Category Archives: Automation

Lease abstraction is one of the biggest administrative burdens in retail leasing. The manual processing of entering key data points from leases is a pain point for any company managing a significant number of leases. So the team at LeaseInfo has created the perfect solution with automation.Its been in the market for more than a year and some early adopters have taken advantage of the new technology.

Accurait, is a cloud-based platform revolutionising the automation of lease abstraction. It converts a normal PDF lease into structured and meaningful insights by creating a data repository for portfolio management, lease audit, analysis and financial standards compliance.

Accurait was created by LeaseInfo, the largest retail leasing data provider in Australia. They understand the burden lease abstraction can have on a business, having spent the past 15 years extracting key data from thousands of lease contracts each year.

Along with CSIROs Data61, one of the worlds most respected data research agencies, the challenge of creating Accurait was coming up with a digitisation and extraction solution that could cater for the large range of contracts in Australia that differ in their structural complexity from overseas. This is why international software cant be used straight out of the box here in Australia.

Accurait uses Artificial Intelligenceto scan through each lease and extract the information needed such as the base rent, rent increases and key dates. It uses a suite of machine learning technologies to allow the system to continually learn with each contract the system sees. This means Accurait will only become more and more powerful over time.

Put simply, Accurait works by feeding a lease contract into the cloud-based, secure system, then in just a few seconds Accurait will show you an extraction of key data points for you to quickly audit and approve. It is then exportable to Excel, CSV or to a portfolio management system, like LeaseInfos My Portfolio.

Lease abstraction isnt the only thing Accurait can do. Built in are features like Advance Search, allowing you to search your entire portfolio for key clauses; bulk upload lets you load multiple leases at once; document search which gives you the ability to tag entire clauses throughout all your leases; calendar reminders of important dates; estimate rent and marketing levy; and document compare which gives you the ability to compare two similar documents to check for changes.

Accurait is currently being used by landlords, retailers, government agencies and organisations with large portfolios of leases. All are claiming to have improved efficiency and saved thousands of dollars in processing errors.

One early adopter of Accurait, Swarovski say they save 2,000 hours over the life of a lease contract, because they dont have to spend the usual six hours to reread the contract each time it needs to be consulted. All key data and clauses are captured and cataloged in Accurait for the life of the lease and beyond.

Swarovski say, We anticipate Accurait could save us in excess of $100,000 per year in terms of increased productivity, reduction in additional labour, legal and accounting costs and savings in rent from processing errors.

Michael Miller, Director NSW Small Business Commission says Accurait is an innovative tool that will help us to quickly deliver insights into our landlord and tenant clients and thereby deliver how we may better serve their needs.

CEO and Co-Founder of Panthera Property Group says Panthera Group have been an early adaptor of Accurait. It created efficiencies in our Retail Asset Management Platform. We use Accurait for due diligence of other shopping centres to check passing rent, produce future cashflow reports and diarise critical dates. It is a part of our ongoing strategy to be a market leader in the adaptation of technology for the shopping centre industry.

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Accurait is revolutionising the automation of lease abstraction - Belinda Daly

DUBLIN, March 5, 2020 /PRNewswire/ -- The "Automated Material Handling (AMH) Market - Growth, Trends, and Forecast (2020 - 2025)" report has been added to ResearchAndMarkets.com's offering.

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In 2019, the automated material handling market was valued at USD 6.42 billion and is expected to reach a value of USD 10.96 billion by 2025, registering a CAGR of about 11.3%, over the forecast period 2020-2025.

The Census of Fatal Occupational Injuries, which has been conducted under the U.S. Bureau of Labor Statistics, has established that workplace injuries have decreased by 25% in 10 years, due to the advent of various technologies in the workplace. This helps in boosting the automated material handling market.

Key Highlights

Major Market Trends

Airport Developments to Significantly Drive the Market Growth

Asia-Pacific to Witness the Fastest Growth

Competitive Landscape

The automated material handling market is fragmented and highly competitive in nature. Some of the major players are Daifuku Co, BEUMER Group, Siemens, JBT Corporation, Honeywell Intelligrated amongst others. Product launches, high expense on research and development, partnerships and acquisitions, etc. are the prime growth strategies adopted by these companies to sustain the intense competition.

Some of the recent developments are:

Key Topics Covered

1. INTRODUCTION1.1 Study Assumptions and Market Definition1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET INSIGHTS4.1 Market Overview4.2 Industry Value Chain Analysis4.3 Industry Attractiveness - Porter's Five Forces Analysis4.3.1 Bargaining Power of Suppliers4.3.2 Bargaining Power of Buyers4.3.3 Threat of New Entrants4.3.4 Intensity of Competitive Rivalry4.3.5 Threat of Substitutes

5. MARKET DYNAMICS5.1 Market Drivers5.1.1 Increasing Technological Advancements Aiding Market Growth5.1.2 Industry 4.0 Investments Driving the Demand for Automation and Material Handling5.1.3 Rapid Growth of E-Commerce5.2 Market Restraints5.2.1 High Initial Costs5.2.2 Unavailability for Skilled Workforce

