Learn and Earn

By Ryan Falkenberg

South African companies need to change their approach to skills development in order to address SA’s skills crisis. Most companies approach skills development by assessing what employees need to know and then developing content to use for training. The problem with the current skills development paradigm, however, is that doing any given job isn’t about knowing things – it’s about doing things. This is the knowledge/skills conundrum.

The big challenge SA has in terms of skills development is that people need experience to develop expertise through the application of knowledge. And few young people are offered this opportunity, largely because of the risks associated with practical learning. For example, inexperienced financial sales consultants raise fiduciary risk if they offer the wrong solutions to a client; technicians raise technical and physical risk if they link the wrong wires; and call centre agents raise brand risk if they offer the wrong answers. Interestingly, most of the decisions and actions that carry this risk are defined by clear policies and procedures. The issue is therefore that people struggle to learn and apply these rules in many contexts. But, what if, rather than trying to train their brains to replicate known rules, they were offered a decision navigator to guide them?

Decision navigation is not a new concept, although, for decades, people’s ability to make it practical was limited by their decision tree or process mapping logic. This created very restrictive guides that proved impractical in jobs where context varied.

On auto-pilot

However, with the advent of multidimensional data-driven logic that is unlocking many artificial intelligence technologies, this can now become a reality. In effect, people can be offered a navigator that can work like a GPS, guiding them through every known decision and action so they get it right, every time. And as a result, the person using the navigator can learn as they go, without worrying about making a mistake.

This is very much in line with how one uses a GPS when driving. If I go to CT for the first time, I can find my way around using a GPS. I don’t need to try read a map while driving through new roads with lots of cars. My risk of a crash is high. But, if I just focus my brain on driving and allow the GPS to guide my route, my risk of error drops.

The same applies to navigating staff through new jobs. Companies can now effectively offer new financial sales consultants a navigator that will safely steer them through a sales conversation, ensuring they ask the right questions and offer the right recommendations, based on clear rules. The same applies for technicians being guided through technical diagnostics, or call centre agents being guided through customer queries. This co-pilot technology effectively liberates people to focus on the road in front, and to learn while doing, without the worry of a mistake.

Learn on the go

To break the stranglehold of the skills crisis, SA needs to get people working today – not after they’ve completed a course or dozens of courses. The only way to do it is by using technologies that help me ‘do’, not help me ‘know’.

Technologies like AI have been much vaunted as solving the skills crisis – mostly by removing humans from the equation. What offers a better alternative is technology that can augment humans. This technology falls between the traditional one-dimensional knowledge management and the fully fledged self-driving car that is AI/cognitive computing.

Using multidimensional logic platforms, navigators can be created that guide humans through tasks or actions, using the knowledge in knowledge management systems plus the information housed in cognitive computing systems – knowing at every step where the person is in the process, what they are doing, and providing them with the help they need to get it right.

This has a number of implications for businesses, but particularly from a skills perspective. It means people can be brought on board and get up and running in a role within a very short time, without the need for weeks of training.

From a risk and compliance perspective, it means every action performed has a clear audit trail, showing all of the steps taken by an employee to reach a particular action – whether that is a particular piece of financial advice offered to a client, or a procurement decision. It is all tracked and recorded, substantially reducing the risk to the organisation.

The navigator model can be applied to pretty much every area of a business where the roads (policies and procedures) are known and it’s just the routes that change based on the person’s context. This frees people to focus more of their energy on innovation, creativity and customer engagement without worrying about if they have applied required rules to known problems.

Technology can solve SA’s skills crisis, and it is not learning technology. It is performing technology that allows people to begin work today and to learn as they perform, not in order to perform.

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Artificial force for good

By Jon Pienaar

In an interview with Bloomberg two years ago, Elon Musk, South African-born Tesla CEO and billionaire founder of SpaceX, likened building artificial intelligence to “summoning the demon”. And globally acclaimed physicist Stephen Hawking has warned that it could “spell the end of the human race”.

But futurist, inventor and computer scientist Ray Kurzweil says the potential benefits of AI far outstrip the perils. In Time magazine, Kurzweil writes: “We have a moral imperative to realize this promise while controlling the peril. It won’t be the first time we’ve succeeded in doing this.”  

AI isn’t just the stuff of tomorrow, or science fiction anymore – it is likely you’ve already interacted with smart machines. If you’ve used Siri on iPhone, or OK Google on Android, then you’ve interacted with a learning machine. Similarly, spam filters are intelligent software that sorts through mail to figure out what is junk. These programs learn from user behaviour all the time.  

