Leaders in an Agile Enterprise

Can leadership style be at dissonance with an organization’s incentive/rewards scheme? And what is its correlation to motivation?

An individuals motivation can be intrinsic or extrinsic. Intrinsic is when we act, not for external rewards, but for the simple pleasure or satisfaction of achieving something. Performing one of these activities is reinforcing in-and-of itself.

Laissez-faire leadership can be effective in situations where group members are highly skilled, motivated, and capable of working on their own, with very little guidance. Laissez-faire style is used in situations where followers have a high-level of passion and intrinsic motivation for their work.

So what happens when laissez-faire leadership meets people who are not good at setting their own deadlines, managing their own projects, and solving problems on their own, skills essential for an agile organization? How can leaders adapt?

Laissez-faire leaders are often seen as uninvolved and withdrawn, which can lead to lack of cohesiveness within the group. In such a situation, leaders need to change their style – easier said than done – and get more proactive, assertive and hands-on with the task or process needed to accomplish the task.

Eventually, as followers acquire more expertise, leaders might switch back to a more delegative approach that gives group members more freedom to work independently.

A major dissonance occurs when laissez-faire leaders implement rewards schemes, which in reality is a switch to a benevolent authoritative style. “Meet your targets and you will be suitably rewarded!”. The followers, even those who are intrinsically motivated, now must adopt performance to maximize rewards.

In this situation, the leader now uses rewards to encourage appropriate performance and listens more to concerns lower down in the organization, though what they hear is often rose-tinted, being limited to what their subordinates think the boss wants to hear.

And if the span of control is one to many (as is often the case), the leaders time has to be split across multiple stakeholders. Overtime, the leader chooses to listen more to those who think like they do (and is what they would like to believe), thereby reducing the space for dissenting voices.

Thereafter is a rapid spiral downward into a crisis.

In the final analysis, the source of the most insurmountable hurdle in achieving the goal of strategic agility is the organization’s leaders.

Software WIP

So you have established a software development process. Now what?

This question always comes up at a point when development teams have settled into their initial process and each team member understands the work flows, its tools and its artifacts.
It sometimes becomes difficult to explain why the processes that have been just implemented are just “initial” processes and that they now need to get down to the tasks of evolving these processes.

So why do you need to evolve an established process that everyone appears comfortable with? The answer, I believe, lies in determining the end objectives of any software development process, and those are to (1) maximize throughput (or minimize time to market) and (2) reduce work in process inventories.

While the first is easily understood and justifiable, the second is a bit elusive and as some may say, nebulous and theoretical. So let’s try and understand who is saying it and why they are saying it.

To many organizations, caught up as it is, with a routine and a host of day to day distractions, the thought of reducing work in process inventories probably never even crosses the mind.

I mean, is that important or can I just “get on with my job” is the attitude that flows back at you, especially if you are engaged as an external consultant. Here is a very apt graphic that captures the tone of the engagement at this point in time:

So now what? You have seen the problem and have wheels to offer, but your client says, “No thanks. We are too busy”. Or, “This is too theoretical! People are getting bored.”

Firstly, and let’s just get this out of the way – What the hell is “work in process inventory” for a software development organization? For software development organizations, “work-in-process inventory” is any software artifact, the creation of which has consumed some effort, and the said artifact has not been deployed to production yet. That includes all code files, test or database scripts, or documentation that is being worked on.

To really get to grip with this, you got  to take a look at costs. Assuming an average blended rate of $1 per hour per seat at a development centre in India. Now say, the TL of Team A has spent 2 hours reading the specification, an hour in discussion with the architect, and another hour in a discussion with the creative team on the user interfaces.

Together, the total time spent by the TL for this one requirement is 2+1+1 = 4 hours, which at the rate of $1 per hour works out to $4.

Total effort including the architect and creative designer works out to 4+1+1 = 6 hours, or $6.

Now suppose the TL switches context to another requirement and spends 2 hours in a discussion with the business analyst to develop, say, design options. Total effort by the TL and BA put together is 2+2 = 4 hours or $4, taking the total “work in process inventory” cost to $6 + $4 = $10. Both these requirements are a long way from production.

Now consider a centre with 100 developers. This amounts to 100*8=800 hours of capacity per day. Assume a cycle of 2 weeks, i.e., 800*10 = 8000 hours. Take a scenario where 35% of the effort (not too bad for many organizations) is spent in each cycle on artifacts that never move into production or one reason or the other (low priority, resource constraints, technology hiccup, upgrade needed, etc). That is 35% * 8000 hours = 2800 hours, which in cost terms is $2800 per cycle, given the same $1 per hour rate (this rate is difficult to achieve with just a 100 person team and is likely to be in the range of $2.35 to $3.00 per hour) .

Over 26 cycles (theoretical maximum per annum for this team), that amounts to $ 72,800.
Given a blended average annual CTC of $13,500 per person, the figure derived here works out to 5.4% of salary cost (COR). In other words it is like having an additional, hidden bench of 5% throughout the year. If you take the more likely cost per hour figure for this size of development centre, the bench works out to between 14-20%.

Now what? The solution lies in identifying who is really affected by increasing work in process inventories. In other words, who owns the cost metrics. This will, in most cases be either the portfolio or service delivery head, or the head of engineering, usually someone who owns the project management function within the organization. 

