What are your skills, exactly?

When a woman comes to work after a break, the no. 1 question she is asked is "skills." So here it is, a skill based:

RESUME OF A WOMAN

Profile Brief

A CEO level talent with incredible view of all dimensions of running an enterprise. A dedicated and mature leader who has proven track record in aligning contrasting stakeholders to a common goal.

Finance

End to end budgeting, funds allocation and management of funds, accounting and internal audit for an annual budget of XX LPA. Upto 7-10% YoY increase in the budget every year. Additional responsibility is absorbed with no team augmentation.

Operations

Task Scheduling and Monitoring to ensure end to end efficiency in operations. Track record of less than 2% outage/task slippage over x years.

Operations Planning using CPM to ensure non-stop business continuity with minimal time investment.

Maintenance Scheduling and monitoring for all capital and operational assets including perishables.

Inventory Management

Demand forecasting and Inventory Management for 120+ SKUs, panning across Capex, Opex and perishables, with 0 outages and less than 10% forecasting error.

Human Resources

Recruitment, Talent Engagement, Agile Performance Management system with ongoing 360 degree feedback for a team of 5. Annual Attrition at <20%. Exit management and HR transactions like payroll, benefits, grievance and discipline management. 24*7*365 POSH monitoring and control.

Stakeholder Engagement

Excellent stakeholder management skills with proven ability to align stakeholders with opposing agendas to arrive at a common ground and collaborate. Ability to deal with a variety of stakeholders across levels, domains and organisations.

Negotiation Skills

Ability to negotiate in 1:1 and 1:M situations and arrive at Win-Win outcomes.

Project Management

Ability to plan, execute, monitor, control and close projects of short and long term duration across travel, construction and education industries. Brings valuable client perspective to the table.

Procurement

Ability to source on both “L1” and “L1,V1” basis for industries as varied as FMCG, Stationery, Appliances, Construction, Materials(B2B) etc.

Vendor Management

Contract Management, Performance Monitoring, Review Feedback, Payments processing and ongoing vendor relationship management.

Risk Management

Operational and Behavioral Risk Management in operational capacity. Ability to foresee risk, threat, vulnerability and plan accordingly.

Internal Audit

Ability to deduce information from written and unwritten sources and remain an agile internal watchdog. Also ensures organisational preparedness for external audits.

Communications Management

Ability to customise the message according to the needs of the recipient. Ability to be sensitive and responsive to the communication needs of various stakeholders and ensures adequate contact and communication.

Quality

Ability to apply simple QA and QC procedures to ensure quality. Ability to train team members on the importance of quality.

 

 

 

An article from 2011: Not betting on Android yet

 

I love the news that Android has overtaken Symbian as the mobile OS. It is, in principle, the victory of the open source.

 

But am not betting on Android just yet. Because, Android is yet to face and successfully deflect a major challenge. And that, is the acid test of a victor. An unchallenged victor is not a victor – merely a figure of preponderance.

 

Sample this: An Android app is created. it appears to be a simple stress buster app that allows you to knock a hammer virtually when you are stressed. Great. A few million downloads happen over a time unit – say a month or so. Its a viral app that is promoted by online word of mouth and because its free, the download is easy.

 

What we do not know is, that underneath the hammer code is another code – malware. It could be anything – a code that surreptitiously handles your data – either obliterating it systematically, or acting like a virus and moving to other phones (not the app section, just the virus section, or monitoring all your connections and forwarding your emails to another address in bcc without telling you, or using your phone to participate in a DDOS attack .. anything at all.

 

The 2 things that stack up against Android as against other OSs are:

1. The easy implementation and the much higher “Viral” impact possible.

2. The more the no. of connected Android smartphones, the greater the temptation for a malware creator.

 

I’d love to see the victory of the Android.. because it puts the power in the hands of the user – because it allows people to contribute and use .. creating a community of producers and consumers. 

 

Which is why, its important for Android to anticipate at least some of the growth pangs, and to plan for it by creating security apps that can be downloaded by users. Am sure someone has thought of it already and its in process somewhere.. just wish we non geeks knew about it.

