it is because humans have "intelligence" which allows them to have a high level understanding of their environment and handle most of the edge cases fairly easily. This is fundamentally not true for AI systems we have today. When you think of these systems in terms of "automation" rather than "intelligence", you start to realize some of the hard challenges that need to be overcome. To top it all, Tesla's attempt to try to achieve this using a primarily vision-based system if anything puts it at a significant disadvantage to the rest of the competition.

So what does this mean for Tesla's Autopilot system? Firstly, a big part of my critique about its design is that it has minimal redundancy in its system. It is primarily a vision based system. However, this idea is sometimes challenged by stating that it has multiple cameras that offer redundancy. I don't mean to pick on my fellow contributor ValueAnalyst, but this was the most recent exchange in writing I remember having about this topic in a recent article I published about Audi's (OTCPK:AUDVF) new Level 3 system.

He is not alone in making this assumption. There was also a recent paper claiming why adversarial attacks like the one I talked about earlier do not apply to autonomous vehicles because there is redundancy in the various angles and scales at which the same object is observed and this defeats instances of mis-classification. What I find really funny is the rebuttal to this argument came from Musk's very own OpenAI.

We've created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and the like. - OpenAI Blog

Tesla's challenge though is even bigger. What we have been talking about so far is classification of well-defined categories of objects. Tesla's system however not only has to identify and classify these well-defined objects but also reliably identify any other potential object that is an obstacle in its drive path without false positives. This makes it a significantly harder problem. Again, I'm not saying the systems won't improve. However, the current state-of-the-art systems are not reliable enough to do this, and there is no reason to believe Tesla has surpassed the state of the art in this field. This makes Tesla's claim of achieving full autonomy in this short time frame all the more ridiculous.

None of this would matter that much if everyone understood that this as a field of research with future potential and not factor in its impact into current valuations. However, this is not the case. Again, I don't want to pick on any one person, but I'm drawn to Morgan Stanley's Adam Jonas. He is currently neutral on the stock after it reached his price target, but let's take a look at what got him to that price target. I remember watching one of his interviews on CNBC a few months back and having a hard time stopping myself from throwing stuff at the television to stop the insanity. What was really amazing about his performance was his confidence in talking about a topic he clearly has no understanding about. I highly recommend you watch his full interview.

We continue to believe over 100% of the upside from the current price to our $305 target can be accounted for by the value of Tesla Mobility, an on-demand and highly automated transportation service we anticipate to be launched at low volume in 2018. - Morgan Stanley

In a note he sent clients earlier that month, he tried to break down the prospects of the company by segments. He had assigned zero value to Tesla Energy because of its negative margins and he believed any prospects for this segment would be a rounding error in the grand scheme of things. He was significantly below the Street and management on the sales volume for the Model 3 while being higher than most on the average selling price of the Model 3 ($60,000). He spoke about some of his assumptions in an interview with Bloomberg at the time. He also is not all that very bullish on the sale of electric vehicles to individual customers. He gets to his valuation based on the assumption that Tesla will have a deployable autonomous driving system that can be used for ride-sharing within a Tesla Network.

"Well, we think the electric cars for private use really are ... for human driving pleasure for wealthier individuals. That's why it's so important that in the shared model where you're not driving 10,000 miles a year, but 50 or 100 in a fleet operation, then the economics of electrification you can get that pay back period under three years. That's the game changer - shared." - Adam Jonas, Morgan Stanley

So now what happens if this possibility evaporates? How much real demand would there be for a $35,000 electric vehicle if the possibility of generating revenue via participating in an autonomous ride-sharing network goes away? Forget even that, how many people are really interested in a midsize luxury sedan if the convenience of autonomous driving is taken away? Consider the volume of all Small/Midsize Luxury car sales in America last year shown below:

Source

The entire Small/Midsize Luxury segment sold a little over 800,000 vehicles across all manufactures and models in the US in 2016. Without the prospects of autonomous driving, this will be the target market for the Model 3. Further, as other manufacturers start to bring some of their more advanced driver assist and limited self-driving features to lower-range models, Tesla, relying primarily on its vision-based system, will have a hard time keeping up with the functionality offered by its competitors.