Engineering, as we saw earlier, has the two objectives:

1. To maximize throughput (by reducing time to market), and
2. To minimize WIP inventory

Incidentally, another dimension to WIP inventory is Technical Debt, but measuring that is even more nebulous, so we will cover that in another article. What is the solution? Meaning, how do you go about reducing WIP inventories? That’s precisely what Kanban is all about and the subject of yet another article. For flow process, this is fairly straightforward as long as there is a common definition for work prioritization. For batch processes, it is a more involved process and organization’s will get there over time through staged process evolution (Process Roadmap).

Does it make sense?

On the Sharing Economy

In what is called collaborative consumption, the sharing economy or the peer economy, owners rent out something they are not using, such as a car, house or bicycle to a stranger using these peer-to-peer services. The company typically has an eBay-style rating or review system so people on both sides of the transaction can trust the other. With the popularity of these services, many people don’t need to buy when they can rent from others.

Airbnb, the San Francisco startup is the poster child of the collaborative consumption or peer economy. Here, travellers can rent a room or a whole home or a British castle on Airbnb. Dog owners can leave their dog with a host who will take care of the dog on DogVacay. On Google Ventures-backed RelayRides, people can borrow cars from neighbours. They can rent the cars by the hour or by the day. If the car has a service like OnStar, users can open the car automatically through a mobile app.

TaskRabbit is a mobile marketplace for people to hire people to do jobs and tasks, from delivery, to handyman to office help. Founded in 2008, the site has 4000 TaskRabbits on the service nationwide who bid to do tasks that are posted by people looking for a service. All the “rabbits” are interviewed and have their backgrounds checked before going on the system.

Peer-to-peer car sharing company Getaround lets people borrow cars from others. Owners who are out of town can also leave their car with Getaround, which will rent out the car, clean it and take care of it. Getaround cars are covered by a $1 million insurance policy from Berkshire Hathaway.

Liquid, a rent a bike from a neighbour was formerly known as Spinlister. Zaarly is a peer-to-peer marketplace for people to provide services to others. Compared to other services, Zaarly focuses on creating “stores” for sellers to market their services, from home repair to iPhone repairs, buy a home made pie or hire a cobbler.

Lyft is a ride sharing service for people to find rides from “regular” people who have a car. The service, created by Zimride, only takes “donations” because it is not a taxi service.

Lending Club’s peer-to-peer network can be used to get cold hard cash. Lending Club is cheaper than credit cards for borrowers and provides better interest rates than savings accounts for investors. Since July 2007, Lending Club investors have invested over $1 billion in loans and received more than $85 million in interest payments.

Startup Fon enables people to share some of their home Wi-Fi network in exchange for getting free Wi-fi from anyone of the 7 million people in Fon’s network.

SideCar, a ride sharing startup, now available in San Francisco and Seattle, allows “regular” drivers to pick up people who want a ride. Drivers also accept a donation, but don’t charge a fee.

People buy or sell their clothing via Poshmark’s mobile app. They can also display their virtual closets and find friends who have similar styles.

And NeighborGoods is yet another community service where you can save money and resources by sharing stuff with your friends. With Americans spending $22 billion a year on self-storage, that’s a lot of unused stuff. So need a ladder? Borrow it from your neighbour. Have a bike collecting dust in your closet? Lend it out and make a new friend. And what more, borrowing and lending items on NeighborGoods is free of charge though members may charge a deposit or a rental fee for the use of their items. However, NeighborGoods does allow members to upgrade their accounts for $9.99 for access to more items.

The “sharing economy” has attracted a great deal of attention in recent months. Platforms such as Airbnb and Uber are experiencing explosive growth, which, in turn, has led to regulatory and political battles. Boosters claim the new technologies will yield utopian outcomes—empowerment of ordinary people, efficiency, and even lower carbon footprints. Critics denounce them for being about economic self-interest rather than sharing, and for being predatory and exploitative. Not surprisingly, the reality is more complex.

Sharing economy activities fall into four broad categories: recirculation of goods, increased utilization of durable assets, exchange of services, and sharing of productive assets.

The origins of the first date to 1995 with the founding of eBay and Craigslist, two marketplaces for recirculation of goods that are now firmly part of the mainstream consumer experience.

These sites were propelled by nearly two decades of heavy acquisition of cheap imports that led to a proliferation of unwanted items. In addition, sophisticated software reduced the traditionally high transaction costs of secondary markets, and at eBay, reputational information on sellers was crowdsourced from buyers, thereby reducing the risks of transacting with strangers.

By 2010, many similar sites had launched, including ThredUp and Threadflip for apparel, free exchange sites like Freecycle and Yerdle, and barter sites such as Swapstyle.com. Online exchange now includes “thick,” or dense markets in apparel, books, and toys, as well as thinner markets for sporting equipment, furniture, and home goods.

The second type of platform facilitates using durable goods and other assets more intensively.

In wealthy nations, households purchase products or hold property that is not used to capacity (e.g., spare rooms and lawn mowers). Here, the innovator was Zipcar, a company that placed vehicles in convenient urban locations and offered hourly rentals.

