Tag Archives: New Normal

Planning should not require a Gantt chart

There’s a standard slide in my bag of tricks which finds it’s way into a surprising number of presentations. It’s a simple slide, one allowing me to explore the idea of planning as a spectrum of possible methodologies rather than treating planning as an either-or choice: either be bottom-up reactive, or requiring us to engage is a major top-down planning processes. By combining elements of both top-down and bottom-up approaches we can modulate how reactive, or how proactive and predetermined, our execution is. The idea is to set the slider where we want it, at the position that best suits what we are trying to achieve, instead of being forced to one end of the spectrum or the other in a purely reactive or purely deliberative mode.

A slide for our times
A slide for our times

Planning has a bad name. How many projects get stuck in that endless spiral of planning (and re-planning) as they try to find their way to the middle of the project hedge maze? It doesn’t seem to matter if we’re planning the expansion of our business into a new geography or a major IT transformation, the process drives us all nuts; wasted days and nights spent constructing (and then deconstructing and reconstructing) elaborate Gantt charts which we’re all sure will never be used.

All of this runs counter to what could be called the first rule of management:

Make a timely decision, and then make it work.

Most organisations’ first thought is to focus on being reactive and deal with the problems of here and now. Unfortunately this too has its own challenges. The Agile software movement can be seen as one well documented reactive methodology which has seen mixed success. Where time, scope and cost are negotiable, taking a reactive approach is the same as choosing to put scope up for grabs. The result of the project will be whatever the project manages to deliver, unsurprisingly. This might be enough to realise the original business case, or it might not.

A top-down, deliberative, approach is planning as a chess game (the untimed1)Types of chess games defined at Chess.net rather than the timed variety). We assume that we have complete information and can take as long as we want to formulate our next few moves. The more we know about our opponent — the more tacit knowledge we have about what might go wrong (and right) on a project — the better and more accurate our plans will be and the further into the future we can plan. We can measure and evaluate our current situation, use tools like scenario planning2)Martin Börjesson has put together some nice resources on Scenario planning to anticipate the future, or even hire an innovation consultancy to identify our next, disruptive move. In a perfect world the only limitation to our planning ability is our own ability to comprehend the problem at hand (or the number of tasks we can cram into a Gantt chart, whichever comes first).

The problem is the unexpected — the unpredicted (and possibly unpredictable) event — which makes our plans unravel. It’s the event that we didn’t manage to anticipate, invalidating our assumptions and converting a carefully crafted plan into wasted effort. The faster the environment changes the more likely it is that something unexpected will happen between the plan’s conception and the delivery of its final outcome. Even worse, we might not even finish planning before something unexpected pops up which invalidates our work to date, causing us to restart the planning process.

Take your average major IT transformation: a multiyear project involving a massive investment in both time and money. To kick-start the project we need to predict what the business will need when the transformation is finally delivered (and as I’ve said elsewhere, this is a challenge in itself3)I’ve already told you 125% of what I know @ PEG). If we’re lucky, then assumptions we’ve made about the business’s requirements will still hold true all the way through to the end. However, what’s more likely to happen is that the change orders will start arriving well before we’ve finished, possibly even we’ve completed requirements gathering. The team then struggles to divide their time between scheduled work and change orders before re-planning (and often re-planning again and again) to try and regain control of the project. Try as we may though, the end result is often more like coughing up a fur ball than the slick solution we originally imagined.

A reactive approach, on the other hand, doesn’t worry having about complete information. The focus is on reacting to events as they are encountered, with little thought to long term goals or strategy. A shotgun approach, as it were. We craft our strategy by creating a set of rules covering what we should do in all the circumstances we care about. See a stop sign? Stop. And so on. The challenge is to craft a set of rules which cover most eventualities, and this is a major focus of the “agile” methodologies. They try and craft their manifestos and playbooks to document the tactics — the rules — which they think will drive their projects in the right direction.

playbook [ˈpleɪˌbʊk]

  1. (Team Sports / American Football) a book containing a range of possible set plays
  2. a notional range of possible tactics in any sphere of activity

The American Heritage Dictionary of the English Language, Fourth Edition.