For a long time now, I have believed Elon Musk has been misleading TSLA shareholders and customers about the potential and development curve of Tesla's Autopilot system. While I still believe that, I am now starting to question whether he genuinely understands the capabilities and limitations of narrow AI systems. At the end of the day, neither option is good for Tesla shareholders. If and when the Model 3 starts to ship in large volumes, those future customers will have a lot of expectations for the autonomous driving technology promised to them and they may not be as forgiving as some of the early adopters have been so far.

Disclosure: I am/we are short TSLA.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: The Content provided in this article should be used for informational and educational purposes only and is not intended to provide tax, legal, insurance, investment, or financial advice, and the content is not intended to be a substitute for professional advice. Always seek the advice of a relevant professional with any questions about any financial, legal or other decision you are seeking to make. Any views expressed by Laxman Vembar are his own and do not necessarily reflect the view, opinions and positions of FundamentalSpeculation.IO. Finally, you should not rely solely on the information provided by the models on FundamentalSpeculation.IO in making investment decisions, but you should consider this information in the context of all information available to you.

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Automation != Intelligence - Seeking Alpha

Machines are being used to automate a rising number of processes in the marketing world. Programmatic ad buying, artificial intelligence, chatbotsand other emerging technologies are changing the landscape and bringing with them new efficiencies and ways of working.

It followsthen, thatmarket research also stands to benefit from automation. One such example is the use of robots to test the effectiveness of advertising.

Brands want answers to specific creative campaign questions before their activity starts (around messaging and execution), while it is live (to assess how the target audience is responding) and when completed (to determine what ROIit has delivered).

Automation improves the accuracy of this kind of research, speeds up the collection of data and can save brands money. It also makes ad testing more intuitive and should mean human researchers can spend more time analysing the results to produce the actionable insight that brands crave.

READ MORE:Artificial intelligence: A force for good or evil?

One British multinational to invest in a fully-automated creative testing process is Reckitt Benckiser (RB), owner ofbrands including Dettol, Durex and Cillit Bang.

It is working with market research technology provider ZappiStore to improve ad testing results. Byautomating processes it has been able to increase the number of ads it tests in a year by 77%, from 188 to 333, which has resulted in a 14% jump in market effectiveness. Previously the business focused primarily on analysing the effectiveness ofTV commercials but it now examines creativity across Facebook, point of sale and online video.

Automation allows large brand owners to think and act with the agility of a startup.

The company has also increased the number of brands it can evaluate from 25 to 32, which has improved overall ad effectiveness from 45% to 59%.

Mathilde Levy, RBs senior consumer and market insight manager for Europe and the US, says automation has made a big difference.

In the FMCG world there is the internal clock of the marketing function and the external clock of the life of the customer. These two clocks are not always synchronised, she says. By using automation the internal clock is more in tune and allows large brand owners to think and act with the agility of a startup.

The company is keen to introduce automation into other areas of its research, such as qualitative work enablingmore interviews to becarried out in peoples homes using machines.

Automation is also removing barriers internally, says Levy. The research we provide is not always as timely as marketers want it to be and we can be regarded as blockers. Automation changes this. Instead of serving as a validation function and being the policemen, we become more of a consultant, providing insight that can help to drive the business forward.

RBis now looking to upgrade its automated efforts,which will enable its brand marketers to cross-compare previous studies with new ones to reveal trends that would previously have cost too much time and money to uncover.

For Dominic Grounsell, former global marketing director at Travelex and Marketing Society board member, it is the improved accuracy provided by automation which appeals.

I am not a fan of traditional quantitative and qualitative research methods and interviews on street corners that provide unnatural reactions when people are pressured for time, he says. Things have evolved, with tools such as neuroscience technology assessing the emotional impact of an ad or messaging.

He also points to the development of mobile phone tracking in providing more reliable analytics.

The more brands use [smartphones]to track consumer behaviour on a granular level the better answers they will get to more specific questions on where people go and how long they spend there.

Grounsell believestechnology that provides retailers with real-time location-based behavioural data about consumers, will be a huge help to marketers going forward.You can actually see people walking into a restaurant or a retailer, which provides a greater understanding of footfall, he says.