After the 2009 recession, renting assets became more economically attractive, and similar initiatives proliferated. In transportation, these include car rental sites (Relay Rides), ride sharing (Zimride), ride services (Uber, UberX, Lyft), and bicycle sharing (Boston’s Hubway or Chicago’s Divvy Bikes).

In the lodging sector, the innovator was Couchsurfing, which began pairing travelers with people who offered rooms or couches without payment back in 1999. Couchsurfing led to Airbnb, which has reported more than 40 million stays in over 190 countries.

This type of service includes non-monetized assets such as tools, which are more immediate neighbourhood based, providing people with low-cost access to goods and space and some opportunities to earn money.

The third practice is service exchange which began in the 1980s as a means to provide opportunities to the unemployed. These Time banks are community-based, non-profit multilateral barter sites in which services are traded on the basis of time spent. However, these have been less popular than monetized service exchanges such as TaskRabbit and Zaarly, which pair users who need tasks done with people who do them.

The fourth category focuses on sharing assets or space in order to enable production, rather than consumption. These include hackerspaces for computer professionals, makerspaces which shared tools and co-working spaces that served as offices. Other production sites include educational platforms that aim to supplant traditional educational institutions by democratizing access to skills and knowledge and promoting peer instruction.

These new technologies of peer-to-peer economic activity are potentially powerful tools for building a social movement centered on genuine practices of sharing and cooperation in the production and consumption of goods and services. But achieving that potential will require democratizing the ownership and governance of the platforms.

The trend has not been without its naysayers. “How are we going to harness the sharing economy to spread the wealth?” The Airbnbs of the world and their venture capitalist backers are siphoning off too much value, some argue. Discussions of labor exploitation, race to the bottom dynamics, perverse economic impacts, unequal access for low-income and minority communities, and the status of regulation and taxation are some of the negatives that have engaged industry watchers for a while.

And while the politics of these sharing efforts differ across the globe, what is common is the desire among participants to create fairer, more sustainable, and more socially connected societies.

REFERENCES

1. Airbnb is Inc’s 2014 Company of the Year; Dec 2014; Burt Helm [inc.com]
2. The Rise of the Sharing Economy; [triplepundit.com]
3. Debating the Sharing Economy; Oct 2014; Juliet Schor [greattransition.org]
4. Today’s smart Choice: Don’t Own. Share; Mar 2011; Bryan Walsh [time.com]
5. Consumer intelligence Series “The Sharing Economy”; Apr 2015;

Examining Complexity Management

It was Oliver Wendell Homes Jr. who said:

I would not give a fig for the simplicity on this side of complexity, but I would give my right arm for the simplicity on the far side of complexity.

Traditional management thinking evolved in the Industrial Age dominated as it were by machines, the linear mechanistic principle of cause and effect, and cast into management literature by the likes of Frederick Winslow Taylor in his treatise on Scientific Management. Management in this age was essentially reductionist in approach, that of decomposing complex problems into its elements and analyzing them in order to make sense of the whole.

However Complex Systems and organizations in the Knowledge Economy are non-linear, highly interconnected and interdependent demonstrating what is referred to as “emergent behaviour“, that is, the behaviour of a system that does not depend on its individual parts, but on their relationship to one another.

Emergent behaviour cannot be predicted by examination of a system’s individual parts (traditional reductionist approach). It can only be predicted, managed, or controlled by understanding the parts and their relationships – “the whole is greater that a sum of the parts.”

Individual parts of a complex system are arranged into a structure, which then determines the behaviour of the system. Systems analysis is thus a matter of identifying the relevant structure of the system and its most important parts.

Examples of parts are atoms, the parts in a machine, in people, and in nations.

Examples of structure are the social contract that people enter into to form a government or an organization, the molecular structure of a chemical compound like amino acids, or the way in which individual cells in the body are organized into a myriad of organs.

Examples of emergent behaviour then is, human life, the perfidies of the global financial system, dysfunction of communities (in demonstrating undesirable or criminal behaviour), the quirks of the economic models of nation states, as well as the impact of the environmental sustainability problem on the bottom lines of some large commercial organizations in sectors like Oil & Gas, Minerals, Metals, Mining, Fisheries, Energy, or even, Infrastructure.

The new prescription is that the more you step back and embrace complexity, the better chance you have of finding simple answers.

For example, in most organizations, sales is a frequent focus of financial objectives and concerns. When targets aren’t being met, and a business isn’t growing at the rate you hoped it would be, it’s tempting to assume that you simply need to drive more sales and for your sales people to work harder.

Their targets have been set, and they must achieve them. We even design incentive systems to reward those who simply achieve their target without reference to any other dimension of their work.

However, this can be a simplistic and naive outlook. For there may be a whole host of other factors that might be influencing this outcome.

It may be that your target market is declining or your market has shifted such that your product or service no longer meets the needsof your audience. A new competitor or a substitute product/service may have appeared in your marketplace making it difficult for you to compete.

Your marketing may be failing to generate an adequate number of leads or to encourage trust and loyalty to your brand. Your branding and positioning may have become outdated or may no longer be relevant to your market. Or it could be that your sales targets are in fact inaccurate.

And that is just a handful of the factors that could be involved. By focusing only on the sales and finance ‘nodes’ in this situation, you risk missing the fundamental root cause that is in reality your key to success.