It is a fundamental revolution for humankind. As Andrew Ng, chief scientist at Chinese web giant Baidu puts it, “AI is the new electricity. Just as electricity, about a hundred years ago, transformed industry after industry, I think that AI is now in a position to have a similarly large impact on society.”  

ICT giants like Microsoft, Twitter, Intel, Salesforce and Apple are investing heavily in AI technology. Since 2011, according to research firm CB Insights, nearly 140 companies that have developed AI technology have been acquired as part of a race between these global corporations to own this space – 40 of these acquisitions took place in 2016. 

AI is hard at work across most sectors. Financial institutions use software to monitor market movements, while security forces use machine learning in facial recognition systems that fight terrorism. In the medical field, AI examines vast datasets to factor in genomic, phenotypic and social aspects to assist doctors with making diagnoses.

Not a robot

“When you tell people you are working on AI, they assume you are building a robot that is going to take your kids to school,” Dale Humby, chief technology officer at Nomanini, says with a chuckle. Humby is at the coalface of AI development in the field of embedded systems and micro-payments.  

He explains that commercial machine learning works with algorithms to perform specific tasks. “Like predicting what songs you might want to listen to next on Spotify, or which movie you might next find interesting
on YouTube.”    

Nomanini’s clients are all prepaid services vendors, who sell airtime and electricity tokens directly to the public. These vendors have to purchase stock in advance, so the Nomanini system can advise them how much to purchase at certain times of the month.   

“We also advise them where the hotspots are, or where they should stand to sell the most airtime or electricity, based on learning where they live,” says Humby.   

AI enables Nomanini to make personalised decisions for these vendors based on large sets of data, explains Humby. “It’s only through using computers and machine learning that we can do this in practice. There is not enough time or money to have a whole team of analysts do this manually.”

Computers deciding for you   

Humby contrasts social-media-mediated purchasing to the typical supermarket experience, where one is presented with a specific set of items to purchase, reinforced by advertising and product placement. “When you go on your Facebook, it is incredibly personalised,” he says, explaining that the Facebook back-end computers are making decisions “based on things you are going to find interesting or useful”.  

“For business this helps with client engagement – particularly if you are a consumer-based web store like takealot.com.”   

Humby says that if the AI engine shows you things that are specific to you, there is a higher likelihood that you are going to buy it.   

“It knows your demographic – for example, if you are a new mom it presents you with baby merchandise and information, rather than chainsaws.” The more data an AI system has about customers, the better it can predict their purchasing needs. “Generally you are predicting what someone’s thinking, and suggesting what they might need before they remember that they need it,” he explains.    

In the mathematical world of investing, where fast, accurate analysis is key, AI is making great progress. Magda Wierzycka is the CEO of Sygnia Asset Management, which launched a “RoboAdvisor” in May this year. The RoboAdvisor is a computer program that was installed as a back-end to a website that asks clients to input a range of information about themselves. It then provides investment advice based on an ever-fluctuating financial environment.   

“Financial planning is quantitative in nature, so there shouldn’t be any emotive judgment applied to the information given to you,” says Wierzycka. “It should be a quantitative mathematical overlay that gets supplied to the information provider that comes up with an optimal financial plan for an individual.   

“Based on the client’s inputs, and the financial planning model that underpins the website, the system calculates your net worth and projects what you will require in order to be able to retire without taking a cut in living standards,” Wierzycka explains.  

Can a RoboAdvisor do better than a human financial planner? On a basic level, Wierzycka says, it does a great job. But when it comes to issues like death and disability, the human touch is still needed. Incremental improvements are taking place all the time, and Wierzycka says that in 10 to 15 years, AI-based financial advisers will be the norm.   

Wierzycka says the financial services industry is an environment most conducive to the use of AI because machine learning allows for business functions to be done faster and cheaper.    

In the UK, the Financial Conduct Authority has encouraged people to make use of AI tools to save costs.

Intelligent adviser   

Ryan Falkenberg, the co-founder and joint CEO of Stellenbosch-based AI start-up Clevva, and his team have been working on an AI platform that is an intelligent “virtual adviser”. The machine learning being developed by Clevva aims to assist people where human error or boredom is a factor that could impact on the quality of service provision.   

“Our view is, how do we use AI to make people stronger or more effective, so that they still retain relevance – as opposed to excluding them entirely? How do we help companies leverage AI, but in a way that gets more out of people?” asks Falkenberg.  

“Most training and knowledge management is aimed at capturing process logic or sales logic,” he says. “In contact centres, this becomes formulaic.” The net effect is that these systems require people to be trained to behave like robots.  