6. SEGMENTATION - BY PRODUCT TYPE6.1 Hardware6.2 Software6.3 Services

7. SEGMENTATION - BY EQUIPMENT TYPE7.1 Mobile Robots7.1.1 Automated Guided Vehicle (AGV)7.1.1.1 Automated Forklift7.1.1.2 Automated Tow/Tractor/Tug7.1.1.3 Unit Load7.1.1.4 Assembly Line7.1.1.5 Special Purpose7.1.2 Autonomous Mobile Robots (AMR)7.1.3 Laser Guided Vehicle7.2 Automated Storage and Retrieval System (ASRS)7.2.1 Fixed Aisle (Stacker Crane + Shuttle System)7.2.2 Carousel (Horizontal Carousel +Vertical Carousel)7.2.3 Vertical Lift Module7.3 Automated Conveyor7.3.1 Belt7.3.2 Roller7.3.3 Pallet7.3.4 Overhead7.4 Palletizer7.4.1 Conventional (High Level + Low Level)7.4.2 Robotic7.5 Sortation System

8. SEGMENTATION - BY REGION8.1 North America8.2 Europe8.3 Asia-Pacific8.4 Latin America8.5 Middle East & Africa

9. KEY VENDOR PROFILES9.1 Daifuku Co. Ltd.9.2 Kardex Group9.3 KION Group9.4 JBT Corporation9.5 Jungheinrich AG9.6 TGW Logistics Group GmbH9.7 SSI Schaefer AG9.8 KNAPP AG9.9 Mecalux S.A.9.10 System Logistics9.11 Viastore Systems GmbH9.12 BEUMER Group GmbH & Co. KG9.13 Interroll Group9.14 WITRON Logistik9.15 Dearborn Mid-West Company9.16 KUKA AG9.17 Honeywell Intelligrated9.18 Murata Machinery Ltd.9.19 Toyota Industries Corporation

10. INVESTMENT ANALYSIS

11. FUTURE OF THE MARKET

Story continues

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Automated Material Handling (AMH) Market, Forecast to 2025 - Daifuku, BEUMER Group, Siemens, JBT, and Honeywell Intelligrated are Dominating - Yahoo...

International Data Corporation (IDC) the premier global market intelligence firm, predicts that between 2018 and 2021, companies worldwide will have collectively spent nearly $6trn on digital transformation initiatives. And, according to Krishnan Ramanujam, president of business and technology services for Tata Consultancy Services (TCS), a global IT services, consulting, and business solutions organisation: CFOs, along with their counterparts in strategy and technology, can play a major role in determining which models may be economically viable for their firms, now and in the future.

CFOs will have numerous sizable internal funding requests fall on their desks and they cant be blamed for playing the devils advocate since they argue to help determine the validity of any digital transformation project. But their primary role as a digital CFO will be transforming their own department.

According to AccenturesFinance 2020report, automation will eliminate up to 40 percent of the transactional accounting work the finance department does today.Terry Walby, founder of Thoughtonomy, a software company with multi-award winning automation technology platform, reiterates the CFOs critical approach: As the project sponsor, the CFO needs to be comfortable building a business case, willing to take input from other departments and to spend the time to fully understand processes at a granular level.

A study undertaken by Compleat How tech is changing the role of finance, found that 51 percent of workers within UK businesses have rushed to implement new financial technology in the past couple of years, citing the UK Governments Making Tax Digital (MTD) initiative as a key driver.

Researchers at Gartner conducted interviews with 150+ corporate controllers, chief accounting officers, and chief accounting leaders to study about the benefits automation could pose for businesses. One of the highlights from the study was that the average amount of avoidable rework in accounting departments can take up to 30 percent of a full-time employees time. If fully implemented, automation can save upward of 25,000 hours per year and close to 675,000.

According to The dawn of a new partnership: A robotics-led finance function by EY, automating manual processes with little subjective judgment like data input and output, reconciliation, data quality management, reporting, and dashboard and business rules can reduce man-hours between 20 percent-80 percent.

The use of automation in finance can drive efficiencies by reducing human error. It helps in freeing up the finance team to refocus on more strategic work. By using automation, the finance function can accurately forecast, which means that the business can make more real-time decisions as opposed to just playing catch-up. The CFO can start to get more predictions from the accounting department and that can result in better business outcomes.

Back in 2018, Spanish football club RCD Espanyol automated its financial processes and according to their finance director Joan Fit: The finance team has become infinitely more flexible since making use of the automation features, with productivity going up by more than 20 percent, reporting time reduced by 50 percent and errors reduced by over 25 percent. The team can instead focus on using Club information, analysing it in real-time to become more strategic in its effort to become a globally-recognised name in the world of football.

Tim Leger, SVP business process automation and transformation at Sutherland Global Services said in an article on Financial Director: The future of digital finance is intelligent automation and RPA is yesterdays news. As organisations have embraced robotic process automation (RPA), it has become a single, commodity tool in the larger automation toolbox no longer at the centre of transformation and synonymous with process automation.

It is difficult to associate a cost in terms of price for finance function automation. It depends on the kind of project, the scale of it, size of the company and several other factors. Understanding and explaining the actual costs associated with deploying finance automation are tough since they are quite different from an industrial robot.

According to a blog on DocuPhase, business automation tools can start at 23 a month for 0-10 employees, and rise from there. Typically, automation in the finance function starts from accounting tasks. This article in Accountancy Age gives a good idea of the pricing of the best online accounting software in the UK. Business analysis tools, such as ActiveOps, StereoLOGIC or Celonis compare the short-term costs of using automation over the next two to five years versus a finance software tool.

