SCENARIO-BASED MODELLING: Storytelling our way to success. 1

“The soft stuff is always the hard stuff.”

Unknown.

Whoever said ‘the soft stuff is the hard stuff’ was right.  In fact, Douglas R. Conant, coauthor of TouchPoints: Creating Powerful Leadership Connections in the Smallest of Moments, when talking about an excerpt from The 3rd Alternative: Solving Life’s Most Difficult Problems, by Stephen R. Covey, goes on to note:

“In my 35-year corporate journey and my 60-year life journey, I have consistently found that the thorniest problems I face each day are soft stuff — problems of intention, understanding, communication, and interpersonal effectiveness — not hard stuff such as return on investment and other quantitative challenges. Inevitably, I have found myself needing to step back from the problem, listen more carefully, and frame the conflict more thoughtfully, while still finding a way to advance the corporate agenda empathetically. Most of the time, interestingly, this has led to a more promising path forward and a better relationship, which in turn has made the next conflict easier to deal with.”

Douglas R. Conant.

Conant is talking about the most pressing problem in modern organisations – making sense of stuff.

Sense Making

Companies today are awash with data.  Big data.  Small data.  Sharp data.  Fuzzy data.  Indeed, there are myriad software companies offering niche and bespoke software to help manage and analyse data.  Data, however is only one-dimensional.  To make sense of inforamtion is, essentially, to turn it into knowledge. To do this we need to contextualise it within the frameworks of our own understanding.  This is a phenomenally important point in sense-making; the notion of understanding something within the parameters of our own metal frameworks and it is something that most people can immediately recognise within their every day work.

Contextualisation

Take, for instance, the building of a bridge.  The mental framework by which an accountant understands risks in building the bridge is uniquely different from the way an engineer understands the risks or indeed how a lawyer sees those very same risks.  Each was educated differently and the mental models they all use to conceptualise the same risks (for example)  leads to different understandings.  Knowledge has broad utility – it is polyvalent – but it needs to be contextualised before it can be caplitalised.

Knowledge has broad utility – it is polyvalent – but it needs to be contextualised before it can be caplitalised.

For instance, take again the same risk of a structural weakness within the new bridge.  The accountant will understand it as a financial problem, the engineer will understand it as a design issue and the lawyer will see some form of liability and warranty issue.  Ontologically, the ‘thing’ is the same but its context is different.  However, in order to make decisions based on their understanding, each person builds a ‘mental model’ to re-contextualise this new knowledge (with some additional information).

There is a problem.

Just like when we all learned to add fractions when we were 8, we have to have a ‘common denominator’ when we add models together.  I call this calibration, i.e. the art and science of creating a common denominator among models in order to combine and make sense of them.

Calibration

Why do we need to calibrate?  Because trying to analyse vast amounts of the same type of information only increases information overload.  It is a key tenent of Knowledge Management that increasing variation decreases overload.

It is a key tenent of Knowledge Management that increasing variation decreases overload.

We know this to be intuitively correct.  We know that staring at reams and reams of data on a spreadsheet will not lead to an epiphany.  The clouds will not part and the trumpets will not blare and no shepherd in the sky will point the right way.  Overload and confusion occurs when one has too much of the same kind of information.  Making sense of something requires more variety.  In fact, overload only increases puzzlement due to the amount of uncertainty and imprecision in the data.  This, in turn, leads to greater deliberation which then leads to increased emotional arousal.  The ensuing ‘management hysteria’ is all too easily recognisable.  It leads to much more cost growth as senior management spend time and energy trying to make sense of a problem and it also leads to further strategic risk and lost opportunity as these same people don’t do their own jobs whilst trying to make sense of it.

De-Mystifying

In order to make sense, therefore, we need to aggregate and analyse disparate, calibrated models.  In other words, we need to look at the information from a variety of different perspectives through a variety of lenses.  The notion that IT companies would have us believe, that we can simply pour a load of wild data into a big tech hopper and have it spit out answers like some modern Delphic oracle is absurd.

The notion that IT companies would have us believe, that we can simply pour a load of wild data into a big tech hopper and have it spit out answers like some modern Delphic oracle is absurd.

Information still needs a lot of structural similarity if it’s to be calibrated and analysed by both technology and our own brains.

The diagram below gives an outline as to how this is done but it is only part of the equation.  Once the data is analysed and valid inferences are made then we still are only partially on our way to better understanding.  We still need those inferences to be contextualised and explained back to us in order for the answers to crystalise.  For example, in our model of a bridge, we may make valid inferences of engineering problems based on a detailed analysis of the schedule and the Earned Value but we still don’t know it that’s correct.