But, he points out, the human brain is not good at memorising formulae and vast tracts of information, especially over the long term. Trainees use their short-term memory to pass the course, but generally only 20% of what is learnt is retained.  

The solution Clevva presents enables human beings to do what they are good at – engaging with the client, and putting emotional intelligence to work.   

“Innovation, creativity, human engagement – these are the types of capabilities that differentiate human beings from technology. We are on a mission to make sure human beings stay strong and relevant by enabling them with decision logic. Together humans and computers add a value that AI and computers alone would struggle to add,” he explains.  

AI is often seen as a threat to unskilled or undereducated people, but Falkenberg says an unskilled person who has good emotional intelligence, a great attitude and the right aptitude, can be teamed up with a decision-making machine that helps to solve customer queries or sell products, or even deliver services.   

He has a high-road vision in which SA’s education deficits are augmented by AI, and where people get a better shot at university and careers through supplemental machine learning.  

Let’s hope AI can help address SA’s failings and be an engine for economic growth

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Build bots to save jobs, not replace them

By Adam Oxford

There’s a lot of angst in the world at the moment. From State Capture to Trump to Brexit, lots of things are making South Africans afraid of the future.

And one of the scariest things that’s happening in the world today is the way in which AIs and bots are replacing human jobs. Automation of jobs is terrifying people smarter that us, who reckon 47% of jobs in the US are at risk of automation. 

In South Africa, where jobs are scarce enough as it is, it’s a great and largely undiscussed issue we have to face.

Ryan Falkenberg, the managing director of South Africa bot developer CLEVVA, believes that instead of focussing on the way AIs can replace humans, we should be thinking about how they can enhance and improve the humans at the business front line.

Speaking at BotCon Africa in Joburg this morning, Falkenberg explained his belief that there’s a fundamental disconnect between the way new business are developed and the way they are used. New business processes tend to based on two dimensional decision trees drawn up in Visio, when actually most problems an employee will face are much more complex and multifaceted.

The problem, he says, is that training people to follow a script or learn detailed product manuals by rote is setting people up for failure. Ultimately, it leads to information overload and over-complexity, so “it’s no wonder it looks like people are failing at simple tasks”.

The blame starts within the school system, Falkenberg says, which teaches students to repeat things rather than think creatively around problems.

There’s always a right and wrong answer, and ultimately it means everyone will get it wrong at some point and fail. He says he’s met many employees who live in perpetual fear of failure, they know that in the course of their day, they will get something wrong.

This thinking, Falkenberg believes, is pervasive in business in South Africa – particularly in businesses that employ large numbers of people who may not have received quality educations. The upshot is that people live in fear of failure, which they can’t avoid.

“We spend our lives giving people formula and then salivating at the way we can replace them with tech.”

This is true in many areas of employment, he says, but most obvious in customer service fields.

“Most orgs focus on bots in customer services space- remove the need for contact centres and retail branches. Able to do that pretty well already,” Falkenberg says, and part of this is because the solutions are being designed by the IT team and not involving HR. As result, the focus becomes on systems and efficiency without ascribing any value that human interaction brings to a job.

“Data scientists don’t have to manage people, that’s not their job. Their job is to build systems.”

Falkenberg warns that once you introduce automated responses and bots into these products, the temptation for designers who don’t work with people on a daily basis to start to design humans out of the process.

The alternative that Falkenberg proposes is to use the capabilities of machine learning and chatbots to enhance people’s roles. He uses the analogy of a paper map representing old ways of training staff and a GPS-like system which helps them do their jobs and be creative. He describes this principle as building “a copilot” to make you better at your job.

In practice, it sounds like the way IBM is approaching its deployment of its Watson AI in call centres, as a way of bringing better information to human agents rather than replacing them. Falkenberg’s example is of a bank that CLEVVA has worked with which has hundreds of branches in South Africa in which the average staff member may not have progressed beyond grade 8 or matric.

CLEVVA’s answer, rather than moving to remove people out of the system, was to arm branch staff with a tablet and software which acts as an intelligent guide through normal customer processes, but allows the staff to focus their energies on providing the experience that they’re good at.

“Your job becomes to be a facilitator of awesome customer experience,” he explains. And in his experience he says that this strategy pays off. The unnamed bank, he claims, saw immediate benefits in customer satisfaction, lead generation and sales and – importantly – staff happiness too.

Is it enough to stop the bots ultimately replacing us? Who knows…

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Toss the maps. Give your staff a Navigator!

By Ryan Falkenberg

The truth is that no matter how much staff are trained in policies and procedures, they forget most of it and struggle to keep up with the constant rule changes. All the documents and process flows we capture as decision-making maps for our staff are seldom read or referred to post training.

