Risk Management is routinely asked for on big projects and it inevitably ends up as a big process of hierarchies of spreadsheets or a database that identifies the risk, the potential impact and ways to mitigate it. I have seen many systems, and also seen many project and programme managers pay lip-service to them, by filling in either the bare minimum, or populating it with racing certainties! E.g. ‘Lack of resources’; This is not a risk, it is a management decision.

Yet, as far as software programme management is concerned, for any new development featuring any form of novelty (product, technology, architecture, people, organisation), risk management should be one of the key tools for planning the programme.

Significant risks are, actually, usually pretty obvious… and a browse through the system requirements by someone with even little appreciation of the project, and little experience, will quickly identify the major issues that are likely to have big impacts. Once the big issues are addressed, there will be a much greater number of lesser issues which may take more expertise to assess with regards investment of ‘mitigation’. Iterating this process quickly drops you into the usual ‘noise’ of typical project variation.

Where the risk responsibility lies is often a key factor, in getting authority to address it. It is rare that big impact risks exist within a single discipline (and if it does the technical discipline manager is usually loathe to admit he doesn’t know the solution). These factors make declaring risk unattractive to some practitioners and may put the project and business at risk.

Investing in ‘experiments’ is really what risk management is about. When you don’t understand the science well enough to have some suitable engineering solution that has provenance, you create a task, switch from engineer to scientist (but with a focus on a particular problem), and look for possible solutions, or to gain some understanding, that allows you to mitigate, avoid, control or at least ‘size’ the problem and the effort required in solving the same.

But there is absolutely no point in defining and executing experimental tasks, if the learning is then not applied, in a timely fashion, to your real project. Classical failures in risk management are:

i)                    Doing the experiment too late, or on the project when eventually encountered

ii)                  Not using the information gleaned from the experiment to modify the programme, or product

iii)                Failing to understand the underlying science that creates the risk, such that mitigation actions can be assessed

iv)                Adding extra complexity, further technology risk or unproven processes in the solution

Often risk reduction programmes require trades between different parts of the system and need multi-discipline skills. Often these will be executed with third parties who have a better understanding of the underlying science, or an ability to think more openly (e.g. academic researchers and institutions).

Technology development programmes are inherently risk management/risk reduction exercises and show a maturity of the business in tackling the problem ahead of bidding a programme that deploys the technology in question.

Embedded software in control and information systems say, is practiced by a wide community of businesses but is largely protected as intellectual property within those businesses (and often inside individual business units). It is fair to say, that most problems in software will probably have already been encountered, and in most cases a solution exists, but others will be unaware.

Even if solutions don’t exist there is potential for finding partners who face that common problem to share the burden of finding a solution. These issues will be the subject of a further instalment, but the general principles of Industrial Collaboration can be found here.

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Previously we talked about Planning and Estimation. These estimation techniques are traditionally used at the beginning of a project, but are immensely useful as periodic techniques for measuring progress.

We observed that during the generation process, we also create errors, whose correction is a generation process and so on. In good programmes this recursion is finite, and measurement of the number and rate of iterations, and their place relative to plan, can provide us with key progress and  process indicators.

By observing the number of versions of a component generated (information drawn from the version control system) and relating it to the (programme plan) planned timing, you can understand when errors are being detected/corrected. If this has more iterations than you expect, the component may be too complex or the developer immature, say. If those iterations occur later than the plan, then the component development may be running late, or be insufficiently tested (which may be a fault of either development or test environment).

These trigger signal can usefully lead us to investigate the component, the development /test environments or the skills of the members of the team. If several components are assigned to the same team members the skill association may be evident; if all components, irrespective of team members, show the same propensity for iteration rates then it is likely the processes or environment is inadequate.

Software programme management is about identifying and fixing root causes of deviation to programme, rather than just about progress chasing. The manufacturing stages of software engineering are its processes and a careful watch should be maintained on both input quality and output as a measure of the process’ efficacy. Resource levels, skill requirements and lean processes are outputs from running a software programme that can be re-used as seed for a new programme, or for ensuring realistic planning of the programme.

Earlier we showed that understanding where errors should be detected is key to planning. For instance, a self-contained component with a simple interface (e.g. a Maths function), would expect to be error free very close to generation; A message transport protocol, that relies on the interaction of 2 different pieces of hardware, and a series of lower level protocol stacks, is unlikely to be error free until significant system test.

Early development effort (in creation of error free components) should major on ‘infrastructure’, i.e. the primitive components and functions that are used by all other features. Failing to sufficiently test these components may seriously hamper future progress at higher levels of application.

Having a ‘slick’ change mechanism, that is suitably controlled, makes the development productive and efficient. No other process stage needs as much effort at being lean. Instrumenting this change process will provide all the valuable information from which the above metrics can be extracted and compared with the ‘expectation’ implied in the plan.

Careful control is required to differentiate causes of change, e.g. internal due to errors in implementation, refactoring due to not being able to accommodate a previously unaddressed requirement, or externally driven change. All will impact your development effort, but the project manager should have contingencies for the first two and be able to negotiate cost, programme etc changes for the last (even if still internal!). No change is for free, even scope reduction can cost money in a programme in which design effort has already been expended.

Now all you have to do is convince the business that your estimates and contingency are correct, including a statement on the assumed requirement that is addressed, and defensible, by reference to previous metrics and adjustments for the success or lack thereof on previous programmes.

Finally, it is never acceptable to arbitrarily cut costs or programme duration without a commensurate change in scope, skill capacity and capability, or risk.

___________________________________________________________________________

Let us help you maximise the business potential of your product and its software

Email me on stuart.jobbins@sofintsys.com

Visit our website, or follow us on your preferred Social Media for our latest views.     ___________________________________________________________________________