It is the ability to understandconsumerreactions in the momentthat prompted theNational Association for Stock Car Auto Racing (NASCAR) to beginconducting real-time fan research during races, enabling it to improve the experience for viewers and advertisers.

The organisation,which sanctions more than 1,200 races across the US, Canada, Mexico and Europe,understood thatpeople watch with their friends, chat about the races on social media and engaging with sponsorswhile drivers battle it out but neededto be part of the conversation in order to learn from it.

Working withmachine learning platform Remesh,NASCAR has been able to engage hundreds of thousands of fanssimultaneously to drive research.It works by a single moderator asking an open-ended question about a specific moment to the entire community but results in members of the fan council responding individually, providing qualitative data that NASCAR can then analyse.

People are complex, and to capture this complexity you need a human element.

Fans are asked for their views on which manufacturer has the most attractive car, what they think about the companies advertising and how they rate the race on a scale of one to10.

While some of the techniques outlined above are new, many brands have been using aspectsof automation in market research for years. Transport for London (TfL), for example, started using online quantitative methods to evaluate its different marketing campaigns 13 years ago.

TfL is now employing an element of automation in its qualitative work, via online discussion forums, and it has introduced mobile apps into its ethnographic research so customers can record their own experiences in real time.

TfLs customer insight manager Ian Pring welcomes the benefits of automation but says it is not time yet to lose the human element of market research completely.

TfL isnt just about running a transport system, we are a customer service business and were aware that people dont always report their behaviour, thoughts and feelings in a straightforward way, he says. People are complex, and to capture this complexity you need a human element, not just in qualitative fieldwork but in analysis, interpretation and integration of all customer insights.

READ MORE:Rise of the machinesAre robots after your job?

In the publishing sector Trinity Mirrors groups marketing director Zoe Harris says there is an internal debate on whether the automated analytics it uses for online brands would work for its print products.

Our editor-in-chief Lloyd Embley observes that if we used the same analysis for print as we do for online we would put the crossword on the front page, says Harris. Many people turn to itfirst and its the piece of content that people spend the most time engaged with.

There is a serious point to this observation. It demonstrates how in any content-driven business the data generated must inform long-term thinking and be authentic.

If all the research was automated it would not be as genuine. One of our most traditional and trusted methods of research is our postbag, says Harris.

Automation should be viewed as just another tool we can use as we try to do more with the same research budget.

Trinity Mirror also has its10,000-strong online research community Mouthpiece, which brings together readers and web visitors from more than 20 of its national and regional news brands. This provides feedback on how the big news stories are being covered and how people are feeling about the country or politics.

The research is informing our advertisers to help them get their content right, says Harris. We have seen, for instance, a shift from a north/south divide to more of a London versus the rest of the UK split. Brands need insight into underlying trends to remain in touch with mainstream Britain.

When it comes to automated ad testing, she does worry that it hinders creativity.

Some of the best ad campaigns are the ones that initially test badly. Automation should be viewed as just another tool we can use as we try to do more with the same research budget.

The speed of change in research automation is almost as rapid as NASCAR champion Kyle Busch flying around the Kentucky Speedway track at Julys Alsco 300. However, for the immediate future at least, robots and human researchers will co-exist so that brands benefit from the accuracy and pace of using computers without losing the creativity and gut feel of a real person.

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The rise of automation in market research - Marketing Week

I love watching my son mastera LEGO set. Logic is the key ingredient in putting a set together, especially the super complexmodels that require many hours to assemble.

The LEGO company is smart. For the complex sets, the company breaks the whole into units, which are packaged to be built separately. The assembled sections are then added together to create the overall object.

The unit approach makes it much less overwhelming, while also making it easier to find the right pieces. It also helps kids realize success as each section is completed.

An added bonus is that the sections become a pathway to producing something different and creative. Many times my son has reused those units by putting togethermodules from a variety of sets to create something different and original,thereby expanding his enjoyment of the toy.

Marketing automation has a lot in common with building LEGOs. Complexmarketing automation campaigns designed and built unit by unit areeasier and more effective than anentire campaign implemented as a single unit.