Storytelling

As an accountant or lawyer, therefore, in order to make sense of the technical risks we need the engineers to play back our inferences in our own language.  The easiest way to do this is through storytelling.  Storytelling is a new take on an old phenomenon.  It is the rediscovery of possibly the oldest practice of knowledge management – a practice which has come to the fore out of necessity and due to the abysmal failure of IT in this field.

Scenario-Based Model Development copy

Using our diagram above in our fictitious example, we can see how the Legal and Finance teams, armed with new analysis-based  information, seek to understand how the programme may be recovered.   They themselves have nowhere near enough contextual information or technical understanding of either the makeup or execution of such a complex programme but they do know it isn’t going according to plan.

So, with new analysis they engage the Project Managers in a series of detailed conversations whereby the technical experts tell their ‘stories’ of how they intend to right-side the ailing project.

Notice the key differentiator between a bedtime story and a business story – DETAIL!  Asking a broad generalised question typically elicits a stormy response.  Being non-specific is either adversarial or leaves too much room to evade the question altogether.  Engaging in specific narratives around particular scenarios (backed up by their S-curves) forces the managers to contextualise the right information in the right way.

From an organisational perspective, specific scenario-based storytelling forces manages into a positive, inquistive and non-adversarial narrative on how they are going to make things work without having to painfully translate technical data.  Done right, scenario based modelling is an ideal way to squeeze the most out of human capital without massive IT spends.

 

 

 

 

 

Is it really OK to bash HR? Reply

In a recent article in Forbes magazine online, Ron Ashkenas wrote a heartfelt piece on how essential the Human Resources function is in response to recent HR bashing.  He wove a lovely story of  how critical the function is, how deeply misunderstood its people are and how we should all band together to help this function succeed.

HR Survey. Mckinsey

The idea that we should all club together to support a non-operational function outside both our remit and remunerative motivation is farcical.  The truth is twofold:  (i) Firstly, bad hires come from bad specifications.  HR cannot be blamed for finding the wrong person that a business unit specified.  (ii) Secondly, HR needs to force the various business units to communicate their needs proactively and pre-emptively.

There is often a lot of subtext, contextual knowledge and peripheral information which comes along with requests for a new hire.  Internal HR managers need to get analytical if they are going to remain relevant and not cede their function.  If they fail to grasp the cost and revenue interdependencies of various roles then external boutique consultancies will thrive.  These companies will analyse, assess and source the best talent.  There will be a premium on this cost and it will ultimately be funded by removing more internal HRs.

Soccer TeamThe research tells a story.  In a recent survey by Mckinsey, CEOs identified the top 8 barriers to talent acquisition and management.  At the top of the list was the failure of senior management to spend enough time on HR.  This is not HR’s fault but that the blame lies with HR is topical.  Another factor was perceived to be the failure of managers to understand that good people are good for good business.  Good people execute strategy well.    The secret to this is understanding (a) the structural roles which people satisfy that are vital to the effective functioning of the business, and (b) the functional knowledge which is inherent in executing those roles.

In a recent post I wrote about the likely demise of internal HR and the rise of boutique consultancies which had the skills to analyse, assess and source talent.  Internal HR is better placed to deliver this role better and more cost effectively.  They should know and understand the people, they should understand the dependencies, they should have a clear understanding of contextual knowledge and they should also be able to bolster the role specs with additional peripheral information. Critically, managers need to know which position which their staff play.  Without this understanding businesses looks like an under-12 soccer team where everyone is chasing the ball.

 

The Complexity of Cost (Pt.1): problems with ICT cost reduction Reply

cost reduction

In a crisis the company P&L statement can be a useful starting point for cost reduction programs.  Over the long term, however, general ledger entries do not have the required level of detail to garner the requisite per unit analysis (McKinsey, May 2010).  Unfortunately, few companies do not have systems which can analyse the complexity of cost and spend in order to make accurate and detailed changes.

In the following series of blogs we will highlight the problems with standard ICT cost reduction & management programs and detail how to structure and run one effectively.

The key to an effective ICT cost reduction & management program is detailed cost modelling.  Most financial systems do not capture costs at the right level of detail for businesses to perform accurate and detailed cost reductions.  Businesses need to perform intricate spend analyses and build up intricate cost models for ICT which highlight the following:

  • The capabilities which various ICT components support (and where in the Value Chain they lie).  Only through this level of visibility can the business consolidate their ICT spend.
  • The HR and process dependencies which are indirectly attributed to various ICT elements.  Only with this level of detail can ICT remove duplication and redundancy.

In the absence of this granularity, cost reduction programs invariably fail or fail to stick.  In fact, McKinsey & Co note that 90% of cost reduction programs fail.  Only 10% of these programs actually succeed in realising sustained cost management three years on.

In a typical IT cost reduction cycle the following happens:

  • Headcount is reduced.  The remaining people then have to work harder (but with fewer skills, because tasks are pushed to the lower pay bands) to achieve the same amount of work.
  • Many, often unique, soft skills are also removed (from experienced people in the higher pay bands) in the redundancies.
  • Overall service levels decrease.
  • Further cost reductions are then required and some applications and services are axed.