The unexpected is not a problem for a reactive approach: you simply deal with problems as they arrive. If you’re not expecting anything in particular, then whatever turns up must have been what your were expecting. (There is logic in there.) However, this puts you at the mercy of what does turn up; as you’re focused on reacting to events, the events which arrive (and the order they arrive in) determine where you end up. While cost and time (i.e. effort) might be fixed, scope (and therefor the final result) is up for grabs, making it hard to drive a reactive approach to planning to deliver a well defined outcome.

With it’s focus on incremental delivery and improvement, a reactive approach is not an obvious bedfellow for your major IT transformation. It’s modus operandi is to focus on shot term demands, understand what the business needs next, build that, and then iterate. The IT estate evolves (somewhat) organically as we add things here, patch things there, and generally muddle our way through. Yes, we are reacting to short term business needs, but at what cost? Its a bit like taking our hands off the tiller to leave ourselves to the mercy of the wind; our boat will probably stay afloat, as long as the weather isn’t too bad, but we have little control over where we end up. Without the ability to drive toward a clear, long term goal, we soon find that all the well meaning tactical decisions we’ve made have resulted in a giant fur ball, just like those occasions where we tried to drive the project forward with a giant Gantt chart.

Neither of these two approaches to planning are necessarily wrong; they’re just not suited to solve the sort of problems we’re dealing with in the new normal4)The new normal @ McKinsey Quarterly. They represent two extremes — proactive and reactive planning — but we need to balance proactive and reactive, and find a middle path.

First we need to admit that we’re resource constrained. This might be in terms of time, the funds we have available, or even simply the number of people we can usefully bring to bear on a problem. (As Frederick Brooks5)Frederick Brooks on the Mythical Man Month pointed, it might take one woman nine months to produce a baby, but we can’t expect nine woman to deliver a baby in one month.) And this is in an environment where meaningful business change is measured in months, if not weeks. The effort required to develop our plan needs to fit into the time available, and our approach needs to provide opportunities to regularly revisit our assumptions and allow us to react to changes within and without the project. We need need to be reactive, but not too reactive, as we need to work within an overarching framework so that we can have some confidence that we are working toward our long term goals.

People — that’s you and I — take a more pragmatic approach to planning. If we didn’t, then I couldn’t imagine that we would manage to make it through the day with everything we need to get done and the disruptions that we all deal with. Think about how you went to work this morning. (Or how you went to the local café for a coffee, if it’s the weekend.) You weren’t purely reactive. If you were then I expect you would still be lying in bed trying to sort out you manifesto and playbook, hoping for something to happen which will prod you in the right direction. Nor do you take an exclusively top-down, deliberative approach, popping open the laptop on your knee whilst in bed and firing up your favourite planning tool. You’d probably still be stuck in bed, working at the never-ending ending task of plotting exceptions and eventualities. (What should I do if the case of divine intervention?).

People take a middle road. We establish a clear goal, usually something quite prosaic, like:

Get to work (on time)

We have a clear understanding — a set of beliefs, things we expect to be true — of the context we need to do this in.

  • I’m lying in bed
  • it’s a weekday
  • the alarm has just gone off
  • the weather forecast was for a clear sky and sun
  • I’m feeling a bit pudgy today

We also have a library of plans — short patterns of behaviour — which we know that, either from experience or by design, will drive us toward our goal. For example, to get to work we might usually follow the pattern:

  1. get up
  2. shower
  3. get dressed
  4. eat
  5. commute to the office

where each of the steps in this pattern can also be goals themselves.

We might, for example, have a few different plans for commuting: one each for by car, by bike, via public transport, and so on. When it comes time to commute, we consider our beliefs (it’s sunny and I need the exercise) and choose what we think is the most suitable option (I’ll ride). If the option turns out to be a bad choice (one tyre on my bike is unexpectedly flat) or unsuitable due to some change in the environment (it starts raining when I’m less than a block from home), then you discard the plan and pick another (heading back to the garage to take the car). After all, we hadn’t invested much in developing or executing the plan so we’re not losing a lot by throwing it away.