However, the real cost of automation in the finance function is beyond the project implementation cost and the price of the software or the technology. Here are considerations that CFOs must make while deciding on implementing automation projects.

As in accounting terms, make or buy analysis needs to be conducted to check the feasibility of both making an automation software in-housing or buying/getting it developed from external providers. The analysis will help in highlighting the costs and benefits associated with either of the decision.

The success of the automation initiative depends on its integration with existing business applications and hardware.

Keeping business continuity in mind, the implementation of the automation project needs to consider the current and the proposed architecture, hardware and IT infrastructure on priority. Over dependencies on the current set up can create an outage that can have a significant business impact post-implementation.

While its easy to get caught up focusing on the commercial rationale, the success of the automation project depends on the willingness and participation of the staff involved not just in its implementation, but also in using it.

Another outcome of automation, which might be a potential notional cost at least for the CFOs, is the perceived threat of machine taking over humans. CFOs, as leaders of the finance function, need to keep viable streams ready to deploy the members of the team whose tasks have been cut short. Automation will inevitably lead to changes in organisational structures and redefined roles, if not layoffs. Amazon recently said it would spend close to 540m ($700m) to retrain 100,000 employees to perform new jobs made possible by AI and robots.

CFOs could come up with plans like financial planning and analysis personnel getting deployed to support the business closely than before and tax specialists refocusing to maximize after-tax income for the business.

Automated processes require oversight to make sure they are operating properly. Hence monitoring is necessary to make sure that the process is being operated and yielding results as per its objectives. Automation software is like middleware in the sense that someone needs to support and maintain the programs on an ongoing basis.

The cost of upgrading the automation software must be considered specifically, for regression testing and possibly re-implementing required to take advantage of new features or changes in features.

Automation, once up and running can appear magical. But, just like the magic shows seen on stage, theres more to it than what meets the eye. Automation software are typically rule-based systems that need creating rules, basically if statements, that are fed and followed.

It is vital to accept that automation cant handle irregular or highly complex processes, make decisions, fix broken processes, self-correct, and thus cant replace the human team. When businesses attribute the abilities of automation to magic, the spell can soon break down.

Andrew Spanyi, the author of four books on process management, says: RPA does not redesign anything. It doesnt ask whether we need to do this activity at all. It operates at the task level and not the end-to-end process level.

The adoption of emerging technologies like automation in the finance function during the next decade is going to change the role of the CFO. As per Accentures estimates based on insights from market analysis, cross-functional integrated teams will deliver 80 percent of traditional finance services.

As a business case to CFOs, automation contributes to both, the top as well the bottom line by not only replacing time-intensive, low-value and backward-looking accounting tasks but also enabling finance teams to spend more of their time on high-value, forward-looking business building and in-turn making them companys most important competitive advantages.

By saying yes to automation, CFOs can position the finance function as a strategic partner and in turn secure their own positions on the board and get closer to the CEO. But they deserve to be provided with a strong business case.

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Cost of automation for the cynical CFO - Financial Director

Automation has become the new buzzword for the world today, doling out hope to millions across the world that many mundane tasks can be done through machines or algorithms.

In such a scenario, Artificial Intelligence (AI)-driven startup, AntWorks, wants to redefine the world of automation where there is a definite business outcome. That is not all. It also passes the ethics test.

AntWorks, the Singapore-headquartered AI startup in the space of robotic process automation (RPA), was founded by Asheesh Mehra and Govind Sandhu in 2015. With over three-fourth of its employees based out of India, AntWorks believes its time has come. Time to showcase to the world the technology prowess it has built and which is aligned with the needs of business.

Asheesh and Govind come with long experience of working with business process management (BPM), popularly known as the BPO industry. They had early interaction with RPA but felt there were many gaps which were unaddressed.

Asheesh Mehra, co-founder & Group CEO, AntWorks Group

For the first three years, AntWorks was working on a parallel mode where, on the one hand, it was engaged with clients to provide automation services, and on the other, it was building its own technology engine.

According to Asheesh, the biggest challenge that all the RPA companies were facing was that they were coming out with automation solutions without tackling the fundamental issue of how to deal with data.

The existing technology framework which was used to read various patterns of data was optical character recognition (OCR) but it had its own limitations as it could not go through complex maze of information. Enterprises generally have 85 percent of information passing through them which is unstructured.

The co-founder of AntWorks also claims that if one talks to 100 RPA users, it boils down to a situation where 95 percent of them have not seen any of their business cases being solved.

Having built this data engine based on fractal science, AntWorks was able to create a pattern recognition whereby enterprises and business could more accurately automate their tasks and have the desired outcome.

Towards this end, AntWorks created its own technology platform which does the task of RPA while giving the flexibility to the customers on how they would like to use it.

To use our platform, one does not have to be a data scientist or need any specialised coding skills. We have a drag-and-drop environment to create the bots for automation tasks, says Asheesh.

The platform built by AntWorks is for consumption of business analysts. We have created an integrated automation platform where it can solve business cases of our customers, says Asheesh.

It was also observed in the RPA industry that a vast majority of the projects have not scaled beyond a point and AntWorks spent a lot of time in 2019 to educate the marketplace about its platform. It also impressed upon the various global analyst bodies on the skills it possesses.

