Transparency is the foundation of good candidate experience- Part 1

An article by my colleague Dinesh Gokhale described how a candidate would feel short-changed by a well orchestrated, well thought out , stage managed candidate experience. We conducted a survey to understand the candidates’ psychology better. This two part article covers the insights gained in the survey.

Candidates actively seek more information

Some might think why add to the information overload by telling the candidate why she is rejected. What difference would it make to her? Contrary to what is commonly believed majority of the candidates do value feedback. The survey shows that majority of the candidates call the company to get feedback. There’s no teacher better than failure. But how can you learn from the failure unless you know the reason behind it.

Candidates Value Feedback

Candidates Value Feedback

Applicant Processing- A Lost Opportunity

Applicant process is in fact a marketing opportunity for the company to enhance its brand image. The applicant is a representative of the target segment and the process is a rare opportunity to engage in a two way communication with the target market. Every applicant is a potential future employee even if she may not be the best fit for the job for which she has applied. Companies must use this opportunity to develop a strong bond with the applicant by having a meaningful dialogue. How many companies actually do it?

Companies don't provide feedback

Companies don’t provide feedback

Companies get all the information and get answers to all their questions, but that’s just half the story. Our survey indicated that majority of the applicants rarely get any constructive feedback. Most companies are simply wasting this valuable opportunity to engage. It’s more like a monologue and less like a dialogue.

Companies Fake It But Don’t Make It

Only one out of many applicants is selected. Thus it’s important to study the feedback that is received by the majority- the rejected applicants. Here are some typical answers given by companies to the rejected applicants.

Top 5 Excuses

Top 5 Excuses

Excuses can’t replace relevant and constructive feedback. Relationships can’t be built by pretending to be engaging. “Fake it till you make it ” formula doesn’t work if there is no intention of ever making it. In fact companies who provide stock answers instead of meaningful feedback may be perceived as spammers. The same sentiment is resonated by this article about “Well Designed Candidate Experience” .

Companies who buy time with  promises that are never kept are pushing the applicants to become frustrated. Delay is the deadliest form of denial. One fails to understand why most companies take the applicants for granted.

What is the problem?

Companies don’t deliberately withhold information. The root cause is elsewhere. It’s the general lack of communication and clarity that engulfs all stages of the hiring process. Hiring is not seen as an activity of strategic importance by those engaging in it. Job descriptions, screening of resumes, interview scheduling and interviewing are conducted in silos and individuals engaging in these activities are not working in consonance as a single team. We will publish more insightful data which support these facts in the second part of this article.

 

Toolset used by the IT Recruiters

A panelist in a recent conference said that IT recruiters are overwhelmed by the number of software tools that they are required to use. They have to perform many tasks even after sourcing the required resumes . An earlier post covered various sources from where they source the talent.

This article is based on a survey that explores variety of tools used by technical recruiters for various tasks after sourcing a bunch of resumes. Total of 43 respondents who worked as recruiters in medium and large IT companies in Pune participated in the survey.

Technical Assessment

Technical assessment has always been a challenge for the IT recruiters because of their non-technical background. Tools like Hacker Rank, Hacker Earth, Mettl, Reliscope and Glider are being used by one third of the recruiters to overcome this challenge. Among all these Hacker Rank seems to lead the pack. Wonder what is keeping any of these tools from widespread adoption. May be it’s the time and effort to create, administer and analyse results of these tests. May be it’s sheer inertia. Total cost per use is non-trivial. These tests need continuous updates as new technologies get added every day.

Technical Assessment Tools

Technical Assessment Tools

There is no established software solution to conduct technical assessment. Two thirds of the organizations depend on in house on line or off line tools. Hacker Rank undoubtedly leads the branded technical assessment tools lot.

Applicant Tracking Systems (ATS)

 Applicant tracking solutions are by far most used special purpose tools. Here the adoption is close to 50%. There are many ATSs providing varied degree of automation at number of price points. Many enterprises already use Oracle and SAP resulting in their natural affinity towards Taleo and Success Factors respectively. I will be surprised to find a company using the ATS without the ERP. It’s surprising that none of the respondents mentioned the Naukri RMS in spite of it being integrated with the most used source of resumes.

 

Applicant Tracking System

Applicant Tracking System

The respondents are evenly divided between branded ATSs and other means to track. Taleo and Success Factors tie for the first place in branded ATSs.

Personalised Log of transactions or Tracker

There is no personalised database solution available for the recruiters to maintain their own pipeline of current and past candidates sourced by them for various openings. Excel is the default choice – easy to use and ubiquitous. Looking at 80% adoption there is no reason for any competing solution to try to dislodge Excel. Recruiters are so additced to Excel that they are maintaining their trackers even though the entire log of all the transactions is automatically tracked by the ATS!