The twisty path between us and our goal
The twisty path between us and our goal

The gap after each step provides us with time to pause and reflect, consider our goal, and respond to the environment by selecting how best to execute the next step. This ability to revisit our decisions frequently — at each step on the journey between the office and home — allows us to be reactive, but not too reactive, while the knowledge that each step is part of a large plan provides us with the confidence that we’re working toward our longer term goals. The more granular we make our plans the more opportunities we provide to react to changes in our environment, but at the cost of being less deliberative and proactive, and potentially less efficient. The more coarse grained we make our plans, the fewer opportunities we create for being reactive, by it allows us to be more deliberative and efficient in delivery.

By modulating the size of our plans — the size of the effort we commit to — we can set the slider where we want it on that planning scale, with reactive on one end, and top down deliberative. This lets us align our planning with the degree of uncertainty and change we’re seeing in the environment around us.

I’ve been using this approach to plan and manage business and IT strategies for some time, with a great deal of success. Most of the tooling required already exists in the business business world, tools such as strategy maps6)Strategy map defined @ Value Based Mangement by Kaplan & Norton, mission statements7)Mission statement defined @ The Centre for Business Planning, and project portfolio management tools. Using these tools we can clearly identify our goals, articulate the tactics we want to use to drive ourselves toward them, and then create a portfolio of work which realises the tactics.

For example, the mission of being a low cost service provider might result in a goal of having efficient operations (which we can measure via a benchmark), and the tactics we can use to deliver more efficient operations might include consolidation (reducing the number of offices, data centres, or event tools). We can realise this need for consolidation by identifying a set of small projects (such as shutting down a small data centre, and consolidating its servers into a major one), each of which delivers one step on the journey. These projects then become part of a larger portfolio of work, with the resources available and business priorities determining which projects are executed next.

Just like the example above of each one of us finding our way to work in the morning, this approach enables us to balance how reactive or proactive we are at any time. We can easily re-proritise in response to business change by updating the mix of projects to be executed, rather than through a major re-planning effort. At the same time, we can be sure that the portfolio of work is driving us toward our long term goals, as each project aligns with an organisational goal. Planning without a major Gantt chart.

References   [ + ]

1. Types of chess games defined at Chess.net
2. Martin Börjesson has put together some nice resources on Scenario planning
3. I’ve already told you 125% of what I know @ PEG
4. The new normal @ McKinsey Quarterly
5. Frederick Brooks on the Mythical Man Month
6. Strategy map defined @ Value Based Mangement by Kaplan & Norton
7. Mission statement defined @ The Centre for Business Planning

Some new rules for IT

The other week I had a go at capturing the rules of enterprise IT{{1}}. The starting point was a few of those beery discussions we all have after work, where we came to wonder how the game of enterprise IT was changing. It’s the common refrain of big-to-small, the Sieble to Saleforce.com transition which sees the need for IT services (internal or external) change dramatically. The rules of IT are definitely changing. Now that I’ve had a go at old rules, I thought I’d have a go at seeing what the new rules might be.

As I mentioned before, enterprise IT has historically been seen as an asset management function, a production line for delivering large IT assets into the IT estate and then maintaining them. The rules are the therefore rules of business operations. My attempt at capturing 4 ± 2 rules (with friends) produced the following (in no particular order):

[[1]]The rules of Enterprise IT @ PEG[[1]]

  • Keep the lights on. Much like being a trucker, the trick is to keep the truck rolling (and avoid spending money on tyres). Otherwise known as smooth running applications are the ticket to the strategy table.
  • Save money. Business IT was born as a cost saving exercise (out with the rooms full of people, in with the punch card machines), and most IT business cases are little different.
  • Build what you need. I wouldn’t be surprised if the team building LEO{{2}} blew their own valve tubes. You couldn’t buy parts of the shelf so you had to make everything. This is still with us in some organisations’ strong desire to build – or at least heavily customise – solutions.
  • Keep the outside outside. We trust whatever’s inside our four walls, while deploying security measures to keep the evil outside. This creates an us (employees) and them (customers, partners, and everyone else) mentality.