In simple businesses this is not a problem.  In large and complex businesses the outcome usually follows a vicious cycle, namely:

  1. The firm still needs to retain a significant management overhead in order to deal with complexity.
  2. In these cases, poor transfer pricing and high overhead allocations mean that perfectly good, competitive core business process seem cost-ineffective.
  3. Critically, Kaplan notes in his seminal work “Relevance Lost: The Rise and Fall of Management Accounting” that the increased costs of  processes leads to outsourcing of perfectly good processes.
  4. Capability suffers and the  business loses competitive advantage.
  5.  The business is no longer able to deal with the level of complexity and complexity reaches an inflection point.  The business outsources the whole problem (eg, large ERM programs with much customisation),  getting locked into  horrific terms and conditions.
  6. Core business is lost and competitive advantage is reduced. Remaining managers pad out their budgets with excessive risk and contingency in order to shield themselves from further cost reductions.
  7. Overheads increase again and the business eventually prices itself out of the market.

cost reduction.accenture

In a recent (2010) Accenture survey on general cost reduction effectiveness in the banking industry, 40% of  respondents noted that the program has reduced overall ICT effectiveness and impacted adversely on both customer service and general management.

in order to reduce costs effectively without impinging on capability as well as making new costs stick, it is essential to view costs and spend at the most granular level possible.

In our next blogs we will go into detail how to structure and run an effective ICT cost reduction and cost management program including effective ICT cost modelling.

 

The Social Enterprise: what will business 2.0 look like? Reply

social-enterprise

If Andrew McAfee‘s book “Enterprise 2.0: New Collaborative Tools for your Organization’s Toughest Challenges” is to be believed then:

“We are on the cusp of a management revolution that is likely to be as profound and unsettling as the one that gave birth to the modern industrial age. Driven by the emergence of powerful new collaborative technologies, this transformation will radically reshape the nature of work, the boundaries of the enterprise, and the responsibilities of business leaders.”

Most pundits believe that Enterprise 2.0 is the full adoption of Web 2.o by an organisation.  In the next few years, therefore, we will see:

  • Cloud technologies and better enterprise application security enable bring-your-own-device and with it the greater fragmentation of organisational information.
  • Greater transparency of organisational work through social media leaks (i.e. people advertising their work and mistakes on the internet)
  • The decomposition of many more business processes into micro-tasks (much of which can be outsourced or contracted out).
  • The improvement of distributed working practices enabled by better collaboration tools, devices and connectivity.
  • Increased pace of business through improved self-governance and, in turn, empowered by better oversight (from GRC and finance software to more pervasive CRM implementations).
  • Shorter time-to-market cycles driven by improved idea generation and organisational creativity (so called – ‘ideation’).

So, is Enterprise 2.0 the social enterprise?  Are the benefits of Enterprise 2.0 merely social?  Simply a more hectic work schedule enabled by greater ease of using mobile devices and tighter communities of practice?

McKinsey Social Enterprise

A 2010 survey by McKinsey & Company found that most executives do believe that this is the sum total of Enterprise 2.0 benefits.  Most simply believe that (i) knowledge flow and management will improve.  Many believe that (ii)  their marketing channels will be greatly improved whilst only a few believe that (iii)  revenue or margins will increase in the networked enterprise.

If this is the dawn of the new enterprise then why do so many large businesses find it difficult even to implement Microsoft SharePoint?

The most likely truth is that this is not the dawn of Enterprise 2.0.  We are probably not on the cusp of a grand new age of information work.  Our businesses are unlikely to change significantly, although the hype will be re-sold by IT vendors for some time. One only has to hearken back to the ’80’s to remember to cries of the ‘paperless office’ to realise the low probability of Enterprise 2.0 materialising.

Whether it will be Enterprise 2.0 is debatable but we are entering the age of  The Social Entreprise.  It has ushered in a new age of commercial culture but it will unlikely herald a paradigm shift in commercial structures.  The truth is that human networks and communities operate in parallel to corporate reality.  Networks are how humans interact  – they are not how humans are paid.  Ask anyone who has ever been through or performed a cost reduction exercise.  In short, emerging social software platforms (ESSPs) are fun and sexy but the do not currently affect operations in most businesses.  Emerging social software platforms will make a difference internally when they affect cost structures and not just when they show up in sales figures.  This means that ESSPs need to be able to track and apportion innovation; they need to actively manage workflow (not just passive engines); they need to engage dynamically in governance and highlight good corporate participation and collaboration.   Only once these elements are incorporated into scales of remuneration and talent sourcing will both the enterprise and the workers benefit.

Maybe then we can move to Enterprise 3.0.