Managing Complexity - The Demonetization Case Study

On 08 Oct at 8 PM, the Prime Minister of India, Mr Narendra Modi, in one of the most significant and dramatic policy changes in the history of independent India, announced to a shocked nation that high denomination notes of Rs 500 and 1000 would cease to be legal tender at the stroke of midnight.

For a majority of Indians, accustomed to the existence of the parallel economy for decades, it represented a bold and sweeping new landscape. It bought with it a glimmer of hope for a bright future, for this was the kind of change that India had expected after having elected Modi to power in May 2014.

For businesses, it is useful to follow developments as a case study in managing complexity using new sense-making frameworks such as the Cynefin.

Our first attempt at understanding the decisions and events following the announcement gave us this dynamic:

We attempted to explain the dynamics as under:
1-2: The long decent into chaos due to years of inaction and neglect by successive governments
2-3: The recovery through a series of modifying actions, post the policy announcement
2-4: Attempts by delinquent elements in the system which are attempting to disrupt the change though propaganda and incitement. Unfortunately, the media in India has been almost completely bought out and hence cannot be trusted to be objective or helpful.

There were a couple of problems with this assessment.

Firstly, did the decent into chaos happen gradually from the complex domain into the chaotic domain (which is a natural transition) or was there some sudden revelation (from the data available to the government) that needed immediate and drastic course correction?

Secondly, was the plunge into crisis the result of the announcement, or was the announcement the start of the recovery process? If the former, it is a controlled shallow dive into chaos for the purposes of driving innovation and behaviour changes among all stakeholders, including the general population. And if the latter, and besides some visibility of its negative effects - propagating terror, secessionism, naxalism, election fraud, endemic corruption, hawala & round tripping, fake currency (FICN) and such like - why wasn't the crisis more visible?

Does the "boiling frog" analogy hold here?

What does this have to do with boiling a frog?  There is a fascinating 19th century science experiment.  As the story goes, researchers found that when they put a frog in a pan of boiling water, the frog just quickly jumped out.  On the other hand, when they put a frog in cold water and put the water to boil over time, the frog just boiled to death.  The hypothesis is that the change in temperature is so gradual, the frog does not realize it’s boiling to death. While the results of the experiment are in question it is a good metaphor for organization cultures[5].

We know that the transition from complex to chaotic domains is a transition for controlled experimentation. And we also know that the transition from Simple to Chaotic is akin to falling off a cliff. This boundary, between Simple and Chaotic, is the Zone of Complacency. Organizations arrive here through neglect of changing circumstances, though believing in one's own myths.

So we revised our dynamic to arrive at this:

Here we moved the 1-2 dynamic to the right so that it first drifts from Complicated (where monetary policy formulation structures and systems design is anchored) to the Simple domain of "best practices" and onward to the Zone of Complacency, the boundary between Simple and Chaotic, until it topples over into a full-blown crisis.

The recovery dynamic was split into two.

The 2-3 dynamic is the recovery through a series of urgent policy modifying actionsto stabilize the situation and subsequently, once stable, the 3-4 dynamic brings the situation back to normal through a series of probing experiments that seeks to establish a coorelation between minor policy change actions and its consequential impact on the monetary system.

The 2-5 dynamic is of course, the actions of the delinquent elements within the system.

We have also linked 5 and 1 with an arrow to indicate the different designs of executive policy formulation processes and monetary policy formulation processes.

Now, there are two ways of arriving in the Chaotic domain - deliberately or accidentally.

• If we enter Chaos deliberately, its primary purpose is innovation and inducing behavior changes.
• If we enter it accidentally, then we need to act swiftly to stabilize the situation.

To further revise the picture, we need to know whether the crisis was induced deliberately or accidentally. 

Past government policies leading up to the demonetization announcement clearly indicate that a fair amount of preparatory steps lead up to it - from announcing Digital India, the opening of Jan Dhan accounts for the marginalized in support of the Direct Benefits Transfer scheme that brought access to basic banking services to a majority of the population, the series of bilateral agreements with numerous countries on money laundering and anti round-tripping, and subsequently the Voluntary Income Disclosure scheme (VIDS 2016) that ended on 30 Sep 2016.

Surely, anyone able to connect to dots would have been able to foresee the next step in this sequence or at the very least, get some inkling of what was to come. That fact that the government managed to keep such a dramatic shift in policy confidential worked well. There was no other choice. There was no way, "better preparation" could have been afforded, if the outcomes were to be realized and the cost of change justified.

It will also be great, if we can get to the real reason why the previous federal reserve (RBI) governor, Mr Raghuram Rajan was not given the extension to which he was clearly amenable. Maybe it will come out at some point in time, probably in an autobiographical narrative. For now, it is just one more dot in the pattern of government actions in the lead up to demonetization.

So we will have to revise the dynamic again, in view of the fact that, the policy was a bold and deliberate move by the government to "rock the boat" at a huge political risk. From all indications, the dynamic that most fits the bill is a deliberate and "deep dive into chaotic domain".

The reasons are obvious.