Currently, AntWorks clientele is broad-based and spread across various geographies like North America, Europe, and Asia Pacific. In India, five of the top 10 banks are engaged with it.

Though AntWorks has dominant focus on the various segments of Banking, Financial Services and Insurance (BFSI) industry, it has got its presence in other areas such as retail, healthcare, telco, and advertising, as well.

This is because it not only provides multiple positive outcomes such as increased productivity, lower costs, and competitive edge, but also frees up the time of the enterprises who can actively look at other market opportunities. All this is being done at a high speed because AntWorks is able to process the data faster to feed its automation engine.

However, Asheesh admits that they have had multiple failures and successes which have kept them grounded and helped them in having an open mind to learning new things.

AntWorks is very clear on how its technology platform is used as it believes that AI should be delivered for good results. AI can be used for malicious purpose, so we go through very stringent deal qualification process with our clients, says Asheesh. Our technology is 100 percent transparent, auditable and everything can be traced back, he remarks.

AntWorks currently has over 650 people with around 430 based at its three centres in India Bengaluru, Chennai, and Mumbai. Besides, it has offices across the globe.

This startup first raised its series A round of funding of $15 million (Rs 105 crore approx) in 2018 from SBI Holdings, Japan. It plans to go for its second round during the course of this year.

Though bootstrapped in its initial years, AntWorks generated enough revenue which provided the resources to reinvest in its business. AntWorks is confident of recording a growth rate in the range of 300-400 percent for FY20, as the fundamental blocks are in place. It also aims to be profitable by 2022.

The co-founder of AntWorks believes in taking everybody along as part of their growth journey as, he says, the startup provides employee stock option even to the lowest level of its employees.

Nobody tells you how hard entrepreneurial journey is as one has to make a lot of sacrifices. It is like going through a sauna, sweating day and night. Outcome has been great for us, says Asheesh.

(Edited by Javed Gaihlot)

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AntWorks wants to reimagine the fundamentals of robotic process automation - YourStory

The jobs of the future are highly technology intensive and the combined effort of governments and international organisations must pick up pace to upgrade workers skills, according to one economic research analyst at analytics firm GlobalData.

Kausani Basak, analyst at Global Data says up-skilling workforces is crucial to arrest job losses due to automation across the ASEAN region.

If left unchecked, it has the potential to create severe macroeconomic imbalances, creating both supply and demand chain disruptions, says Baska.

In the high growth ASEAN countries - Cambodia, Indonesia, the Philippines, Thailand and Vietnam - more than 50% jobs are vulnerable due to automation in the long run, and as a result, up-skilling the workforce becomes a pre-requisite for strong, sustained and balanced growth of the economy.

GlobalData says the traditional educational and training institutes are yet to adopt according to the changing times, leading to a huge skill mismatch in these countries, and consequently, the structural unemployment in countries such as Cambodia, Indonesia and Vietnam has been rising.

The labor market in countries such as Indonesia and Vietnam are already facing heat from high unemployment among people with basic education, says Basak.

On the other hand, these countries also have a huge working age population, thus further adding to the issues.

GlobalData says hotels and restaurants, wholesale and retail trade and construction and manufacturing are the sectors which are particularly staring at the risk of job losses due to automation.

More specifically, hundreds of thousands of sowing machine operators in Cambodias garment manufacturing, millions of shop sales assistants and office clerks in Thailand and Indonesia, respectively, are expected to experience high volume of job losses, Global Data says.

According to GlobalData, the emerging new occupations that are replacing the old ones require up-graded skills that will deepen their competencies and enhance career prospects.

GlobalData says that in the recent years, there has been a rising concern among the governments to reduce the skills mismatch and as a result they have taken some preliminary steps towards increasing the technological education penetration and re-designing the existing curriculum.

Countries such as Singapore, Thailand and Indonesia have been substantially emphasising on the skill development of workers. However, these measures are not providing enough support so as to integrate the workers into the labor force seamlessly.

Nevertheless, positive re-enforcements have started appearing in the region as multinational employers are driving the up-skilling and training initiatives. In November 2018, the World Economic Forum along with top tech companies pledged to develop technological skills for the employees of the ASEAN countries by 2020 through ASEAN Digital Skills Vision 2020.

As of August 2019, more than US$4.4m was raised for providing scholarships to tech students and about 9 million SME workers were trained across the ASEAN.

In March 2019, JP Morgan announced plans to invest US$350m for a period of five years worldwide to up-skill employees. In October 2019, Microsoft announced partnership with Grab and universities in South East Asia to facilitate industry relevant technological learning through hackathons and internships, GlobalData concludes.

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Need to upgrade worker skills to cope with automation, tech intensive jobs of future, says analyst - iTWire

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Over the years, much has been written about how to structure a PPC campaign for maximum performance.

When I was recently asked to lead a panel on the topic, I covered some of the classic structures like single keyword ad groups, single product ad groups, etc.

But now that automation in PPC is much more prevalent, what are some new considerations for the perfect structure?

Maintaining a consistent structure has always been important to:

But where humans can usually figure out where to find things in an inconsistent structure, the machines may have a much harder time.

Heres an example.

One of our clients was using a combination of a few automations:

One day, they noticed their budgets had been exceeded for Nissan vehicles.