 

And before we place that Victor crown of olive branches on the Android head, Android will have to prove that it can quash more than one malware challenge. It will take one, exactly one major application based attack to completely kill the Android credibility. And thats one chink in the armour that some competition is waiting to exploit.

 

As i write this, there is, am sure, a programmer somewhere, writing such a malware and smiling to themselves, and there is somewhere, a programmer writing a code that will take care of phone security on Android. Like the African Giraffe and Lion story, we just have to wait and see which one runs faster.

 

How to Design a Dashboard for a customer

 

1. Do NOT sell flashy stuff for the sake of appearing “trendy” or “up to date” . “Up to date” gets dated pretty quickly. Useful, on the other hand, usually endures.

 

2. Use common sense more than you use the solution vendor’s marketing material.

 

3. Ask a few questions:

 

A. What are your categories of users? (Line managers, Middle Managers, Top Management, HR Business Partners, HR Senior Managers, Finance Managers..)

 

B. Do the information needs remain the same through the year, or do they change according to your time of year (financial year end closing, Appraisal year end closing, quarter end closing of sales…)

 

C. What is the top DECISION SUPPORT information that you need? no less than 1, and no more than 8. For each category of user. Gather this information using questionnaires divided by user category. Arrive at the top (by mode) answers and finalise them.

 

D. How often does this information change enough to impact ur decision making? (Eliminate all information that does not change significantly for a month or more. e.g., gender diversity is a statistic that will not change for the rest of the year, except during the campus recruitment season, when we need to actively monitor if we are hiring enough from each gender)

 

The second use of this information, is to determine the refresh rate with the database.

 

E. Do you want the dashboard to be the opening screen, or do u want to access this on need basis? (Tells you a lot about the actual usage of the dashboards being designed) . Please get this information, again, by category of user, then determine. Some categories may want it to be the first screen, others may want more than one dashboard that they access on need basis.

 

F. NOW, go to the flashy stuff – the look and feel.

 

What is the process you would like to follow, as an Analytics consultant?

 

 

 

Employee Engagement and Productivity – The role of the employee personality

 

This morning, i set self a small challenge – Does employee engagement have a positive correlation with productivity? Can employees be productive even if they are not engaged? Can they be engaged without being productive? (think public sector in India) .

 

In most research studies (see links below) Engagement is almost always found to be positively correlated with Productivity.

 

But what if, it was possible for employees to be productive without being engaged? What if they brought to work  – not their personality, but their experience and expertise?

 

Surprisingly, this was the predominant school of thought in the manufacturing era, when we expected people to leave their personalities outside the door, with their shoes, and to wear them again on the way out. Inside, they were time and motion machines (think Frederick Winslow Taylor and the One Best Way theory) .

 

In the IT era, we said, we are hiring brains and not time and motion machines. And yet, we continued to do effort estimate on “man days” and “man hours” – based on the “average time it should take a person to do this task”.

 

Coming back to the subject, does an employee have to be engaged to be productive?

 

I think that productivity is a function also, of the personal discipline and professional ethics of the employee. Of course, here we assume that the employee has the relevant experience, expertise, and authority, and all the organisational factors have been taken care of. Those are hygiene factors in any discussion on incremental productivity.

 

Without any employee engagement measures, using the pure “Work-for-pay” model, the output is:

 

Work = Pay

OR

Work  < Pay

OR

Work > Pay

 

What are the factors affecting this equation and the direction it tilts in?

The employee’s personal engagement level, his/her personal traits, since all employees are treated the same, but some are on the left of the equation and some on the right.

 

So, at least some part of the engagement quotient comes from the employee – from their own personalities.

 

When doing any engagement initiatives, the organisation has to target them, not towards general theories of psychology and Organisational Behavior, but towards the kind of employees they have hired in the first place. The extra benefit obtained from each engagement dollar is also a function of the fit of initiative to the personalities of employees.

 

In a small organisation, it is self evident. And in large organisations, this principle should be exercised using a simple breakdown process – let each sub organisation decide what works for them. Monitor results, correct course where required, but do not assume that the entire organisation has exactly the same kind of people.