1. There is no way to bring about a dramatic change in behaviour in India that was unitedly in favour of both accountability and transparency in financial transactions, unless the level of use of physical currency in the country was reduced to a bare minimum, that too for small transactions.
2. There was no way to bring about systemic changes in the monetary and its associated systems unless it was jolted into a crisis. For example, even large public sector banks such as the State Bank of India, had consistently refused to participate in the RBI/IBA collaborative ventures such as the National Payments Corporation of India (NPCI), whose charter, among other things, was to create a standardized interface for all retail payment systems in India. 
3. There was a crying need to choke hawala channels, round-tripping and other money laundering mechanisms.
4. Curbing terrorism, naxalism, secessionist movements in the North East, the underworld, and political muscle, all being funded by the parallel economy had become a priority national security issue.
5. Lobbying, election funding, government contracts, defence procurement et al. needed transparency and reform.
6. Major step-by-step reforms were needed to prevent money laundering in the jewelry, gold and precious metals, real estate, metals & mining markets.
7. Rampant funding of NGOs and religious bodies by foreign interests, use of monetary inducements for proselytizing, blocking of development activities through contrived environmental concerns, misuse of official and legal machinery though front organization, all needed to be stopped.

So, assuming that from all indications, the policy was introduced as a deliberate "deep dive into chaos", here is the revised graphic.

The 4-1 dynamic or return to normalcy - the new normal - will take some time. For the moment, the control is very much with the political executive until the end-objectives are achieved (4).

REFERENCES

1. The Cynefin Framework; Cognitive Edge; [YouTube;11 Jul 2010]
2. Cynefin Framework; Cognitive Edge website; [Cognitive Edge ]
3. A leaders framework for decision making; David Snowden & Mary Boone; Harvard Business Review; Nov 2007 Issue
4. Understanding the Cynefin Framework - a basic intro; Julia Webster; Sep 29, 2013; Everyday Kanban website
5. Leadership and the Boiling Frog Experiment; Henna Inam; Aug 28, 2013; Forbes

Checking for creative accounting

When their operational parameters worsen, and the stress starts showing in the financial numbers, a lot of businesses try to be a little creative with their accounts so that investors don't take to their heels.
Can this creativity be detected through analysing the financial results that are released? Not with certainty, but as a probability, yes. What we have here is a probabilistic score that measures a company's resemblance to other companies where the accounting has been creative.

The Modified C-score tells the probability of financial manipulations based on the quantitative method. This has been developed by modifying James Montier's C-score using his six basic checks and further improving it by adding three more checks.

Score the firm based on these nine points by giving them zero or one in for each points based on qualification. Higher a C-score, the higher is the probability of financial manipulations.

Montier's C-Score is made up of six red signals.These are scored in a simple way, with a 1 for yes and a 0 for no. These are then totaled to give a final C-score ranging from 0 (no evidence of earnings manipulation) to 6.

The individual tests are:

1. Is there a growing divergence between net income and operating cash-flow? This is based on the simple observation that earnings can be inflated, but cash flows are hard to manipulate.
2. Are Days Sales Outstanding (DSO) increasing? When a company stuffs the dealer pipeline, this number increases.
3. Are days sales of inventory (DSI) increasing? A sign of slowing sales.
4. Are other current assets increasing vs revenues? Since managements know that DSO and/or DSI can be closely watched, they may use this to hide something.
5. Are there declines in depreciation relative to gross property plant and equipment? Companies may alter their estimate of useful asset life to enhance reported earnings.
6. Is total asset growth high? It has often been observed that high asset growth firms under-perform.

Additional checks

1. Are debtors as per cent to revenue increasing? This means that the company is selling more on credit and realising not cash.
2. Is assets quality improving or declining? Asset quality is measured as the ratio of non-current assets other than plant, property and equipment to total assets. Which means the company may have high non productive assets.
3. Is accrual ratio high or low? Total accruals calculated as the change in working capital accounts other than cash less depreciation. Accrual ratio gives the difference between the accrual accounting and cash actually made out of it. A high ratio means that there is high difference between the cash realised and earnings reported.

Flat-lined Agile

So you have implemented that shiny new Atlassian JIRA+Agile software on a shiny new cloud infrastructure, the system and processes are stable, the levels of enthusiasm from six months ago have ebbed, and it is back to business as usual.

Or is it?

Why have none of the HR policies changed?
Why are there no changed job descriptions?
Where are the promised new organizational roles?
Why is the organizational bureaucracy still in place?
Why are the micronarratives still the same?
Why is it doubly harder to get things done now?
Why have the number of meetings remained the same?
Why is there no significant jump in revenues?

Many organizations implement Agile like they would an ERP. That is, a core group trains on the selected software and run a pilot, the executive approves the spend and the system gets rolled out. At the end of the period of implementation everyone is "using" the software and all is well with the world.

Sounds familiar?

If the answers to any of the questions above leaves you blinking, your Agile initiative has flat-lined. Now is the time to get someone "on the outside" who can do an audit and make recommendations. It shouldn't take more than an hour for this outsider to let you know what went wrong.

The Agile Journey

Agile initiatives are long and exciting "journeys", that pass through multiple fascinating way points and changing landscapes, much like a trekking expedition through the high mountains.

You start at a low altitude.

You pass through the mid-altitudes

And you finally arrive at your destination peak

Does it end there?

Of course not. That's just the mid point.

You need to get back to civilization, tired, sun burnt, a few pounds lighter and yet with a new found confidence and camaraderie.

You are not done till it is done!