[[2]]LEO: Lyons Electronic Office. The first business computer. @ Wikipedia[[2]]

Things have changed since these rules were first laid down. From another post of mine on a similar topic{{3}} (somewhat trimmed and edited):

[[3]]The IT department we have today is not the IT department we’ll need tomorrow @ PEG[[3]]

The recent global financial criss has fundamentally changed the business landscape, with many are even talking about the emergence of a new normal{{4}}. We’ve also seen the emergence of outsource, offshore, cloud computing, SaaS, Enterprise 2.0 and so much more.

Companies are becoming more focused, while leaning more heavily on partners and services companies (BPO, out-sourcers, consultants, and so on) to cover those areas of the business they don’t want to focus on. We can see this from the global companies who have effectively moved to a franchise model, though to the small end of town where startups are using on-line services such as Amazon S3, rather than building their own internal capabilities.

We’re also seeing more rapid business change: what used to take years now takes months, or even weeks. The constant value-chain optimisation we’ve been working on since the 70s has finally cumulated in product and regulatory life-cycles that change faster than we can keep up.

Money is also becoming (or has become) more expensive, causing companies and deals to operate with less leverage. This means that there is less capital available for major projects, pushing companies to favour renting over buying, as well as creating a preference for smaller, incremental change over the major business transformation of the past.

And finally, companies are starting to take a truly global outlook and operate as one cohesive business across the globe, rather than as a family of cloned business who operate more-or-less independently in each region.

[[4]]The new normal @ McKinsey Quarterly[[4]]

So what are the new 4 ± 2 rules? They’re not the old rules of asset management. We could argue that they’re the rules of modern manoeuvre warfare{{5}} (which would allow me to sneak in one of my regular John Boyd references{{6}}), but that would be have the tail wagging the dog as it’s business, and not IT that has that responsibility.

[[5]]Maneuver warfare @ Wikipedia[[5]]
[[6]]John Boyd @ Wikipedia[[6]]

I think that the new rules cast IT as something like that of a pit crew. IT doesn’t make the parts (though we might lash together something when in a pinch), nor do we steer the car. Our job is to swap the tyres, pump the fuel, and straighten the fender, all in that sliver of time available to us, so that the driver can focus on their race strategy and get back out on track as quickly as possible.

With that in mind, the following seems to be a fair (4 ± 2) minimum set to start with.

  • Timeliness. A late solution is often worse than no solution at all, as you’ve spent the money without realising any benefit. Or, as a wise sage once told me, management is the art of making a timely decision, and then making it work. Where before we could take the time to get it right (after all, the solution will be in the field for a long time and needs to support a lot of people, so better to discover problems early rather than later), now we just need to make sure the solution is good enough in the time available, and has the potential to grow to meet future demand. The large “productionisation” efforts of the past need to be broken into a series of incremental improvements (à la Gmail and the land of perpeputal beta), aligning investment with both opportunity and realised value.
  • Availability. Not just up time, but ensuring that all stakeholders (both in and outside the company, including partners and clients) can get access to the solutions and data they need. There’s little value in a sophisticated knowledge base solution if the sales team can’t use it in the field to answer customer questions in real time. Once they’ve had to fire up the laptop, and the 3G card, and the VPN, the moment has passed and the sale lost. Or worse, forcing them to head back to the bricks and mortar office. As I pointed out the other week, decisions are more important than data{{7}}, and success in this environment means empowering stakeholders to make the best possible decisions by ensuring that the have the data and functions they need, where they need, when they need it, and in a format that make it easy to consume.
  • Agility. Agility means creating an IT estate that meet the challenges we can see coming down the road. It doesn’t mean creating an infinitely flexible IT estate. Every bit of flexibility we create, every flex point we add, comes at a cost. Too much flexibility is a bad thing{{8}}, as it weighs us down. Think of formula one cars: they’re fast and they’re agile (which is why driving them tends to be a young mans game), and they’re very stiff. Agility comes from keeping the weight down and being prepared to act quickly. This means keeping things simple, ensuring that we have minimum set of moving parts required. The F1 crowd might have an eye for detail, such as putting nitrogen{{9}} in the tyres, but unnecessary moving parts that might reduce reliability or performance are eliminated. Agility is the cross product of weight, speed, reliability and flexibility, and we need to work to get them all into balance.
  • Sustainability. Business is not a sprint (ideally), and this means that cost and reliability remain important factors, but not the only factors. While timeliness, availability and agility might be what drive us forward, we need still need to ensure that IT is still a smooth running operation. The old rules saw cost and reliability as absolutes, and we strived to keep costs as low, and reliability as high, as possible. The new rules see us balancing sustainability with need, accepting (slightly) higher costs or lower reliability to provide a more timely, available or agile solution while still meeting business requirements. (I wonder if I should have called this one “balance”.)