After investigating, we found that the feed with inventory was sometimes putting the word Nissan in all caps and sometimes not.

As a result, the automation that created the campaigns had started creating two Nissan campaigns as you can see in the image below.

Automation can be broken when there are inconsistencies in account structure, like in this example where words are sometimes capitalized in different ways.

The automation that checks budgets had been set up to expect the brand to be proper cased: Nissan and so the campaign with upper casing NISSAN was causing extra budget to be spent.

Fixing this wasnt rocket science but the issue could have been prevented if naming conventions had been more consistent.

When things are automated, the risk is that humans pay less attention and dont catch simple mistakes like this before they cause an issue.

In other words, the problem is more likely to be discovered after it has caused overspend.

Whereas, in the past when campaigns were manually built, this issue would probably have been noticed by a person while they were creating the campaign by hand.

Taking a small detour from account structure, the previous example highlights another interesting aspect of modern PPC.

Multiple automations are necessary to get the best results.

While I described the three automations that worked hand in hand to turn product data into a budget controlled set of campaigns, I didnt cover the fourth automation, the one that flagged the issue.

This automation monitors anomalies in costs. When a secondary campaign for Nissan vehicles was created with its own budget, costs rose dramatically from one day to the next.

This can be flagged automatically by an alert or script so that the human account manager can investigate what may be amiss.

As we deploy more automations that manage our PPC, its important to also have more automations that monitor what is happening and keep us abreast of the status.

This concept of automation layering is also evident in the following example of an automation that Google doesnt allow advertisers to turn off: close variants.

As we all know, close variants mean that exact match keywords may now trigger ads for queries that are different from the keyword, so long as Googles machine learning brain deems them to mean more or less the same thing.

While this can be helpful to discover new traffic and build more volume, its dangerous to run an account on autopilot in a world of close variants.

We either need to spend our time manually reviewing and vetting close variants or we should deploy automations that ensure they dont drag down our performance.

Human management of close variant queries basically just means more time doing query management. One of my previous scripts can help you more quickly see the performance of the keyword and its related close variants side by side.

Staying on top of close variants in an automated fashion can take one of many forms.

For instance, we can rely on Smart Bidding to ensure that if there is a lower-performing close variant, it will automatically get a lower bid so we still meet our target CPA or ROAS.

As an example, if the more commercially oriented keyword floral arrangement all of a sudden starts to trigger ads for the close variant arranging flowers which is less commercial in nature (and may be used by someone looking to learn how to arrange flowers), then Smart Bidding would set a lower bid.

Some of the close variants may have a similar meaning but have a different level of commerciality, requiring different bids to perform at the needed level.

In another form of automation layering with close variants, we could:

Getting back to account structure, there is a misconception that warrants addressing.

Advertisers sometimes change their account structure in the hopes of getting better performance after enabling automated bidding.

The idea is that Googles machine learning will learn faster if the account structure is made less complex (i.e., keywords are combined into fewer ad groups and fewer campaigns).

It turns out that this restructuring is entirely unnecessary.

The simple explanation is that Googles machine learning learns from every single query.

It uses the many signals (like time of day, device, user signals, etc.) to help it predict the likelihood that a particular query will lead to a specific conversion.

As you can probably guess, its the way youve set up conversions that matters much more.

It shouldnt be surprising to advertisers that Google even uses data from campaigns where you dont have automated bidding enabled to help its system learn.

Thats why its possible to turn Smart Bidding on and instantly get decent results because the machine has already learned what to expect from historical performance.

Theres nothing inherent in changing the account structure that helps the machine learn so if you see better performance after simplifying account structure, consider it may actually be due to another reason, such as:

On the point of seeing better results because your data is less granular, this points to a common human error in analyzing data.

When you have one ad group that used to get three conversions in a month and then goes to two conversions the next month, thats a big jump that will cause a big shift in the CPA.

But if you blend those numbers into all the data of the account where you have hundreds of conversions, that small change of 1 conversion in one ad group wont show up as quite such a significant change.

Google knows that advertisers sometimes assign too much weight to these small absolute changes that are actually small relative changes to the broader account.

But smart advertisers shouldnt need to put on blinders and create a simpler structure when all it takes to see the real results is to

So if you dont have to restructure things to make automated bidding work better, then what is the right structure?

Just as its always been, this depends on your business.

For example, your budgets may dictate that you have to run different campaigns for different business lines. Or your profitability goals may require you to have several campaigns, each with a different target ROAS.

If you need a refresher on the right tROAS to hit break-even on a Google Ads campaign, heres a graphic that shows how to calculate it.

So if you sell many products or have multiple services with different levels of profitability, youll need multiple campaigns, each with their own targets.

Even if you run Smart Shopping campaigns, Googles fully automated shopping ads, it still makes sense to have a few campaigns with different targets.

I see many accounts where advertisers split campaigns by match type, device, region, etc.

These strategies all have their merits and the key point is that if its worked for you so far, you dont need to change it just because you want to start automating bids with Smart Bidding.

And this leads us into a final point related to structure.

If were going to have different campaigns for different target CPA or ROAS, why is it that Google says we shouldnt change the target more than 20% at a time?

If the point of our structure is to support business goals, and if our business goal all of a sudden requires a drastically different target, perhaps due to a big sale, why shouldnt we set the values we need.