 The graphic above is indicative of that half way point - your objective. We start the journey at way point #1, passing through way points 2, 3, 4 etc until we reach our objective at #6. At #6, we are at "constraints maximum" on our Agile journey. All gaps, issues and changes needed would have been highlighted by the time the organization reaches this stage.

Then we have to get back!

It is a lot quicker in terms of the level of effort, but longer in time horizon. This is where most of the organizational learning happens. 

Unfortunately, most organizations are quite happy to sit at 6 and assume the implementation program is complete.

No!

That is just the half way mark.

You still need to find your way back.

Not the whole team, just the living core of the organization.

And the difference is that while your way point #1 was like being aboard a ship adrift, way point #9 is as precise as a street address. It is the new centre of gravity of the organization, designed to ensure the organization remains strategically poised to roll in any direction.

Confused? That's probably because of common perception that Agile resides in the system you finally implement.

Agile does not reside in the system you implement, it resides in nuances within the culture of the organization. Herein lies the crux of the challenge.

4 golden rules of handling complex events

Every Airbus pilot carries a little card on his person at all times. It simply enumerates the four golden rules to handling a system as complex as a modern airliner.

It made me wonder, given the complex nature of managing modern enterprises, whether these are relevant in our context and what useful lessons we can derive from it.

Let's look at each of these four golden rules, one by one.

1. Fly, navigate and communicate

Task sharing should be adapted to the prevailing situation and tasks should be accomplished in accordance with the following priorities:

•  Fly (Aviate): Pilot Flying (PF) must concentrate on flying the aircraft to capture and maintain the desired targets, vertical flight path and lateral flight path. Pilot Monitoring (PM), must back up the PF by monitoring flight parameters and by calling any excessive deviation.
• Navigate: Select the desired modes for navigation, being aware of surrounding terrain and minimum safe altitude. This rule can be summarized by th following three 'know where..." statements of situational-awareness:
• Know where you are
• Know where you should be; and,
• Know where the terrain and obstacles are
• Communicate: Effective crew communication involves communications between flight crew and controller, between flight crew members and between flight crew and cabin crew. Communication allows sharing of goals and intentions, and enhancing crew's situational awareness. 

Of course, managing the continuation of the flight is always the "operational" priority, and this includes:

• Managing aircraft systems; and
• Performing applicable emergency and/or abnormal procedure(s).

Takeaways

Managing modern enterprises is quite akin to managing modern airliners. The primary difference lies in the system response time. In modern fly-by-wire airliners, every known contingency and an idealized response is programmed into the flight management computers (FMC) to keep it safely within the performance envelope. But the pilots may choose to ignore, reduce or even take manual control when required, overriding the systems. Humans remain the ultimate arbiter. And the aircraft responds immediately to control or other inputs.

In enterprises, the equivalent of the pilots is the executive, and the FMC is the management tier. And while many processes are systematized, giving the management a dashboard view of critical enterprise parameters, corrective actions take time as all such input needs to be communicated to the management or supervisory level, who then implement or execute the task. Unless of course, it is a known event in which case, it is operationalized at the appropriate management, supervisory or employee/worker level. Feedback, however, is not real-time. Yet, within a "reasonable period", ranging from a few hours to a few weeks, the effect of control inputs begin to show.

Enterprise events have varying degrees of uncertainty. What you most definitely want to do is to operationalize all of the most obvious event handling processes. And these encompass most of a modern enterprises operations functions including Sales & Marketing, Finance, HR, IT etc. Events that these functions handle are mostly routine, with best practices emerging over time and with team experience.

Above the most obvious, events need to be analyzed before suitable course of action can be determined. This is the domain of middle management in most organizations. Above this lies the domain of complex events, where cause-effect relations, hence organizational response, is not self-evident. These events need experimental probing to determine what works and what does not work, and is thus the domain of senior management.

Beyond the complex, is the domain of Chaos, which companies hope they never have to face and yet occur more frequently in a volatile, ambiguous world. Maturity, experience and the ability to act immediately and decisively are the hallmarks of leaders who manage events in this domain. The desired outcome is a contained situation, simplified and moved back to complex or complicated domain so that senior managers can take charge, define new processes and systems and gradually institutionalize the learning from such events.

2. Use the appropriate level of automation at all times

On highly automated and integrated aircraft, several levels of automation are available to perform a given task. The correct level of automation depends on the task the be performed, the flight phase and time available. The correct level of automation is often the one the pilot feels the most comfortable with, depending on his/her knowledge and experience of the aircraft and systems, skills and confidence. To summarize:

• Understand the implication of the intended level of automation
• Select the intended level
• Confirm the aircraft responds as expected

This leads us to Golden Rule #3.

Takeaways

Appropriate level of automation - there is real beauty in this rule! Of course, it implies that you cannot always rely on data if other indications are contradictory. So what do you do?

You are expected to take manual control of those "in doubt" parameters until a resolution is reached. It indicates events, potentially outside the performance envelope, hence accompanied by high risk.

But then, the human mind is only capable of juggling so many variables. Any more variables beyond this threshold, and you reach a condition commonly referred to as analysis paralysis, or decision paralysis. The trick is in knowing which signals or data to rely on and which to ignore, until you can determine a course of action.

So what is situation normal?