From a psychological standpoint, smaller modules are easier to focus on than one large overwhelming campaign. By breaking down a campaign into small units, it becomes much easier to tackle and the focused-brain can hone in on exactly what is needed, as Eric Ravenscraft wrote in Lifehacker.

Designing modules within the marketing automation platform can lead to reuse. Different subsets can be used in different campaigns.

The units (for example a campaign flow or contact filter) can either be copied and the new version slightly updated or they can simply be used as they are. This saves time when building new campaigns.

Testing is also simplerformodularly-designed campaigns. Spotting and fixing issues at a unit level is easier than at the overall campaign level when its not clear what is causing the problem.

Optimization of a modularly-built campaign allows for the pieces to be taken apart, streamlined and put back together. Conversely, if an entire campaign is intertwined and locked tightly together, enhancing the whole is a very complex task.

A modular design allows thecampaign to launch in-market faster than acampaign designed as a single unit.

Single unit campaigns require all the content, landing pages, and emails be built before kick-off . Modularly-designed campaigns only need the initial logic flow to go to market. Additionally, if the flows are the same across buying cycles (or modules) copying them will save time.

Make each component of your marketing automation campaign a separate module. For example, each form, landing page, segment, filter, data store, field merges, dynamic content, etc. should be developed separately.

Units in a modularly-designed campaign interconnect and communicate, necessitating the use ofconsistentdata points throughout. For example, if a filter excludes one demographic by eliminating a certain value, other filters using that demographic should use theexact same value (even if the same result could be achieved a different way).

To create a campaign like a LEGO set, start at the lowest component level. Design first the data components, then the field merges, dynamic content, and forms that interface with those data components. Lastly, build out the landing pages, emails, and, finally, the campaign logic flows that use those units.

Test each unit as a single entity before incorporating it into the overall campaign. Do the same thing when the module is copied for reuse. That way you flush out any issues when its a single unit and not when there are multiple versions of it that you must chase down.

For example, when creating a landing page with a form, test that by itself first. Ensure the UI looks as expected in all browsers. Confirm the form functions as designed and that the data collected from the form saves correctly.

Once validated, test the landing page from the link in the email. Now, if something is not working, its easy to isolate the issue and resolve it beforeit has been propagated to multiple units that all need fixing.

Design each buying cycle of a campaign as a separate module. Use linkage to send contacts from one buying cycle to the next.

This makes the campaign logic easier to read when you open it back up in the future. At the same time,smaller modules are easier to reuse.

More importantly, by modularizing the buying cycle, it makes it easier to work in all the nuances of the business logic and to launch into the market sooner.

Implementing marketing automation as LEGO sets empowersyou for success, SixthDivision founderBrad Martineau explained in a podcast extolling this LEGO method. With a clear vision of the overall business need and associated strategy broken into individual components, campaigns become less overwhelming to build and simplerto put into the market.

Some opinions expressed in this article may be those of a guest author and not necessarily MarTech Today. Staff authors are listed here.

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LEGO logic rocks marketing automation - MarTech Today

AUBURNThe city's automation updates at the Lincoln Street Parking Garage are moving ahead.

Superintendent of Public Works Mike Talbot said in a presentation to the Auburn City Council Thursday that automated ticketing equipment has been installed at both the entrance and exit lanes, but the garage is still staffed with an employee in the booth until the equipment is up and running. Talbot said he expects the internet service to be installed as soon as Friday.

The automated equipment at the city parking garage's entrance has already been installed.

Additionally, the current lower level metered spots will soon utilize an automatic kiosk and 14 spots along the garage's north wall were converted to metered parking. These spots will not offer the two-hour free parking.

The DPW plans to make the garage more accessible to pedestriansby removing several panelsnear the William and Lincoln streets intersection. The city will also name the garage's four stairwells with their corresponding street namesin order to make navigating the garage easier for visitors.

After 32 years on the force, Sgt. Brian Clancy is retiring from his position with the Auburn Police Department. He was honored for his service to the city at Thursday's Auburn City Council meeting.