Ever wished, instead of all this wasted effort, you could just build them a Navigator? Something that would guide them through every known situation so they always ask the right questions, offer the right answers and take the right actions even when they have forgotten everything you covered in training?

Imagine the power this would give your company and your staff! Instead of having to train everyone on the many policy and procedure rules that you want them to apply, you simply hand them your Navigator. When they are faced with a challenge, they then simply let the Navigator know what they think their challenge is, and the Navigator takes over from there.

How your Navigator could work?

Here’s an example of how this could work. A staff member is faced with a known challenge but is not sure how to firstly categorise this challenge, and secondly resolve it. So they turn to their Navigator, either via their stay on top window on their desktop or via their smartphone’s web app. The first thing the Navigator does is help them diagnose their challenge or issue, just to make sure they have got it right. Often a staff member ends up trying to fix the wrong issue simply because they misinterpreted it in the first place.

Once the challenge or issue is confirmed, the Navigator then looks to identify the right solution. This can either be a product, an action and/or a specific answer or response. It does this by asking a series of questions that looks to work out which of the possible solutions is most applicable. These questions could relate to product features or benefits; they could be different technical criteria; or they could be different policy rules. Based on the answers given, the right solution is then identified. The Navigator then looks to guide the user through any relevant process steps that they need to take, based on the solution selected.

Importantly, the Navigator remembers previous choices made and can infer selections or options based on known data. It can also automatically choose different process routes when it is aware of data that could influence route choices.

Once the user gets to their destination, the Navigator can also offer them a detailed record of the route they took, including every option chosen and every step taken.

How hard is it to build a Navigator?

The exciting thing is that with software like CLEVVA, a cloud-based platform that lets you build your own Navigator, you don’t need any coding skills to get it right. You just need to follow a few basic steps:

  • Capture all the known challenges and issues you want to support
  • Capture all the possible outcomes (destinations) a user is allowed to reach for all these challenges and issues (your products, solutions, and/or actions)
  • Capture all the factors that will influence the choice of every destination
  • (your policy rules)
  • Capture any fixed roads that you require the user to follow in reaching any specific destination (your procedures)
  • Link up any existing supporting documentation or videos that could help the user make destination and route choices along the way (your content)

Within a few days you can have a very powerful Navigator capable of guiding staff through all the decisions and actions they tend to get wrong, which create risk in your business.

Why not consider giving it a try? You have very little to lose, and a lot to gain!

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AI can enhance human skills

By Ryan Falkenberg

With the onset of increasingly specific answers to specific challenges so known and prescribed decisions and intelligent systems capable of outperforming humans in many areas, the threat of mass job loss is real. Wherever decisions and actions are guided by known and repeatable formulae, technologies can increasingly outperform people, thereby rendering them redundant.

Traditional skill development models continue to be constrained by industrial era thinking, driven mainly by the need to develop a compliant workforce. Learning methods focus heavily on the transfer of known, historical knowledge into learners’ heads, with tests merely validating the successful data transfer.

The challenge is that people often learn using short term memory, and so while they may pass the test, they tend to forget much of what is learned through lack of application. In addition, the data they are taught is changing so quickly that they soon find themselves outdated and vulnerable. As a result, they make mistakes – mistakes that artificial intelligence (AI) technology does not make.

To enable organisations to thrive within
a knowledge economy, much attention has focused on technologies and approaches that improve the capture, maintenance,
and distribution of organisational information across a diverse workforce. Vast improvements have been made in areas such as information search, content management, quality control workflows and collaboration. Yet, staff still struggle to take full advantage of all the ‘helpful’ information that is increasingly available to them.

One possible reason is that it is not more information they require. In tackling jobs that demand increasing conformity to known organisational formulae, they seek they can perform specific tasks without error. This means they are usually more interested in accessing relevant advice, not relevant information.

This requires a change in our thinking. It requires shifting our focus from the effective capture and distribution of information or single-dimensional logic to the effective capture and distribution of advisory or multi-dimensional logic. It requires us becoming less interested in offering people decision-making maps, and more excited about offering them decision-making GPSs.

Local AI platform CLEVVA was founded based on the belief that unless we can find a way of using AI to empower people, as opposed to replacing them, job losses could prove devastating, especially in developing economies.

The CLEVVA team looked at ways of capturing expert logic into decision-making GPSs (as opposed to “maps” such as documents, process flows or e-modules). These GPSs (or virtual advisors as they
call them) effectively offer people an
expert at their fingertips, able to navigate them through any known situation so
they consistently ask the right questions, identify the right answers, and take the right actions, with detailed records to prove it.