Personal Database (Tracker)

Personal Database (Tracker)

It’s a surprise that 100% don’t use excel. Wonder whether the others maintain their personal database.

Interview Scheduling Tools 

Microsoft Outlook and Google calendar are the leading scheduling tools used by the recruiters accounting for more than 91% of adoption. It’s logical that most ATSs provide integration with these 2 scheduling tools. The vCal and iCal format of calendar invites are becoming the de-facto standards.

Interview Scheduling Tools

Interview Scheduling Tools

90% of the respondents use either Outlook or Google Calendar to schedule interviews. Some years back Outlook had even bigger share.

Remote Interviewing Tools 

What about “Specialised” video interviewing tools like InterviewMocha or Talview? There seems to be no significant adoption. Recruiters are still using Skype and phones.

Remote Interviewing Tools

Remote Interviewing Tools

Skype is the winner with 55% respondents using it as the preferred way to conduct remote interviews – landline calling comes distant second.

We love automation but we hate the loss of control 

Wonder why recruiters are maintaining trackers in Excel and schedule interviews using Outlook or Google Calendar when the entire history of their transacations is maintained and automated alerts are given by the ATS? Is it because old habits die hard? The answer is partly that and partly the fact that automation is a black box. People want to be doubly sure that the interviews happen as scheduled and they don’t lose the history including their comments. It’s the same reason why we carry cash even though we hardly ever use it. I am sure for the same reason we will have our hands on the steering wheels and our feet on the pedals when we get to “drive” our autonomous cars.

Build ontologies, let your chatbots socialize!

It’s 2018 and companies need to improve their understanding of customers, vendors, employees and investors. Companies need many more ears and mouths to absorb and disseminate knowledge. Machines engaging with humans in productive conversations using Natural Laguage Processing is no more a dream as well demonstrated by Siri, Alexa and Google-Home! Why is this so important? Obviously because it would empower companies to do what they need to do this year. But before we get to it , let us pull back and take a look at what makes knowledge transfer hard.

Tacit and Explicit knowledge

Tacit knowledge is what we have internalized and that is what we really use when we make a number of decisions in our personal and professional life. A pilot uses his tacit knowledge and has no use for explicit knowledge such as an instruction manual while flying a large passenger aircraft. Doctors, lawyers, architects and soldiers owe their tacit knowledge to years of training alongside their seniors. This tacit knowledge transfer happens while socializing as per Alex Pentland in his famous book Social Physics

Explicit knowledge is what we externalize and express in English or some other language in articles, books, videos, podcasts, databases and spreadsheets etc.

Nonaka and Takeuchi have developed the SECI model for organizations to grow their knowledge-base by cyclically going through the following 4 steps that looks like an ever expanding spiral

  1. Socialization ( Tacit to Tacit)
  2. Externalization (Tacit to Explicit)
  3. Combination (Explicit to Explicit)
  4. Internalization (Explicit to Tacit)

 

  • SECI

    SECI Model of knowledge transfer

    Tacit knowledge is hard to externalize. No one can communicate all he/she knows by writing it down. On the contrary socialization is easy. It happens easily because of the social setting which provides the context. Human brain snacks on information that is in context. On the contrary most of the communication directed at you on the internet is sheer noise due to lack of context. Wouldn’t it be wonderful if chatbots storing a lot of explicit knowledge could use it in a virtually social setting to engage in conversations with us?

    Let chatbots do the hard work of externalization

    Imagine having a friend by your side who has the patience to answer all your questions that you need to be answered to understand and participate in a conversation. All of us were very inquisitive as children. We stopped asking questions when we saw adults around us losing patience.

    Chatbots can simultaneously engage in thousands of conversations. Socializing with chatbots makes it easy for us to weave bits and pieces of knowledge in the right context. This knowledge is provided accurately in the right context by a chatbot that is lurking the background while we are going about our daily routine of using our enterprise software or our favorite app. Explicit knowledge is internalized by a chatbot in a few seconds. But for chatbots to learn new pieces of knowledge , they need to ask questions and plug incoming pieces of information in the right place. Ontologies provide the underlying infrastructure for chatbots to organize knowledge – somewhat parallel to the way humans learn by organizing related facts in the same part of the brain.

    Building an ontology made easy!

    An ontology is a little more than a taxonomy which is a tree like structure that organizes entities in classes, subclasses and instances. In addition it also establishes connections between leaves of the tree by specifying one way, two way and transient relationships. Its best represented in a graph database such as neo4j. Organizing the knowledge specific to your company’s business domain in a graph database is a daunting task. Many companies have spent years building ontologies. No doubt that it’s an effort that more than pays for itself- but the sheer volume of work deters companies from investing in this project.