Auburn Police Chief Shawn Butler, Deputy Chief Roger Anthony and members of the department were present at the meeting to pay their respects to Clancy.

"You are one of the few remaining officers that will end an era within our ranks, one who leads with great knowledge and experience of a generation in the policing profession that rarely remains," Butler said on behalf of himself and Anthony.

Butler called Clancy a mentor to himself and Anthony and remembered a phrase Clancy is famous around the department for: "You got a badge, you got a gun. Figure it out."

"Many times we did," Butler continued. "But other times we knew we could count on your guidance when we could not find the answer."

Mayor Michael Quill said he and City Manager Jeff Dygert would like to bring back the tradition of honoring all retiring city employees and thanking them for their service.

"We make a big deal when we bring a new person on board, usually a swearing in," Quill said. "At the same time, we need to do something for our retiring employees who have done so much for the city."

Staff writer Natalie Brophy can be reached at (315)282-2239 or natalie.brophy@lee.net. Follow her on Twitter @brophy_natalie.

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Automation at downtown Auburn parking garage nearly complete ... - Auburn Citizen

More efficient lighting and climate control is one of several cost-saving benefits a smart building can offer your customers.

Smart buildings are on the rise around the world as companies recognize the potential cost savings of automation.

With the advent of the Internet of Things (IoT), every building with an integrated security and access control system has the capability to also integrate the buildings energy use, water use, ventilation and more.

Here are five steps to ensure successful automation of a commercial facility.

The first step is to show your customers the potential savings by conducting a thorough cost analysis. When surveying, you should look at everything from air handlers and chillers, to irrigation and what types of lighting are currently in place.

Be sure to also include details like switching to LED lighting, and updating compressors and chillers, and show the total potential cost savings. Buildings waste a lot of energy.

Simply propping a door open can cause the automation system to go into overdrive, pumping out air and creating significant energy waste. The ROI on building automation can sometimes free up money for other projects, while enhancing technology, comfort and security.

Theres an ongoing shift in the decision-making authority from facility managers to the IT leadership. This can be problematic, as many CIOs are unfamiliar with the challenges of maintaining a facilitys physical security.

Facility managers can be equally frustrated by unfamiliar IoT technology. Helping to create or improve the relationship between the CIO and the facility manager is crucial.

Educating the CIO about physical security, and bridging the knowledge gaps for the facility manager with smart device technologies will be essential as the industry moves to a more IoT-centric mindset. Providers and integrators should present themselves as a coordination point.

As with any new technology, there will be those who are hesitant to embrace the change. For instance, the IT director may have concerns about putting all their eggs in one software basket.

When a building is fully automated and networked, a failure in one area can cause failure in others. There may also be network bandwidth limitations that will have to be addressed to handle the amount of data that will becollected and shared between the various components of an automated system.

Concerns can usually be alleviated through detailed communication and concrete information about how the buildings systems can live side-by-side and how integration can benefit the customer in the long run.

The most important thing is to ensure that everyone has an opportunity to voice those concerns at the beginning.

To ensure the long-term success of a project, its crucial that the technology specified is future-forward and will flex and grow as the institution does.

The transition to new technology is never seamless, but there are solutions that can simplify the process. Look for systems and devices that are open source in nature; meaning, they can work together or can be easily integrated with each other.

Choosing proprietary versus open systems and devices could limit overall functionality and long-term adaptability.

Transitioning to a fully optimized smart building may seem overwhelming at first. It can be helpful to outline a series of goals with timeline milestones set.

60 days: Set goals for improving efficiency. Compare energy costs across multiple locations to establish a baseline of use and areas of loss/waste.

Six months: Use the data from your test location to establish an initial ROI and look for areas to further improve.

12 months: Track energy use at all locations to measure energy savings and establish overall ROI.

24 months: Develop a long-term plan for energy savings, including how to integrate new facilities into the overall solution. Experienced players in the security space understand there are no shortcuts.

The adoption of IoT technologies and tools will initially grow at the pace at which industry experts can support it. Wait too long and the space will be disrupted by external forces driven by consumer demand.

Minu Youngkin is Marketing Manager at Allegion.