As a result, staff don’t need to know every product, policy or procedure to get working. They can rather focus their learning and efforts on areas where the formula is not as defined, such as in the area of the customer experience.

By making expertise, as opposed to simply knowledge, available to people, in realtime, it changes the role of people and the focus of training. People are no longer required to simply replicate historically

actions that are detailed in products, policies, systems and procedures – AI can handle this for them. Instead, they can be liberated to focus on shaping new thinking and offering high impact, non-formulaic customer experiences.

By using AI to augment human performance, rather than replace it, organisations will be able to achieve the consistency in execution they desire while benefiting from the creative, adaptive and innovative value of their staff – value that is currently not being unearthed simply because staff are still primarily being used to replicate known formulae. It also allows organisations to adopt AI without being compelled to fundamentally rethink their existing business models.

This form of AI is currently being used
in banks, insurers, petroleum companies, electronic distributors, and telcos – and is not only securing existing jobs, but opening up the possibility for job creation.

CLEVVA’s platform lets people easily and quickly build virtual advisors that contain all the knowledge someone like, for example,
a call centre agent, would need to handle queries. Training then becomes a matter

of teaching people excellent customer engagement, and problem-solving skills rather than reams and reams of product and processes information.

This means that people of all skill levels can become valuable resources, and lets companies onboard people quickly when they hire.

If South Africa is going to address its ongoing skills challenges, it needs to look to technology to empower people, not replace them. AI can help.

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SA artificial firms eyes world stage

By Duncan McLeod (techcentral.co.za)

A Western Cape-based company that specialises in machine learning and artificial intelligence (AI) to help companies’ call centre operations and other parts of their business be more efficient, is now eyeing global expansion.

But the aim, says co-CEO Ryan Falkenberg, is not to use AI to replace people but rather to make them more effective at what they do.

The company, Clevva, which is based on the Avontuur wine farm outside Stellenbosch, claims to be able to “clone” an organisation’s key experts, giving everyone access to their advice through software. It’s won a number of big contracts with South African clients, and has secured its first international customer, too.

“We are now looking at rolling out in the UK and Australia, with the US to follow in 12-18 months,” said Falkenberg, who started the business with his brother Dayne. The pair have bootstrapped the company and, to date, it hasn’t had to go to the market for additional funding.

In short, Clevva develops a Web-based platform that allows companies to build, manage, track and deploy their own “virtual advisers” or “bots”, which then act as online experts, helping staff or customers make the right decisions and take the right actions in line with policy and procedural rules.

In a call centre, for example, an agent would be assisted by the virtual adviser as he or she went through a call with a customer. The idea, said Falkenberg, is to capture organisational expertise rather than simple information.

“We asked, why are we trying to get people to repeat formulae that we already know? Instead of giving you a decision-making map, why don’t I give you a decision-making GPS?” he said.

“This is AI for people, not to replace you, but to assist you. If you look at our skills gap, we cannot train away our skills crisis.”

After searching internationally for a relevant technology solution and not finding one, the brothers set out to build their own.

They bought a Western Cape company called Base10, which made business software for small and medium enterprises, and, while retaining the development team, completely re-purposed it to create Clevva.

They set about building a platform that someone without coding skills could use to deploy virtual assistants in their organisations. “In AI globally, there are some mind-blowing technologies. But they’re not simple to use,” he said.

“Companies can now focus now on employing more people, giving them a virtual adviser or coach, and not worry about them making mistakes”

After 18 months of development, Clevva released the first version of its software, targeted at the sales function in organisations.

It quickly gained traction among corporate customers.

One of the country’s biggest vehicle and asset finance companies, which Falkenberg said he does not have permission to name, asked Clevva to add its technology to its contact centre to help agents handle inbound calls.

“They later purchased an enterprise licence to allow them to build virtual advisers across the organisation.”

He said Clevva can help get new call centre agents up to speed much quicker because they don’t need to learn everything about the processes and procedures upfront.

“You can on-board a contact centre agent within a week, and just teach them about excellent customer service. Previously unemployable people become employable. They might not have the knowledge immediately, but they already have great emotional intelligence [needed to be good at call centre work],” he said.

“Companies can now focus now on employing more people, giving them a virtual adviser or coach, and not worry about them making mistakes. People become assets rather than liabilities.”

“We have every intention to be known as the technology most companies use to start AI in their businesses”

The company has since moved more fully into the banking space and is now building a virtual financial adviser that can diagnose customer needs. It’s also working on a virtual human resources adviser.

Although the business is self-funded, Falkenberg said Clevva will approach venture capitalists to help it expand.