    Synerzip has developed a semi-automated way of building ontologies. The system takes documents relevant to your company’s domain – which may be catalogues, brochures, articles, emails, spreadsheets, resumes or handbooks and puts them in a corpus. Top few hundred the frequently occurring terms in the corpus are manually organized by an subject matter expert to form the seed ontology. This might take a few days or weeks at the most.

    Automation kicks in once you have a reasonably well populated seed ontology. The program computes similarity scores based on the context in which terms appear. Terms having high similarity are put in the same class. There are still some places where a human expert is consulted to resolve contention. But it makes the project more feasible and viable for companies planning to build their ontologies from scratch. For companies who already have built their ontologies , this system could be a good way to update and improve utility.

    Building chatbots has been made easy by providers like Facebook messenger, Slack and Skype. By the end of this year , we will see chatbots being preferred over mobile interfaces by many applications.

The Startup Way- Take-aways from the Lean Startup Week 2017

The main highlight of the conference was the new book- “The Startup Way” authored by Eric Ries. It was released in the week preceding the conference and I was pleasantly surprised to be able to buy a copy from a bookshop in Hong Kong airport. I finished reading the book on the long flight to San Francisco and was all set to hear more about it from Eric himself. I was in for yet another surprise when as a part of the conference kit I got a hard bound copy of the book which many of us got signed by Eric.

The book significantly captures how a passionately motivated team trying to solve a problem under conditions of extreme uncertainty can apply the principles of “The Lean Startup” – even when the team is inside an institution such as a large corporation , Government or a social enterprise. The common idea is that any hypothesis can be validated by conducting a controlled experiment. These are low cost short iterations of few weeks each ending with success or failure. In either case the end result is that the team acquires some validated learning at the end of each iteration.

The Startup Way introduces some new concepts. Innovation boards are senior stake holders within the institution who act like VCs for the internal startups. They decide whether a proposed startup is worth investing in. Once the decision is made they hold the intrapreneurs accountable by reviewing progress on a regular basis in Pivot or Persevere meetings. The innovation board may decide to release the next round of funding or to kill the startup based on the value of validated learning by the startup. The board gives complete freedom to the startup in the way the funds are utilized. But the startup has the onus to use the funds judiciously so as to achieve demonstrable validated learning so that they can go back to the board for the next round. This way of funding is called as metered funding.

As one can see “accountability” is the foundation. The process is designed so that it builds the culture needed to motivate and empower people. All the words in italics have more detailed explanation in the book. The pyramid below shows the order of priority and significance associated with the four concepts.

Accountability

Accountability is the foundation

In this earlier article I had discussed the problems with hierarchies and various options being evaluated. The discussion was inconclusive and we remained admitting that no single structure can replace the hierarchies. “Horses for courses” as suggested by Tathagat Varma was the summary of our conclusion.

The startup way seems to have taken this thought one step further by suggesting a perpetually transforming organization that spins up startups to deal with the challenges as they come up. Some startups will succeed and others will pivot or die. This dynamic structure behaves more like a tree and less like a tower.The process of transformation itself is a series of lean startup style experiments . The diagram below describes the org structure in more detail.

TheStartupWay

Organization Structure for the Startup Way

Startups can be nurtured within the project teams with ambitious and passionate individuals hiring team members and “moonlighting” their way to launch. At some point this team would get blessed by the “innovation board” with a round of metered funding. This means the money comes with strings attached. Innovation board would ensure survival of the fittest by continuing to fund only the few deserving startups. Finally the successful startup would become an integral part of the organization by becoming a revenue earning , profit making project team or business unit.

The entrepreneurship function is just like any other staff function such as marketing or finance. The functional head is in charge of a knowledgebase of validated learning gathered from failed experiments. She will also ensure that the innovation boards do their job of guiding and nurturing the intrapreneurs.

Everything that is written in the book is supported by actual work done in several large conglomerates like GE and Citibank. Its very hard to judge the level of success given the size of these organizations. Most of the evidence is anecdotal. “The Startup Way” brings hope to the large hierarchical dinosaurs – may be they would metamorphose into nimble and vastly more intelligent forms.

The biggest take-away from the book is the accountability that lies at the foundation of the transformation. It brings some sense of control to the whole process of experimentation which is likely to run amok in endless iterations. Measuring validated learning by monitoring a leading metric which serves as a proxy for the net present value is at the center of innovation accounting. The proxy metric also needs to be corrected by accounting for the probability of it actually resulting into a certain net present value. This makes it easy for the innovation board to do apples to apples comparison between various opportunities competing for the next round of metered funding.

