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A case for digital work peers

By the Feathercap team
10 minute read

What if you started a job with a very informed co-worker, work peers or mentor who could answer all of your job questions anytime without judgement?

It’s your first day of work; maybe for a tech company, a factory, a restaurant, a bank or maybe even from home or in the field. As you start your job you feel nervous but great since you know you have access to a friendly work peer or mentor, completely knowledgeable about your role and open to help you anytime and without judgement. As the day progresses, your work peer gives answers based on you, your role, your time on the job and overall experience. Very quickly, you start to see a rise in your confidence, productivity and success. This is great! You’ve never felt better beginning a job. Your employer knows if that state can be maintained, you will have the least likelihood of leaving. Now imagine if this experience of the great work peer and mentor could be in an automated digital form?

 

Reality: Do your employees have the answers they need? Do they have enough peers who can help? The answer is likely “No” and it’s getting worse.

We’ve long known that employees need the right answers to be confident and successful in their jobs. Typically, after completing their initial on-boarding training, everyone who has a job question simply asks their peers or manager. And in a recent study, this has been shown to be the dominant route employees take to get job answers. But rarely do employees have multiple knowledgable job peers to rely on. In fact, as every job becomes more complex and requires more skills. What we could call “skill creep” sets in requiring less people to do more with greater number of required skills. Employees asking questions to their peers becomes less practical and is discouraged more often because of increasing time constraints for everyone. Or worse, an employee’s peer or manager may not know the answer to specific job questions or provide the wrong answer.

In most every industry, monthly resignation rates have risen by at least 50% as those leave their current jobs in favor of better working conditions and higher wages elsewhere. The march to higher wages in an open and free market is probably inevitable when we have employee booms like we do now. But what’s also clear is a big reason for a lot of this turnover are the working conditions and stress employees have at work trying to do and learn their jobs without the previous luxury of having knowledgeable and experienced peers they can engage with to lighten their burden.

 

Existing and emerging technologies – LMSs, LXPs and the AI powered chatbots.

Traditional learning systems or learning management systems (LMSs) are great at delivering a crafted curriculum of on-demand content and vILT/ ILT (Instructor Led Training) at the beginning of an employee’s job tenure, for up-skilling and setting a cultural mindset for employees anytime. All content is crafted regardless of size to be consumed as a whole; varying from 5 minute of micro learning to multi-hour on-demand courses or virtual instructor led sessions. Examples of these are offered by Docebo and Cornerstone-On-Demand.

Learning experience platforms (LXPs) which focus on delivering the right learning and other content to employees as a learning path are great at letting employees get credit and earn credentials for learning any number of skills. The most advanced also help companies develop a talent marketplace to know who based on newly acquired training credentials is ready to move to another role. Great examples are Degreed and LinkedIn Learning.

The problem? According to a study conducted by Degreed back in 2016:

Percent of employees who ask job questions first to:
69% ask bosses or mentors.
55% ask peers or co-workers
28% to their company LMS/ LXP

 The above is troublesome for LXSs/ LXPs, since they’re not designed to give “answers”. Their designed to deliver whole courses and content based on set events and direct you to a specific document or course only when asked. From the above statistics, this has clearly proven ineffective for job answers.

The rise of NLU and chatbots

Since 2017, Google and many other natural language understanding (NLU) vendors have achieved a 95% rate of understanding for spoken and written language compared to a human. This gave rise to text and voice enabled chatbots to understand what you say or write. This is matched to their capabilities for understanding and indexing any text, document or video, comprehending every second of video and every sentence of text. Paired together, asking a chatbot a question gives employees not only the right answer pulled from existing documents, videos or courses the chatbot can start to hold a conversation to further refine the answer provided. Just look at what Google Lambda is doing for conducting a full dialogue with users. Being able to ask questions back and react to each user’s answer to continue a discussion on any topic. Though still experimental, this shows what may be soon possible.

Though none of this is a replacement to LMSs or LXPs, companies like ServiceNow, Microsoft and many others will undoubtedly use these as a great interface for employees in realtime to get the answers and content they need to do their jobs better all through a chat or voice interface.

More resources:

The failure of on-demand courses

What’s missing from enterprise learning?

The case for self-directed learning in the workplace

Three reasons to align user generated content with an LMS

The rise of conversational learning 

The state of AI driven cognitive search today: enter the digital work peer

Knowledge management and enterprise search systems as offered by Microsoft, Google, Coveo and most recently Moveworks have come a long way in understanding the relationship of content to all other content. Known collectively as cognitive search combining NLU (natural language understanding) and auto tagging using AI takes much of the manual curation out of organizing a company’s content. Cognitive search solutions focus on curating all of an organization’s content and the collective experience of this content by all employees and empowering searches to be more accurate. Existing systems to date have been most successful for large Healthcare, technology company focused projects utilizing large teams to deploy and tune.

What’s needed today is a way to combine the above cognitive search, chatbots while deeply understanding every employee. We call this a digital work peer. It’s the idea of building a digital replica of every employee to base and measure the questions asked, answers and content reviewed as a feedback loop to understanding each employee’s goals, curiosity, interests, specific job role as well as current and predicted future job readiness. This is like having our above great and knowledgable human peer all available automatically at anytime. To us, a digital work peer is the embodiment of every employee’s experiences and aspirations as they ask questions, receive answers and review the content addressing their job questions so they can be more happy and successful. For employers this means many advantages; having skilled and confident employees as well as through such a digital peer understanding what their employees need for their current and future roles. We look forward to the days ahead when a digital work peer can work with every employee around the world.  

More resources:

Five reasons content curation is getting more difficult

Five reasons AI will soon curate all your content

Feathercap has AI driven search and curation

Three reasons video search can now rock

About Feathercap 

Feathercap is your digital work peer. We make every employee happier, more curious and successful in their current job as we answer their job questions. For more:

https://feathercap.net

Have questions? Contact us.

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