“Our aim, though, is to unlock [opportunities] as quickly as we can without needing that. We have the technology already, and we also starting to get great partners like Accenture and Singular Systems, who have the capacity to go into big clients.”

Clevva currently has eight people in its core team, though it also works with external user interface and development teams.

Falkenberg said Clevva is “dreaming big” about its global ambitions.

“We have every intention to be known as the technology most companies use to start AI in their businesses,” he said.

“We want to be the best at AI that is easy to on-board and powerful enough to handle complex data and we want to become a major player internationally.”

What skills are necessary to join the Clevva development team?

“There are courses in machine learning at universities, but what we have found in our developers is that you need a passion to become a specialist at this. You have to love this,” Falkenberg said.

“Secondly, it’s important to have the ability to handle complex logic and relationships and to think quite creatively to problem-solve what might seem like impossible data models.”

He said Clevva is hoping to kick-start a working group of people in the machine learning and AI space in South Africa so as to “share experiences and learnings and help each other become stronger”.

He hopes to have the first of these informal meet-ups by the end of August in Johannesburg and Cape Town.

“AI’s time has arrived and we now need to make it practical and workable in companies,” he said. “We need to share our learnings.”

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South Africa’s CLEVVA is making AI-powered virtual advisors a thing

By Hadlee Simons (Memeburn.com)

Artificial intelligence is impressing us more everyday, as the technology demonstrates amazing learning capabilities and flexibility. It’s not just the likes of GoogleApple and Microsoft working on AI though, as South African firm CLEVVA has a rather innovative application for the technology.

The company, founded in 2011, has crafted virtual advisors, powered by AI and used in sales fields (among others) to train and guide sales representatives.

Just how does this service work? Could the average SME easily get to grips with it? What will future of AI look like? Will it take our jobs? We interviewed CLEVVA CEO Ryan Falkenberg…

A ‘GPS’ for decisions

“A VA [virtual advisor] acts like an online expert, asking the required questions to understand the situation, and then recommending the right solution, be it a product or an action. Where an action is required, the VA can also guide the user through the steps, in line with company policies and procedures,” Falkenberg explained.

“It’s a bit like having a GPS that ensures you make the right decisions and take the right actions, without you requiring detailed knowledge or experience. And because every action and decision is recorded for compliance and reporting purposes, there is little risk to the company and the individual.”

CLEVVA is being used across many fields where staff are required to apply a known decision-making formula in a consistent way

The CEO said there are “various wizards and VA templates” for companies to use, allowing them to quickly capture sales, administrative and service expertise.

What fields were well-suited to the technology though? Falkenberg said it was ideal for helping sales staff analyse a customer’s needs (then identifying relevant products), guiding service agents through diagnostics, helping technical staff identify the root cause of problems and helping operational staff through procedure-driven matters.

“CLEVVA VAs are not effective in areas where the required logic is not known, and the business is looking for the AI technology to use machine learning to work it out for them,” Falkenberg noted.

So how many fields are using the platform?

“CLEVVA is being used across many fields where staff are required to apply a known decision-making formula in a consistent way. This includes the financial and insurance sector; call centres; government departments; technical sales and service; and any areas where compliance to policies and procedures is important.”

CLEVVA comparisons to chat bots

Of course, AI efforts have stepped up in recent months, as Google, Facebook and Microsoft experiment with chat bots. But Falkenberg explained how their offering differs from this type of technology.

“Chat bots use natural language processing to work out what you are asking for, and then try execute your request. They require you to know exactly what you want, and even then often struggle to give you the right answer, and end up frustrating you with generic responses. Some use machine learning to learn and improve, although as Microsoft found out, this can be problematic,” the CEO continued, alluding to Microsoft’s Tay chat-bot.

As the internet of things becomes more a reality, with every device connecting and sharing data, there will be more big data available for AI to leverage

“CLEVVA VAs are different. They are not assistants simply responding to your requests. They act like advisors that first analyse your request and help clarify your real issue before offering relevant solutions and actions. VA logic is structured, so you will be asked specific questions that will always lead to relevant answers and actions. This ensures consistent, compliant advice is always offered in line with defined rules.”

Current consumer-focused AI offerings also boast of the ability to learn from the user – something that CLEVVA is working on for next year.

“We are looking to apply machine learning to help optimise known logic, and to offer authors more insights into user patterns. This capability is expected to unlock during 2017. For now we want to first excel at helping companies capture and scale their required and known logic before looking to help them with their unknown logic,” the CEO explained.

The future of AI?

Are concerns about AI costing jobs legitimate though?