To me, this didnt make sense for a long time because Googles machine learning works to predict conversion rates or conversion values for each click.

Why would changing the tCPA all of a sudden interfere with that?

The answer is that it doesnt.

However, what does happen is that a new target changes the CPCs that go into the auction.

And when an advertiser starts to bid more, they become eligible to show ads for queries that they may not have shown up for before.

The query mix changes!

And changes in query mix can be really difficult to analyze.

The specific problem in the case of a different query mix as a result of a big change in tCPA or tROAS is that new queries may perform very differently from the ones youve always appeared for.

This can change the overall result of the campaign and cause advertisers to perceive the system as being broken.

Its not actually broken, because if you analyze the queries you already appeared on before, those will most likely still be performing consistently.

Its the new queries that have shifted the averages and make it seem like the systems performance is different.

Aggressive query management through automation layering as described before can provide the answer in this case.

You can set the new target CPA your business really needs while using automated query management to keep the query mix relatively close to what it was before.

Advertisers need to be aware of some of the pitfalls of automation so that they dont make decisions based on incomplete information.

Automation has caused account managers to be more likely to see mistakes in consistent structures after something has gone wrong rather than at the time the structure was created and before it caused an issue.

This can be fixed with better alerting, monitoring and auditing.

Automation doesnt require simpler account structures. We still need to run the structures that make sense for our business.

If anything, we should devote more time to measuring conversions correctly rather than wrangling account structures into some weird shape we think will help the machines.

And finally, as we need to do more work to keep automation from the engines in check, we should consider how scripts, tools, and other automations that we control can help us offload some of that manual work so we can remain most active in what we do best being strategic.

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How to Structure a PPC Campaign in the Age of Automation - Search Engine Journal

The global industrial wireless automation market is poised to grow by USD 2.03 billion during 2020-2024, progressing at a CAGR of over 7% during the forecast period. Request free sample pages

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Technavio has announced its latest market research report titled Global Industrial Wireless Automation Market2020-2024 (Graphic: Business Wire)

Read the 120-page report with TOC on "Industrial Wireless Automation Market Analysis Report by Solution (Field instrument and Communication network), End-user (Process industry and Discrete industry), Geographic segmentation (North America, APAC, Europe, South America, and MEA), and the Segment Forecasts, 2020-2024".

https://www.technavio.com/report/industrial-wireless-automation-market-industry-analysis

The market is driven by the growing adoption of high-speed communication network solutions for fast data transfer in the industrial sector. In addition, the increasing focus on predictive maintenance is anticipated to boost the growth of the industrial wireless automation market.

The evolution phase of communication protocols has led to an increase in bandwidth and advancements in related devices such as connectors and cables. Some of the major wireless communication network solutions used to transfer data include wireless highway addressable remote transducer (HART) protocol, ISA100.11a, WLAN, RFID, and Bluetooth. These wireless solutions are gaining prominence because they offer varied advantages. For instance, an industrial wireless automation solution such as Wireless HART not only supports energy management, process monitoring, regulatory compliance, and environmental monitoring but also ensures data protection. Thus, the growing adoption of high-speed communication network solutions for fast data transfer in the industrial sector is expected to drive market growth during the forecast period.

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Major Five Industrial Wireless Automation Market Companies:

ABB Ltd.

ABB Ltd. is headquartered in Ireland and operates the business under various segments such as Electrification Products, Robotics and Motion, and Industrial Automation. The company offers Industrial wireless automation solutions.

Cisco Systems Inc.

Cisco Systems Inc. offers products through the following business units: Product and Service. The company offers Cisco Connected Factory Wireless, which enables plantwide communications between machines, databases, and people on the plant floor.

Emerson Electric Co.

Emerson Electric Co. operates under various business segments, namely Automation Solutions, Climate Technologies, and Tools & Home Products. The company offers Wireless Network, Wireless Analytics, Wireless Power, and Others.

General Electric Co.

General Electric Co. offers products through the following business segments: Power, Renewable Energy, Aviation, Oil & Gas, Healthcare, and Others. The company offers industrial wireless automation solutions that include wireless radios for unlicensed and licensed narrowband communication, industrial 2G, 3G, and 4G LTE cellular routers and gateways.

Honeywell International Inc.

Honeywell International Inc. offers products through the following business segments: Aerospace, Honeywell Building Technologies, Performance Materials and Technologies, and Safety and Productivity Solutions. The company offers industrial wireless automation solutions called OneWireless Solutions.

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Industrial Wireless Automation Market Solution Outlook (Revenue, USD Billion, 2020-2024)

Field instrument

Communication network

Industrial Wireless Automation Market End-user Outlook (Revenue, USD Billion, 2020-2024)

Process industry

Discrete industry

Industrial Wireless Automation Market Geographic Outlook (Revenue, USD Billion, 2020-2024)

North America

APAC

Europe

South America

MEA

Technavios sample reports are free of charge and contain multiple sections of the report, such as the market size and forecast, drivers, challenges, trends, and more. Request a free sample report

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Read more:

Global Industrial Wireless Automation Market 2020-2024 | Evolving Opportunities with ABB Ltd. and Cisco Systems Inc. | Technavio - Yahoo Finance

Artificial intelligence (AI) and automation are terms that are frequently and incorrectly used interchangeably. Automation is a system of operating or controlling a process to accomplish tasks with little or no need for human intervention. AI is a horizontal technology that learns and mimics human intelligence over time by analyzing patterns in data. Sometimes the rules that drive automation are preprogrammed, and other times those rules are deduced by AI.