[[7]]Decisions are more important than data @ PEG[[7]]
[[8]]Having too much SOA is a bad thing (and what we might do about it) @ PEG[[8]]
[[9]]Understanding the sport: Tyres @ formula1.com[[9]]

While by no mean complete or definitive, I think that’s a fair set of rules to start the discussion.

People don’t like change. (Or do they?)

I seem to be having a lot of conversations at the moment around whether people (you, me and everyone else) like and embrace change, or whether they resist it. The same question arises for companies. Like a lot of these questions, I think it depends. As individuals we don’t mind change, given appropriate circumstances. Organisations also want to change (and in today’s business environment it seems to be a question of changing or becoming irrelevant). However, people in organisations are usually strongly incentivised to dislike change, especially if they want to make that next repayment on their new mortgage. Fixing this, and creating a culture that embraces change, means changing the way we think about and structure our organisations and our careers. It means rethinking the rules of enterprise IT.

Every time a conversation comes around to the topic of change, I’m always reminded of a visit I made to a Toyota factory something like a decade ago. It’s so long ago now that I can’t even remember the reason for the visit, but that’s not the point of this missive.

Toyota, like most businesses, loves change. (Many large companies reorganise so often that change seems to be the only constant.) Change, embodied in the development of the Toyota Production System, was what took Toyota from the bottom of the global car industry to the top. Change is also why many of us have moved companies, following jobs as our employers reorganise their operations. For some of us, change is an opportunity. For many though, change is the tool of the man as he tries to disrupt our lives. Change means unwanted relocations, pay cuts, career stalls, or the need to shift jobs when we don’t want to. Change is something to be resisted.

What was interesting about my visit to Toyota though, was the attitude of the workers on the shop floor had to change. They didn’t hate it. They didn’t even resist it. They actually arrived at work each day eager to see how work practices had been changed since the end of their last shift.

A Toyota assembly line circa 2000.
A Toyota assembly line circa 2000

The concrete example I saw of this was the pre-sorting of seatbelt parts into coloured tubs. Apparently only a few weeks earlier the parts had been arranged on a wall. All hooks and dangling parts, like your Dad’s tools in the shed. When a car came down the assembly line a worker would select the parts appropriate for the car model, and then attach them to the car. Each seat belt had roughly four parts, so that meant there was three unnecessary decisions. Unnecessary decisions usually mean mistakes, mistakes waste time and money, and there were a number of mistakes made.

One day a member of the shop floor team had had the bright idea of pre-sorting the seat belts to avoid these mistakes. Some coloured tubs were sourced (some of the shop floor team drove to the local Walmart with a little petty cash), parts were sorted into tubs, and they gave the idea a trial run. Selecting seatbelt parts for a car now only required one decision: which tub?

The idea was a huge success; error rates went down dramatically. I hear that it was even taken global, and implemented in most Toyota factories around the world. (Though being around ten years ago, and with today’s rapid pace of change, I expect that the tubs have been superseded by now.)

What’s interesting about this story is that the change originated on the shop floor, from the assembly line worker who were actively looking to improve operations, rather than from head office as part of a reorganisation. Some of the improvements I heard about even resulted in the elimination of jobs, with the workers redeployed elsewhere in the factory. Workers weren’t just changing how they did something, they were also changing what they did. Change was what made the work interesting and engaging for the workers, rather than being seen as an oppressive tool used by the man.