“Yes. Many jobs where staff add little value other than replicating known decisions and actions will be replaced by robotics. However, AI can also help people add more value,” Falkenberg elaborates.

“CLEVVA is AI for people, allowing them not to have to worry about getting known, albeit complex decisions and actions wrong, and rather focusing their efforts on adding value beyond that. For example, focusing more on the customer experience. So for us, our AI is all about making people more powerful, not more vulnerable.”

Falkenberg envisions AI becoming smarter in the future, as more devices become connected.

“As the internet of things becomes more a reality, with every device connecting and sharing data, there will be more big data available for AI to leverage. This means more will be known about you, so AI can shape your experience more effectively. Machine learning will become more effective, and will allow solutions to self correct and improve,” he elaborates.

Falkenberg says that consumer-focused online services will “feel more intuitive and responsive” to your preferences as a result of AI and machine learning.

“That said, from a business perspective, it will result in more administrative roles being made redundant as computers improve their ability to perform these functions unaided. Staff will then move more into value-adding roles where creativity, innovation and EQ differentiate.”

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Clever way to help sales staff

By Loni Prinsloo (Sunday Times)

Three SA entrepreneurs put their heads together over the past year to develop a solution to assist companies in bridging certain skills gaps while reducing time spent on training.

This resulted in a software platform dubbed CLEVVA that allows companies to capture product and technical expertise that can easily be accessed by employees and be used to sell products and service solutions.

“The problem is that employees are often overloaded with information and training requirements in today’s ever-changing working environment” said Ryan Falkenberg.“This results on people being terrified of getting things wrong at work rather than focusing on where the ‘human element’ can add value to the customer experience.

“Trying to velcro large volumes of information into people’s heads is often just overwhelming and time consuming.”

Falkenberg worked with his brother Dayne and business partner Mark Pedersen on the project, all three having run their own successful business over the years.

Ryan Falkenberg, who has his educational roots in industrial psychology, said finding appropriate solutions that could assist with South Africa’s acute skills problem was one of his big passions.

South Africa is suffering with very high unemployment rates at around 25%, and of those jobless around 75% are younger than 35.

Essentially, half of South Africa’s youth is unemployed and many refer to this group as the “lost generation”.

But Falkenberg pointed out that these youngsters were usually much more tech-savvy than any other generation, which made the CLEVVA application a suitable tool to assist them and others in bridging knowledge or skills gaps.

The CLEVVA system is able to capture and maintain sales and support information that will be at employees’ fingertips through the use of laptops, tablets or in-store touch screens all the time.

“This provides a security blanket for employees, and ensures that all variables are taken into account to provide customers with the correct information and products for their different needs,’ said Falkenberg.

CLEVVA is able to capture any company’s product features, value-add services, administrative processes and business rules, and common support challenges and solutions. This means getting the right answers in real time.

Polyflor director Tandy Spolander said her company had been using the system since March this year, finding it to be a powerful tool and an asset the business.

“Our salespeople have access to all the information that they require, and in addition to product information we are currently loading project and client information onto the system, which will significantly reduce time spent on administration.

“Also, our salespeople do not have to drag along large catalogues, but simply take an iPad with to conduct business.

“It is a new tool and there is a learning curve, but everyone loves it.

“I am sure that even my teenage daughters would be able to sell our flooring products like experts if they played around with the system for a day. This eliminates the need for us to hunt around for people with some industry knowledge when new or additional salespeople are required,” said Spolander.

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How to perform like a pro without any training

Ryan Falkenberg knows that most school leavers have little hope of getting formally employed. That’s why he developed CLEVVA, the software system that gives ordinary people the decision-making prowess of experts.

By Keith van der Linde for BusinessTrade.org

What motivated you to start CLEVVA?

My whole career has been dedicated to solving the riddle of, “How can someone who lacks knowledge or experience but who has the right attitude and aptitude, be empowered to perform effectively without having to endure boring training sessions?” I decided to find a way to enable a person with the right attitude and aptitude, but who may lack knowledge and experience, to become highly employable. Not only would this help businesses grow, but it would make thousands of young people social assets (as opposed to social liabilities).

What exactly does CLEVVA do?

CLEVVA allows companies to capture the logic that experts use in making predictable decisions and performing predictable activities. For example, you can now get a sales person to successfully sell hundreds of complex products as if they were a product expert. This is because CLEVVA guides them through the client discussion, analyses the client need, recommends the right products, and then automates the quote while they talk to their client. It allows them to focus more on their interpersonal skills without worrying about making a basic error.

What do you regard as the biggest success of CLEVVA?