While operations sits firm in the domain of the Obvious (where Rule #1 is applicable constantly), the governance should be at the boundary between complicated and complex, with adequate leeway and authority given to mid-level and senior managers to experiment.

Experimentation costs. So it is not just sufficient for the Executive to delegate experimentation authority, it should be backed-up with sufficient resources in terms of people and funding. Indeed, at any given time, multiple, parallel, safe-to-fail experiments would be in progress with the executive monitoring, and available for both mentoring and advice while retaining the option of stepping-in if needed. 

However, there is a critical difference. Even while the PF can take partial to full control by applying the appropriate level of automation, the system as a whole continues to monitor a whole host of other critical parameters.

These sensors send data to the FMC where it is processed continuously, and it also continues to responding appropriately within in-built tolerances, and where it exceeds these tolerances, flashes appropriate notification to the pilots.

This is the event handling, and exception handling and escalation mechanism of organizations, a part of the governance structure.

But what happens when events lie outside the performance envelope of the organization? These unknown-unknowns, as it is referred to in risk management?

This factor highlights another essential difference between airliners and organizations. Most of the design of an airliner happens upfront. That is, the design effort is front loaded. Whereas in the case of organizations, the initial design of the structure and dynamics evolves continuously to market and competitive actions.

One would therefore imagine that organizations would have the ability to monitor many more parameters than airliners. And since the events it needs to handle over its lifetime (read in perpetuity), it would continuously be designing and deploying sensors to monitor new events both within the organization, and outside, in the environment.

In reality however, this is where most organization fail. A sensor in an organization is comprised of its people, processes and systems. The active directive element is always a human. The sensing workload is continuous, ubiquitous and overwhelming.

Yet managers rarely give sufficient thought to designing and implementing sensors or governance structures that can facilitate fast feedback as well as its evolution. Neither do they co-opt the entire organization into this process. It is not difficult to discern the reasons why. In the operational domain, people rarely have the time to focus on anything outside their narrow briefs. Their entire workload has a time horizon of here and now.

How then can they be brought into the fold as discerning, effective sensors? Yes, it needs a different level of capability, and talent. That is a problem that unfortunately has been fully delegated by the Executive to the HR function who merely refers to it as the talent shortage.

So what do they - the HR's talent acquisition sub-function - do? They have targets, so they compromise. They compromise on the "good-to-have" job criteria in order to meet the numbers with just the threshold "must have" capabilities.

It is benign neglect by the executive, and mediocrity by design. And this unfortunately brings with it a level of complacency as it solves the immediate problem, relegating future needs to a later date.

While most HR systems test all threshold criteria, modern HR management insists on testing three levels of skills or competence and aptitude - one that is immediately needed, one that can provide differentiation and one that will be needed in the future.

Nearly 80% of job-seekers will only have varying levels of competency in threshold skills. About 15-18% will have differentiating skills and a miniscule 2-5% will have the basic skills and aptitude for the organization's emerging needs, that is, skills that are immediately utilizable to shape the organizations future. 

3. Understand the FMA* at all times

The Flight Mode Annunciator (FMA) is the feedback mechanism on such aircraft, the manner, so to say, in which the aircraft speaks to the pilots.

The panel of a modern jetliner.
FCU is the knobby unit (orange highlights) above the row of glass displays 

 All inputs to the Flight Control Unit (FCU) should immediately be crossed checked with the FMA or data on other displays.

FMA (boxed in yellow) above on the PFD

Any anomaly may indicate a major problem as this article highlights. At all times, the PF and PM should be aware of:

• The armed or engaged modes
• The guidance targets set
• The aircraft response in terms of attitude, speed and trajectory, etc
• Any mode transitions or reversions.

To sum up:

• Monitor your FMA
• Announce your FMA
• Confirm your FMA
• Understand your FMA

And if any problem occurs, refer to Golden Rule #4.

Takeaways

The most obvious notifications to the executive are issues being escalated by managers. More the centralization of decision making, more the escalated issues.

Outside of formally escalated issues is the micro-narrative. This is the informal information that moves around social informal networks in the organization - the gossip channels, the coffee group, the lunch group, discussions around the water-cooler. This is the pervasive undercurrent and is an element of culture.

While formal notifications are the tip of the iceberg, the micronarrative is the whole iceberg! It is that important. And culture determines whether the executive is even in the loop of what is propagating in the organizational gyre.

This aspect is critical enough to influence organizational performance. And to stick a probe into this information flow, the whole structure of governance needs to be redesigned ground up.

4. Take action if things do not go as expected.

This is straightforward. If the aircraft does not follow the desired flight path or target, the crew should react without delay:

• By PF changing the level of automation:
• From managed guidance to selected guidance
• From selected guidance to manual flying or
• By PM taking action:
• Questioning, and if that is not enough
• Challenging, and if that is still not enough
• Taking over

In abnormal or emergency conditions:

• Understand the prevailing condition before acting
• Assess the risks and time pressure
• Review and evaluate the available options
• Match the response to the situation
• Manage workload
• Create a shared problem model with other crew members
• Apply recommended procedures and other agreed solutions

Takeaways

Rule #4 is about preparing the organization for a crisis. Both the Board and the Executive suite will be well seized of this, however, in most organizations, the structures needed to handle crisis is either poorly developed or non existent.