I think we can safely set aside the idea that works don’t like change, as this story is not an isolated incident. Why then, do so many people resist change? Why, for every Toyota factory, there is a story like the UK newspaper industry, where workers (and unions) resisted change for decades, until Rupert Murdoch came along.

Rupert Murdoch, destroyer of unions, and good Melbourne boy
Rupert Murdoch, destroyer of unions, and good Melbourne boy

The problem is not people or organisations, but people in organisations.

People are funny things; they tend to do what you incentivise them to do. There’s an excellent article over at the NY Times, The no-stars all-star, which talks about measurement and incentives in basketball. We often talk about “what gets measured determines what gets done” from an employee incentive point of view, but this article puts some real meat on the bones of that argument.

Shane Battier, the no-stars all-star
Shane Battier, the no-stars all-star

As the article says (on page two):

There is a tension, peculiar to basketball, between the interests of the team and the interests of the individual. The game continually tempts the people who play it to do things that are not in the interest of the group.

A little later it goes on to mention (on page three):

A point guard might selfishly give up an open shot for an assist. You can see it happen every night, when he’s racing down court for an open layup, and instead of taking it, he passes it back to a trailing teammate. The teammate usually finishes with some sensational dunk, but the likelihood of scoring nevertheless declined. “The marginal assist is worth more money to the point guard than the marginal point,” Morey says.

The point guard’s career is defined by the number of assists he makes (among other metrics), and he’ll try and increase the number of assets even if it’s not in the best interest of the team. After all, teams come and go, while he has a career to maintain.

Once you place a person into a role you have put them on a career path which will determine their attitude to change.

Usually we take an operational approach to defining roles, rewarding people for the volume of work they are responsible for. Career progression then means increasing the amount of work they are responsible for, regardless of what this means for the company.

Measuring a project manager in terms of head count or revenue under management will give them a strong preference for creating ever bigger projects. It doesn’t matter if the right thing to do is create more, smaller projects, rather than run a programme of a few major projects as we have in the past. Your project manager’s career path is to increase their head count and revenue under management. And they do have those private school fees due soon.

Just like the point guard, change that will prevent career progression will be resisted (remember those kids in private school), even if it is counter to the company’s best interests. Which makes the current transformation we’re seeing in IT all the more important, because if we set the wrong incentives in place then we just might be our own worst enemies.

We can’t force a square peg into a round hole; nor can we force our existing employees to take their current roles and careers into a new organisational model. They just don’t fit. Take IT for example. We can’t expect many modern IT departments to spontaneously modernise themselves, transforming into agile business-technology engines under their own volition. It’s not that the departments don’t want to change: they do. Nor are most of the employees, as individuals, opposed (remember the Toyota example). But the combination of people and organisation will repel all but the most destructive boarders.

It’s interesting how other games, games other than basketball that is, have structural solutions to this problem. One solution is the line-up in baseball. From the NY Times article (page two, again):

“There is no way to selfishly get across home plate,” as Morey puts it. “If instead of there being a lineup, I could muscle my way to the plate and hit every single time and damage the efficiency of the team — that would be the analogy.”

Solving this problem in IT means rethinking the rules of IT.

The game of IT has, for the last few decades, been determined by the need to deliver large, enterprise applications into the IT estate. Keep the lights on, don’t lose orders, and automate anything that hasn’t yet been automated. Oh — and I’d like my reports accurate and on time. IT as the game of operational engineering. It was these rules that drove the creation of most of the roles we have in enterprise IT today.

However, this has changed. Decisions are now more important than data, and the global credit crunch is driving us to reconsider the roles we need in IT. We’re trying to reinvent our IT departments for the modern era – I even posted about how this was driving the need the need to manage technology, and not applications – but we haven’t changed the rules to suit.

If we want out people to embrace change, as the people on the shop floor at Toyota did, then we need to provide them with roles and careers that support them in the new normal. And this means changing the rules. Out with the more – more applications, larger projects, more people – and in with the new.