Our biggest success has been that off one platform, we have managed to enable an inexperienced sales person to effectively sell 12 000 products with limited product knowledge.

The biggest challenge?

As a new brand, operating in a new category of technology, it takes longer than I would like to get companies to understand exactly what CLEVVA is (and is not), and what it can potentially do for their business.

How would you describe your personal journey with the company?

My journey really began 18 years ago as a change management consultant. It was there that I realised that people were really struggling to keep up with the rate of business change, and the complexity of the environment they were asked to operate in. I then turned my attention to finding ways of helping people thrive in complex, changing environments. This led me down the path of workplace learning and smart performance support technologies. CLEVVA is the culmination of over 15 years of blood, sweat and tears.

What role has Endeavor played in your personal development?

My relationship with Endeavor stretches over 8 years, as an Endeavor entrepreneur, as a panelist, and as a mentor. What has been most satisfying is the privilege to interact with top corporate leaders and to build friendships with some of the most passionate, talented entrepreneurs on the planet. This incredible network both inspires and teaches. It places you in the company of greats, and thereby asks great things of you in return.

Do you consider yourself a born entrepreneur?

I really don’t know. I have always been very clear about what makes me happy and what I want to achieve in my life. That clarity and self-belief has helped me make certain decisions without necessarily being that clear on exactly how things would pan out. As long as I felt passionate enough about what I wanted to do, and was clear that it would be valued by the market, I trusted that it would work out OK. So far I have been lucky.

Do you have any expansion plans for the future?

You betcha. We have every intention of being a global business within the next 3-years.

If you could advise the entrepreneurs of tomorrow one thing, what would it be?

Once you are clear about what it is that makes you happy, what you value, and what your personal goals are, you can then start exploring the best way to achieve these goals (and whether this matches what the market wants). If any of your goals refer to security or making money, rather consider a corporate career. If your goals refer to making a difference in the world or leaving a personal legacy, then maybe your own business is the right answer for you. Surround yourself with people who share your dream, refuse to ever give up, and before you know it, your collective dreams may just become reality.

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South Africa’s ongoing efforts to train its way out of the deepening skills crisis by using formal, traditional training methods won’t achieve much, says Ryan Falkenberg.

Publisher: FlyMango Magazine

Ryan Falkenberg is a director at CLEVVA, an innovative technology company that specialises in enabling under-trained and inexperienced staff to perform like experts. ‘We’ve been talking about the shortage of skills for years, but we’re no closer to solving the problem than we were five, 10 or even 20 years ago,’ says Ryan. ‘In fact, we are in a far more challenging situation. Ironically, we continue to address the challenge by doing more of what we’ve been doing in the past – expecting different results while still simply offering staff more courses that concentrate skills development within a formal classroom setting. It didn’t work 10 years ago and it isn’t working now.’

What will work, Ryan maintains, is investing in intelligent workplace-support mechanisms that offer support to daily on-the-job challenges. This is particularly necessary for staff who have already attained a basic level of competency, for example, in an introductory training programme. ‘Formal one-size-fits-all classroom training offers insufficient support for this,’ explains Ryan. ‘Far more effective is to invest in support that guides staff through integrated work processes and assists in complex decision-making. In effect, it involves capturing the logic experts use to solve standard work challenges, and offering this to others in a way that lets them perform and learn. This helps staff members to focus their efforts on tackling new challenges in a dynamic world. By offering intelligent, adaptable performance support along with coaching, learning becomes more about doing than memorising. And it is in doing that expertise is developed.’

Ryan also dismisses the typical criticisms of workplace learning: that it takes longer than formal training to achieve the desired outcome; that it is difficult to scale; and that business experts are few and far between, and typically lack the capacity to coach others. ‘Time to competence can be halved through learning by doing – as opposed to learning by listening,’ says Ryan. ‘Furthermore, workplace learning is more collective than individual, and performance coaches don’t necessarily need to be experts – just line managers performing their business roles.

‘Rather than offering more classroom courses, organisations should look to capture their expertise in intelligent systems that can guide new staff through workplace decisions and processes, allowing them to get it right without necessarily having the prerequisite knowledge themselves. By incorporating technology and systems, the possibilities become endless,’ Falkenberg says. ‘You can now enable inexperienced sales staff to sell hundreds of products to any client type, without much knowledge at all. Technology can intelligently guide them through the conversation, automatically recommend the right products and cross sales, and then generate the quote or order while they talk to the client. And that is just in sales. Imagine technicians being helped to diagnose technical problems, and being shown how to solve it without them knowing the answer in their head. Its all very achievable with new technology on offer, even for cash-stretched small businesses,’ Falkenberg concludes.

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