 

Now, lets assume positive correlation between engagment and productivity, such that, for every dollar spent on engagment, the producivity does go up, only the scale is unpredictable.

 

i.e.,

Pay + Engagement = Work + x

where x is the additional productivity created by engagement initiatives.

 

Question to ponder: Can x be a negative value? Can engagement intiatives backfire and make employees even less productive than they would otherwise be? What do you think leads to negative values of x?

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Further reading

 

Here is the set of online resources that mentions other studies done on the subject:

http://www.workforce.com/article/20130501/DEAR_WORKFORCE/130509997/how-do-we-know-our-engagement-efforts-are-paying-off

 

http://www.insyncsurveys.com.au/resources/articles/employee-engagement/2012/10/impact-of-employee-engagement-on-productivity/

 

http://www.sciencedaily.com/releases/2011/07/110720142459.htm

 

http://www.sciencedaily.com/releases/2009/05/090513121050.htm

Predicting Employee Attrition Using Big Data

 

2 weeks ago, the HR Head asked me a question – I want to know which employee is going to put in his papers – and when.

 

It was one of those rare moments when i was completely, totally stumped.

 

Here is a partial answer- How to use Big(and small) data together to predict employee turnover.

 

Factors that impact turnover

Lets start at the very beginning. What makes an employee quit?

 

When I conducted Exit interviews at our small 700 people IT organisation, i wouldnt ask them, “why are you leaving?” I would ask, “Why did you start looking?” I wanted to understand where the distance began, and why. The resignation is not what we are investigating. That action is the result of a disengagement that began weeks, months, even years before the actual resignation.

 

We are investing that disengagement. And the probability of its resulting in a separation. Two different things.

 

How do we measure something as intangible as disengagement?

 

I believe we may have some ideas here.

 

Pointers to Disengagement

 

• Employee Satisfaction Scores

This one is apparently a no brainer. Yet I am suprised to see that most ERP packages dont have a place to store the employee’s engagement score and compare that year on year. Then check for its correlation with their performance ratings and other behavioral actions. There are pointers there.

 

• Social Media Activity

This is where big data comes in. Have an internal IM program and an internal social media platform like yammer or internal discussion boards? Let your Big Data analysts do quick calculations on how often and with how many colleagues the IM was used. And how often the social media platform and discussion boards were used. Engaged employees will use more “connection points” to connect with the organisation and its people.

Notable Exception: Introverts. Introverts are people too. And they wont use Social Media. The end of this post says “Its the pattern, not the static data.” Read that section to know more.

 

• Meet the Parents

This is one of my favorite metaphors. When they bring the family, they are engaged. No exceptions. This also can be automated. Attendance at the family events is automated and can be fed into the giant supercomputer for automatic analysis. If you know when they stopped bringing the family, you know when they started thinking out.

 

• Access Card Patterns

Another big data beauty which needs individualised reading to make sense. How often was the access card used to go in and out? Whats the pattern? Has it changed lately?

 

Which access cards are used together? Are the breaks in groups, with one or two friends, or alone?

 

• Use of development resources on the learning portal

What kind of courses are being accessed? What was it earlier? Is it consistent with the expectations of the current role? What is the usage pattern?

 

• Correlate with Performance Ratings and the moneys

The higest risk categories are employees who have recently witnessed a fall in the rating, or whose difference from their maximum potential earning is very high. Let me explain. Suppose Mr. Alpha is paid INR 100 at the highest paying company. You are at the 60th percentile as an organisation, so you pay INR 60 for the same profile. But suppose the actual salary of Mr. Alpha is not INR 60, but INR 55, because of your internal compa ratio adjustments. Which means that Mr. Alpha is at a 45% discount from his maximum earning potential. That kind of gap is not sustainable.

 

And lastly, remember, its the pattern, not the static data. Big data will, over a period of time, establish patterns of behavior for each employee. When this pattern of behavior changes in a perceptible way, and for a consistent period, you know you should care enough to investigate more.

 

Does disengagement always result in attrition? Is it worth bothering with if it doesnt lead to attrition? What are some of the other pointers that can be used to arrive at behavioral disengagement? Anything we have missed out in the article above?