This muddying of the waters can have the negative effect of deterring many small and medium businesses from implementing automation (the importance of which I discussed in my previous article) because they believe their operations arent quite ready for this level of technology. They may be right, but only partially. While they may not be ready for AI, there are few businesses that would not benefit from some type of automation.

In my experience, the two most common types of automation found in enterprise IT environments are robotic process automation (RPA) and workload automation (WLA). RPA is software programmed to do basic tasks that mimic human users across applications. It is installed on the desktop and is operated directly by business users. WLA is software used to design, schedule, monitor and manage scripts and executables across the enterprise. It is installed on a companys servers and largely operated by IT users.

They are complementary solutions with distinctly different use cases, which means that depending on the need, many organizations might benefit from both. At their core, RPA and WLA enable businesses to focus on highest-value work, so if you are considering automation as part of your organizations digital transformation, there are several important factors to consider.

Identify exactly what headaches automation will solve for you.

Is your organization inundated with a large quantity of data that is time-intensive to organize and input? Is it eating up man-hours that could be better allocated elsewhere? If you answered yes, and there is no way to get this data programmatically, then RPA might be the appropriate remedy to your data-deluge-induced headache because data entry is what it does best. In addition to mimicking user inputs into the application user interface, RPA can also automatically download files from websites and autoformat documents.

Perhaps your organizations needs are slightly more complicated, and in addition to being inundated by data that requires filing, there are dozens, or maybe even hundreds, of processes that must be accomplished each day, often simultaneously, in order to simply function. Examples of such tasks include data processing, file transfers, service level agreement (SLA) monitoring, complex reporting, business day closing/opening process and many more. If your needs fall somewhere in this realm, WLA may be the ideal choice, potentially in addition to RPA.

Evaluate the risks.

Every process in place resists change and makes further adaptations challenging. But not all resist changes equally. Consider:

1. Manual processes resist change because people dont like to change. And the actual process being followed can be difficult to even know because the knowledge is spread among many individuals, often with no one person knowing the whole process. However, small changes tend to be adapted to easily.

2. RPA can automate the repetitive tasks of some of those people. But the specifics of what is being done continue to be hidden from the owner of the whole process. And worse than in the manual case, the RPA may fail when a small change is introduced to a website or screen that the RPA interacts with (e.g., the addition of a confirmation pop-up). Conversely, people can often easily adapt to these types of changes and recognize what needs to be done differently to keep the process working.

3. WLA resists change simply because it takes time and energy to redo steps of automation. However, in the case of WLA, the automation itself is self-documented such that you have a complete road map of your process. This makes adapting to change understandable and the timeline for doing so predictable much more so than processes run by people or robots.

I believe this distinction in risks makes WLA the compelling choice whenever possible, with RPA used for those steps that simply resist programmatic automation. When done this way, the WLA process documentation helps keep track of the RPA in use and minimizes the risk of using RPA.

Consider your budget.

Because installation and implementation are quick and easy, RPA is typically the least expensive upfront, especially if your needs are simple and you have a limited number of users. However, you will find that as your workforce and needs grow, so can the cost of RPA this in addition to the risks discussed above.

Conversely, WLA typically has a higher upfront cost due to the amount of work required to install and implement it. However, depending on the use case, WLA can end up being the least expensive option in the long run, due to its ease of scale and maintainability as your business evolves.

At the end of the day, its important to remember that automation isnt synonymous with artificial intelligence. Just because your business may not be ready for AI (and all of the expenses and intricacies that come with it), doesnt mean it isnt ready for RPA, WLA or maybe even both.

Each step you take toward automation preps more of your business to benefit from AI in the future. And by taking a proactive approach to automation, not only do you move your business forward; you can help keep it from sliding further into the traps of unknown and hidden processes.

Link:

How To Choose Automation That's Best For Your Business - Forbes

Ready Robotics cofounders Kel Guerin (left) and Ben Gibbs

Ben Gibbs was working in Johns Hopkins Universitys office for licensing and commercialization of intellectual property when he teamed up with Ph.D. robotics researcher Kel Guerin on the technology that became Ready Robotics in 2016. Their idea: Software that could power industrial robots, with an easy-to-use dashboard, enabling even small- and mid-size manufacturers to get the productivity benefit of robotic arms.

Today, the Columbus, Ohio-based company said that it had raised $23 million, led by Canaan, to expand its robotic O/S. The startup counts major manufacturers like Stanley Black & Decker and Smith+Nephew as customers, as well as smaller shops that would not otherwise be able to automate. The new funding brings Ready Robotics total investment to $42 million at a valuation that Forbes estimates at $70 million, up from $32.5 million after its last round, according to venture-capital database PitchBook.

Factories are hungry for robotic automation, but there are only 32,000 robotics engineers employed in U.S. manufacturing today and there are not enough systems integrators, Gibbs, the companys 37-year-old CEO, told Forbes. Where we are at with robotic automation today is like making you write 10,000 lines of code before you can write an article in Word. These bottlenecks are a major problem for factories that are desperate to enable automation to remain competitive.