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5 Steps to Successful Smart Building Automation - Security Sales & Integration

BBC News

The automation-resistant skills we should nurture BBC News In China, manufacturing businesses that fled wealthy countries to find low-wage workers are now replacing those humans with machines. And on farms around the world, automated systems are beginning to take on backbreaking tasks like weeding lettuce.

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The automation-resistant skills we should nurture - BBC News

A slip in certificate handling is one of three bugs in Cisco's Autonomic Networking software.

As its name implies, Autonomic Networking is about reducing the load on network administrators by offering self-management for suitable switches and routers under suitable versions of the IOS operating system.

And then, as they say, the murders began: Autonomous Networking uses infrastructure certificates to verify nodes in the system, and that's where the problem has emerged.

It starts with this advisory: a mistake in infrastructure certificate revocation.

In Cisco IOS XE, the bug could let an unauthenticated, remote autonomic node back into a network after its certificate has been revoked.

That's because the software doesn't transfer certificate revocation lists across Autonomic Control Plane Channels (ACP). An attacker with access to the remote node, even if its certificate has been revoked, can re-insert the revoked node into the autonomic domain.

The bug affects Release 16.x of Cisco IOS XE Software and are configured to use Autonomic Networking.

The only option for affected admins is to manually check that the bad node's certificate has been deleted properly, and then update the Autonomic Networking whitelist file.

The other Autonomic Networking bugs in the collection are an information disclosure vulnerability, and a denial-of-service vulnerability.

In the first, the information disclosure is only available to an unauthenticated, adjacent attacker to view control plane packets in clear text. So far, there's no fix available.

In the second, attackers can crash adjacent IOS and IOS XE Autonomic Networking nodes. Cisco doesn't yet know what causes the bug, but if an attacker captured packets (exploiting the information disclosure bug, for example), they can replay them to reset the ACP channel of the system. Again, users will have to keep an eye out for when a fix lands.

Sponsored: The Joy and Pain of Buying IT - Have Your Say

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Cisco bugs leave network automation vulnerable to attack - The Register

27 July 2017

Advanced technologies bring many potential advantages to manufacturers looking to improve their production processes. CTC provides the flexibility to develop bespoke systems by offering a choice of platform, programming, networks and architectures. Its Incentive Software, for instance, runs on standard PC hardware. This can be married with CTCs Series 5300 programmable automation controllers, with integrated motion, data handling and a powerful high-level language.

Designed to run on standard PC platforms, the main components in the Incentive family include:

IncentivePLC a multitasking control runtime system executing the powerful QuickBuilder automation language. IncentiveECAT a high-performance EtherCAT master controller for direct control of EtherCAT devices from standard PC hardware. IncentiveAPI a DLL (dynamic-link library) offering a high-level control API (application programming interface) for code written in C#, C++ or VB.Net.

Incentive provides users a complete solution for high-performance PC-based control of automated industrial processes, whether for standalone equipment, motion control, or plantwide control architectures, explains Gerard Bush of INMOCO.

Incentive has a real-time operating system (RTOS) that enables simultaneous operation of Windows 10 (or Windows 7) and one or more independent real-time processes. The system combines the responsiveness required of high-speed motion applications and the flexibility of a fully-featured operating system able to run vision systems, HMIs, data tracking and processing applications, and other high-level programs.

Incentive also provides data aggregation, enabling efficient interfacing with database applications. It has provision for network security and other functions necessary when transferring sensitive data.

IncentivePLC has the functionality of a programmable logic controller, so can replace hardware PLCs and create a truly open architecture.

IncentiveAPI provides an extensive API to interface your C#, C++ or VB.Net code to IncentivePLC and/or IncentiveECAT processes running either locally or remotely. In addition to supporting custom applications, this makes it easier to integrate vision systems, HMIs and other third-party subsystems into a systems control architecture.

IncentiveECAT is a powerful software-based EtherCAT master controller that works in conjunction with IncentivePLC, IncentiveAPI or indeed both simultaneously.

During initialisation, IncentiveECAT can scan the network to identify all the field devices in the system and automatically configure them for use.