This is the Chaos domain events and occurs when events occur outside the performance envelope of the organization.

It is also the domain in which the maximum learning occurs, albeit, a little too late for some organization to survive as amply demonstrated by the likes of Enron, Worldcom and some Wall Street icons like Lehman Brothers and Merrill Lynch.

The crash of 2008 is a classic Level 4 event when the entire financial world teetered at the edge of chaos, with many of the "too-big-to-fail" institutions only being saved in the nick of time by state intervention.

What is critical here is quick, visible and decisive action, to the exclusion of almost all other considerations.

Conclusions

There is no doubt that the four golden rules are very much applicable in the world of enterprise, often to a larger range of variables.

In designing machines, even as sophisticated as modern airliners, one can not only define a desired performance envelope, but also build in mechanisms to respond to a large number of variables.

Enterprises on the other hand, need to be perpetually on the drawing board even while being in operation. This calls for a very different talent pool from the one that is currently available with most organizations.

So how can organization respond and create a pool of talent to handle the spectrum of potential events? The path forward appears to lie in open organizations with a global talent pool.

Already, in the more advanced economies, the trend indicates a greater reliance on outside pool of contract workers providing a specialized set of skills for a defined period of time.

And when the need passes, contracts can be terminated and new talent can be onboarded. Some of the competencies of the contract workforce gets transferred to employees thereby enriching the in-house pool. The mix today is already at 60-40. It won't be long before this inverts to 40-60.

And as the Golden Rules underlines, remember to always...

Fly the aircraft.........Fly the aircraft..........Fly the aircraft

Fragile Agile

At an annual leadership summit of a $100 billion conglomerate, the chief executive exhorted the groups top managers and its 600,000 employees to be more agile both at a strategic and an organizational level, and identify opportunities with a sense of urgency.

Quite obviously, the Chief did not have Scrum or any of the many other Agile Methodologies in mind. So what exactly did he mean by encouraging his managers to be agile at the "strategic and organizational levels"?

At the strategic level, it simply means the nimble-footed capacity of the organization to seek new paths, or new opportunities to expand and seed new businesses in a fast changing environment. That implies an evolved and facilitating leadership style, the availability and quick access to capital, as well as a deep tolerance for entrepreneurial experimentation and failure.

At the organizational level, it meant creating the necessary structure and culture that nurtures merit and entrepreneurship, one that is alert to the subtle and not-so-subtle changes in the competitive environment, and has developed the capacity to dynamically orient and adapt to change using a bottom-up approach. It means staying on top of emerging business technologies while blurring the boundaries between departments, verticals and businesses.

At the team level, it implies adopting one or the other suitable Agile Methodology. At this level, the practice is fairly developed, though because of its narrow organizational scope, 75% of organizations will not succeed in getting the benefits that they hope will materialize from the transition.

Does an Agile Transformation change organizations as we know it and the manner in which it operates?
Yes! Fundamental to this change is inculcating the leadership ability and organizational capacities for complexity management. It also implies deconstructing the hierarchy into sets of self-organizing, independent team nodes, and then to single-person nodes and allowing the organization to rebuild into a network structure through emergence. Part of the existing hierarchy - the bureaucracy needed for due diligence and governance - will continue to co-exist, in parallel with the network, with formal or informal linkages between the two structures.

What is that and what does it entail?
It challenges the common understanding that a few people at the top of the organization will have all the solutions, the only solutions, which they will then give to other people who are in charge of implementing it. It implied that the organization was heavily dependent on the limited cognitive and information processing capability of a few people at the top of the hierarchy. It also reduced the capacity of the majority of the organization's members to act autonomously, innovate and respond to local level information.

To overcome that, transformation programs have to be done at three levels - team, business and strategy. Each of these work-streams will progress through three overlapping stages in the preliminary phase with the objective of resolving and streamlining communication and coordination issues at functional interfaces while teams transition to one or the other established agile methodology.

All post agile transition surveys point to one fact - that the ability to change organizational culture is the biggest stumbling block - much more than a general resistance to change. If that be the case, the attempt to change the culture of just one or two of the many business functions will result in failure. This is simply because, the targets of a Level 1 transition (usually technical teams) are not the repository of organizational culture. If one has to overcome the culture barrier, the scope of the Agile initiative would necessarily have to be organization wide.

Yet, it cannot all be done at once. It requires careful choreographing the progress of the initiative taking intangibles such as competence of individuals, availability of key personnel and the incidence of critical events. This single failure to make the scope of Agile initiatives organization wide is what makes Agile fragile.

And what is often forgotten in the hurly-burly of an Agile transition is the end objective of the program

In qualitative terms, it is about adaptability, business sustainability, managing business complexity, and making strategy everyone everyday business and creating the requisite structure that facilitates it.

In quantitative terms, it is primarily about a quantum jump in revenue  or other hard metric. If an Agile transformation does not result in a 30-40 % or greater jump in revenue, with an ROI period of less than 12 months, rest assured, it can safely be classified a failure.

It appears to work for a while, and everyone is excited. Then the cracks appear, projects or teams are given a "one-off exception" to drop agile temporarily and return once their project or other such activity is completed.

That is classic fragile Agile. And unfortunately, in a majority of the cases, this fragmentation is usually facilitated by the executive suite.