Readys operating system, called Forge O/S, allows workers without any robotics background or coding experience to easily program the robots their plant uses. Forge O/S can plug and play with the variety of robot manufacturers. That allows plants that have a mix of, say, Kuka and Universal Robots, for different jobs to operate them through one dashboard. Forge O/S is the first operating system that allows you to operate any robot from any brand, and it does that by fixing all the complex back-end work, says Guerin, 35. The system starts at a price around $10,000 a year, and goes up from there depending on complexity and the number of robots and factories integrated.

The entire market for robots as a service, including affiliated software, is less than $1 billion out of a total robotics market around $50 billion, according to ABI Research analyst Rian Whitton. But by 2030, he figures, it could grow to more than 30% of a $521 billion market. Its quite a nascent space, he says. The hardware manufacturers like Kuka and Fanuc have their own control platforms so they dont have interoperability. What Ready Robotics is trying to do is create a common platform so it doesnt matter what robots you are using, and anyone can use the platform not just an engineer from CalTech.

The idea for Ready Robotics grew out of Guerins Ph.D. research. I was preoccupied with the idea of usability, he says. Before he finished school, he approached Johns Hopkins tech transfer office, where he met Gibbs. The two decided to team up to create their own company. I was itching to get back out into the startup world, says Gibbs, who had previously founded a company that licensed technology developed by the U.S. Navy. As is common in university spinouts, Johns Hopkins owns a small stake in the business.

Gibbs and Guerin moved operations from Baltimore to Ohio after an investment by Drive Capital, a venture firm based in Columbus thats managed by former partners of Sequoia Capital, in 2018. Sixty percent of the factories in the United States are located in the Midwest, and they buy the vast majority of the robot arms, Gibbs says.

Later that year, Ready began speaking with tools giant Stanley Black & Decker, which has built a team to scour for high-tech startups and innovations to improve operations at its 122 factories worldwide. Sudhi Bangalore, Stanley Black & Deckers vice president of Industry 4.0, says that when he began looking at ways to scale cobots, or collaborative robots, he discovered that Ready Robotics was already doing a small project with one of the companys Oregon factories. We fast-tracked the paperwork to see how they could engage with us on a few sites, Bangalore says.

In mid-December, Bangalore gave Ready the okay to launch in its Ohio factory, which makes fastening systems, telling the startup it hoped to do so in a tight timetable of four weeks, including the Christmas holidays. I was quite skeptical about how they would pull everything together, Bangalore says. Thats where they proved me wrong. When the launch proved more difficult than expected due to the plants aging infrastructure, he says, Kel came over and started designing things.

Since then, Bangalore says, Stanley Black & Decker has expanded its partnership with Ready Robotics to other factories, including a power-tools plant in Greenfield, Indiana, and is considering rolling out further among its 60-or-so U.S. factories. But big companies like Stanley test products all the time, and as the emerging robots-as-a-service field heats up, a key question for that expansion will be whether Ready can scale up at a lower cost. We pay a premium for this interface they are building, Bangalore says. It looks like the industry is catching on. So how can they evolve their value proposition?

Gibbs and Guerin believe that the emergence of inexpensive robotics and the software with which to operate them would enable automation in factories where it previously had been too costly. A McKinsey studyfound that 88% of manufacturers and other companies in heavy industry have either increased their spending on robotic automation or plan to do so. Yet getting benefit out of spending on automation has not been easy: The same McKinsey study found that only 4% of those manufacturers showed significant bottom-line improvements.

There have been all these investments in computer vision and machine learning, yet you are not seeing it live up to the hype in the industrial setting out of a few use cases, says Canaans Rayfe Gaspar-Asaoka, who led the investment in Ready. What we learned is that the software programmability of the robots is just broken.

For Canaan, the deal follows an earlier investment in retail robotics firm Berkshire Grey, which raised a whopping $263 million from investors that include SoftBank and Khosla Ventures in January.

Other investors in the Ready Robotics deal include RRE Ventures, Eniac Ventures and Drive Capital.

Read this article:

As Factories Struggle With How To Automate, Ready Robotics, Spun Out Of Johns Hopkins, Raises $23 Million For Robotic O/S - Forbes

In 2015, senior software engineer Benjamin Willenbring was excited when his employer, Autodesk, introduced automated software testing. That excitement didn't last long. The small automation team didn't communicate much with his division. And when the tests reached production, they weren't what anyone hoped for.

"My teammates were talking about tests failing non-deterministically, and not really having a lot of confidence in the test," Willenbring says. He found that "to get to actually run the test was very, very difficult. It wasn't documented. You had to talk to someone. And there were an enormous amount of files and I didn't really understand why."

Automation was supposed to make Willenbring's work easier. Instead, the problems it created came to dominate much of his energy for the next several years.

Willenbrings experience isnt uncommon. And with automation rapidly spreading through IT, cautionary tales provide valuable lessons.

From the automated workflows of DevOps to robotic process automation (RPA), automated processes aim to reduce scut work and free skilled employees for higher-level tasks. But flawed premises or botched rollouts can turn the dream of automation into a nightmare. We spoke to several IT pros about automation horror stories they've heard about or endured, and distilled out six commandments to help your automation initiatives avoid such fates.

Originally posted here:

6 tips to avoid automation disaster - CIO