Execution Behavior change Customer Impact Financial Impact
Did we do what we said we were going to do? Are our people working differently? Do customers (internal and external) recognize an improvement? Are we unlocking new sources of growth as a company?
Project Team Is the founder and the team committed and stable? Has the team spent enough moonlighting hours on baking the idea? Does the idea pass the test of basic commonsense? Are they having a well defined business plan canvas? Do they know their LOFA? Do they hold P & P meetings? Do they run their experiments properly? Is there a recorded impact in terms of customer satisfaction? Shorter cycle time? Monetary savings? Customer referrals? NPV of business model. Productivity gain? Savings?
Business Unit What is the % of employees in startups? % of startup founders in this BU? What are the number of successful projects in the BU? Does the BU have mechanism of celebrating failures and capturing the learning? Employee morale? Per project cost? Average time taken by projects before first customer demo? Average cost incurred before first customer demo? Growth of BU revenue? Billable Head Count? Total Valuation of all projects incubated by the the BU
Company What is the % of employees in startups? % of startup founders in the company? Success rate? Is everyone talking about LOFA , Experiments and NPV? Number of pitches to the innovation board? Is the process simple? Are we able to attract better talent? Is it impacting Net promoter score? Are the number of red days zero? % of deep green accounts? New products launched? Value of phantom stock, Growth in revnue , billable head count and EBITDA, % of resources on bench

The cells in the table suggest some leading metrics for each stage from execution to behavior change to customer impact to financial impact.

In the end I would like to leave the readers think about a quote from Jack Welch. “ “If the rate of change on the outside exceeds the rate of change on the inside, then the end is near.”

 

Future of Work- impact of blockchain and smart contracts

Scope of this article is limited to innovative /learning organizations that are responding to constantly changing world. Traditional hierarchical organizations like the military or church are out of scope.

Distributed Autonomous Organizations (DAOs)will come into existence. These will have the advantages communities have over hierarchical structures. Individual team members will be bound by smart contracts and there won’t be any need for a corporate entity to govern their relationships.

blockchainforsmartcontracts

The risk of failure of a project will be assumed by an individual stakeholder who will be rewarded as the owner of the outcome if it succeeds.

These DAOs will be short lived – their lives will be limited to the project for the purpose of which the team is put together. Once the project is over the team will be disbanded.

Team members will be bound by a smart contract to the DAO. These smart contracts will ensure that no central authority is required to enforce the terms of the contract.

There will be no managerial overhead required to supervise individual team members and to ensure that they are delivering the work that they are being paid for. Smart contracts will automatically enforce accountability and discipline.

Work itself will be more interesting with one individual playing multiple roles – a leader in one project could be an intern in another project.

With smaller teams engaged in number of small short lived DAOs executing innovative projects the job of hiring team members will become more frequent. One can’t spend 12 weeks (as in the traditional recruitment process )searching for and evaluating candidates for a project which might last for 20 weeks.

More automated ways of recruitment using AI and Machine Learning will help recruiters and DAOs to reduce the time to hire to a few days – not weeks. Teams will get formed by like minded individuals finding each other. Trust relationships will be more easily forged by smart contracts.

Jobs will be replaced by assignments. An individual would be engaged in multiple assignments simultaneously. Each assignment will be customized to suit the needs of the project. Working hours, place of work, compensation, skills needed etc. will depend on the project. Designations will be replaced by multiple roles

Individuals will develop T shaped skills with depth in one area and interest and working knowledge of many other areas. In fact they will relish learning new skills by offering to work under a relatively younger team member. Reporting relationships will become more flexible- one can be reporting to a person who is a reportee on another project.

DAOs will pay individual team members in cryptocurrencies which will ensure that the economy in which the DAO is participates will thrive increasing the value of the cryptocurrency as compared to the fiat currency.

Monthly earning will depend on the value added and will reduce over the years if new skills are not acquired. There will be less politics as people will stop holding higher authority and getting paid higher merely because of their seniority. Authority and leadership will be short lived and based only on merit.

There will be a wider acceptance of the fact that intellectual property grows by sharing it openly , by maximizing its use and inclusion than by restricting its use and exclusion. Open source culture will gain ground. IP rights, patents and litigations will fade and become history.

Smart contracts will ensure that royalty, license fees and commissions will be automatically paid directly to the creator triggered by use of the digital asset. Intermediaries aggregating , distributing and collecting payments for digital assets will go out of business – the way music publishers like HMV and Nickelodeon went. Creative talent will be richly rewarded leading to an age of ultra modern renaissance.

Individuals will stop taking comfort in “getting hired” as the project to which they are assigned may not last more than a few weeks. Lifetime / Long Term employment with retention bonus etc. will become things of the past.

Smart contracts won’t need corporate law to ensure implementation. Cryptocurrencies would isolate these contracts from vagaries of fiat currency fluctuations. People working across national borders will be able to enter into contracts and get paid for their work without bothering about corporate laws of any particular nation. Geographical proximity would become less relevant. Teams will be formed based on mental proximity than physical proximity.