The Incentive family of industrial control software joins CTCs hardware offerings, featuring the Series 5300 programmable automation controllers, panel-mountable hardware solutions for both standalone and distributed control applications. With a wide range of high-density digital, analogue and motion control modules available, and extensive data communications and networking capabilities, these systems can serve as the principal control system on even the most complex equipment designs, or as intelligent remotes.

There is a growing list of vendors devices which are compatible with the Incentive series, explains Gerard, making it possible to select the most appropriate equipment for any given duty.

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Automation software components for powerful and comprehensive control - Design Products & Applications (press release) (registration)

There are nearly 16 million people working in retail in the U.S., and its estimated that almost half could lose their jobs to robots over the next 10 years. Specifically, a new study shows that 7.5 million retail jobs are expected to become automated, and cashiers are the most likely to be affected.

However, technology is not sophisticated enough to take over positions that require high levels of customer interaction.

FierceRetail spoke with Allison Wallrapp, an attorney with Constangy, Brooks, Smith & Prophete, LLP, to gain more insight into the realities of automation for retail workers.

FierceRetail (FR): Will technology ultimately hurt the retail job force?

Allison Wallrapp (AW): Ultimately, technology and automation will reduce the number of employees necessary in the retail industry. We are already seeing robots and other technological advances reduce the need for certain positions. Given these advancements, coupled with pressures on the industry, we expect to see the retail job force decline in the coming years.

FR: Does automation also have the potential to create some jobs?

AW: We may see the creation of new analyst positions to determine whether jobs can be automated and if doing so is feasible, efficientand financially worthwhile. These positions may also include studying how consumers react to the technological changes and what exactly they are seeking from their in-store experiences.

FR: Which jobs will be most affected by automation?

AW: We are already seeing declines in the need for positions such as cashiers, stock clerks and store accountants. For example, Walmart has rolled out Cash360 machines across nearly all of its stores. These machines count eight bills per second and 3,000 coins a minute, and then digitally deposit money at the bank. The Cash360 machines are taking over the work of Walmarts store accountants, who were responsible for counting cash and tracking the accuracy of a stores books. While some of these former store accountants have been shifted into other jobs at Walmart, more than 500 people who held these positions have left the company.

FR: Which jobs will be secure?

AW: Jobs that will be most secure will be those that involve a high level of customer interaction. The current technology is not sophisticated enough to take over these positions, so individuals whose positions are customer-facing and more service-focused will be better able to weather these changes in the industry.

FR: So what are some of the possible legal ramifications that go along with automation?

AW: There is the possibility of new regulations being implemented regarding the use of automation in the retail sector. Additionally, as the use of automation percolates down to smalleremployers, a reduction in their workforcecould mean that the remaining employees are no longer covered by Title VII (which prohibits employers from discriminating against employees on the basis of sex, race, color, national origin and religion) or the Family and Medical Leave Act (which entitles eligible employees of covered employers to take unpaid, job-protected leave for specified family and medical reasons).

FR: How important is customer interaction in 2017 and how important will it be in the future?

AW: With so much shopping shifting online and so many other changes happening in the industry, the way retailers interact with customers has evolved markedly in the past few years. Digital interactions, including engaging with customers on social media and via mobile applications, are allowing retailers to continue conversations with customers long after they have left the store or start ones if a customer has never stepped foot in one of their brick-and-mortar locations. However, as far as in-store interaction, savvy retailers know that customers will be seeking out that which they cannot get onlineone-on-one service from well-trained human associates and immediate access to goods.

FR: What should retailers keep in mind as they prepare their workforce and technology for the future of retail?

AW: Retailers should keep in mind that technology can eliminate or reduce the need for employees to perform mundane tasks, which can allow associates to create a more personalized shopping experience for consumers. They should look to see how technology is able to facilitate or enhance a human connection in their physical stores and provide training to their associates in order to maximize this. Additionally, retailers should remember to keep the concept of digital parity, which is the consumers desire for an in-store shopping experience that is as convenient and seamless as what they can find online, at the forefront of their minds when providing training and creating incentives for their employees.

Read more from the original source:

Retail jobs in the face of automation - Fierce (registration)