So what are the new rules for IT?

Decisions are more important than data

Names and categories are important. Just look at the challenges faced by the archeology community as DNA evidence forces history to be rewritten when it breaks old understandings, changing how we think and feel in the process. Just who invaded who? Or was related to who?

We have the same problem with (enterprise) technology; how we think about the building blocks of the IT estate has a strong influence on how approach the problems we need to solve. Unfortunately our current taxonomy has a very functional basis, rooted as it is in the original challenge of creating the major IT assets we have today. This is a problem, as it’s preventing us to taking full advantage of the technologies available to us. If we want to move forward, creating solutions that will thrive in a post GFC world, then we need to think about enterprise IT in a different way.

Enterprise applications – the applications we often know and love (or hate) – fall into a few distinct types. A taxonomy, if you will. This taxonomy has a very functional basis, founded as it is on the challenge of delivering high performance and stable solutions into difficult operational environments. Categories tend to be focused on the technical role a group of assets have in the overall IT estate. We might quibble over the precise number of categories and their makeup, but for the purposes of this argument I’m going to go with three distinct categories (plus another one).

SABER @ American Airlines

First, there’s the applications responsible for data storage and coherence: the electronic filing cabinets that replaced rooms full of clerks and accountants back in the day. From the first computerised general ledger through to CRM, their business case is a simple one of automating paper shuffling. Put the data in on place and making access quick and easy; like SABER did, which I’ve mentioned before.

Next, are the data transformation tools. Applications which take a bunch of inputs and generate an answer. This might be a plan (production plan, staffing roster, transport planning or supply chain movements …) or a figure (price, tax, overnight interest calculation). State might be stored somewhere else, but these solutions still need some some serious computing power to cope with hugh bursts in demand.

Third is data presentation: taking corporate information and presenting in some form that humans can consume (though looking at my latest phone bill, there’s no attempt to make the data easy to consume). This might be billing or invoicing engines, application specific GUIs, or even portals.

We can also typically add one more category – data integration – though this is mainly the domain of data warehouses. Solutions that pull together data from multiple sources to create a summary view. This category of solutions wouldn’t exist aside from the fact that our operational, data management solutions, can’t cope with an additional reporting load. This is also the category for all those XLS spreadsheets that spread through business like a virus, as high integration costs or more important projects prevent us from supporting user requests.

A long time ago we’d bake all these layers into the one solution. SABER, I’m sure, did a bit of everything, though its main focus was data management. Client-server changed things a bit by breaking user interface from back-end data management, and then portals took this a step further. Planning tools (and other data transformation tools) started as modules in larger applications, eventually popping out as stand alone solutions when they grew large enough (and complex enough) to justify their own delivery effort. Now we have separate solutions in each of these categories, and a major integration problem.

This categorisation creates a number of problems for me. First and foremost is the disconnection between what business has become, and what technology is trying to be. Back in the day when “computer” referred to someone sitting at a desk computing ballistics tables, we organised data processing in much the same way that Henry Ford organised his production line. Our current approach to technology is simply the latest step in the automation of this production line.

Computers in the past
Computers in the past

Quite a bit has changed since then. We’ve reconfigured out businesses, we’re reconfiguring our IT departments, and we need to reconfigure our approach to IT. Business today is really a network of actors who collaborate to make decisions, with most (if not all) of the heavy data lifting done by technology. Retail chains are trying to reduce the transaction load on their team working the tills so that they can focus on customer relationships. The focus in supply chains to on ensuring that your network of exception managers can work together to effectively manage disruptions in the supply chain. Even head office focused on understanding and responding to market changes, rather than trying to optimise the business in an unchanging market.

The moving parts of business have changed. Henry Ford focused on mass: the challenge of scaling manufacturing processes to get cost down. We’re moved well beyond mass, through velocity, to focus on agility. A modern business is a collection of actors collaborating and making decisions, not a set of statically defined processes backed by technology assets. Trying to force modern business practices into yesterdays IT taxonomy is the source of one of the disconnects between business and IT that we complain so much about.

There’s no finer example of this than Sales and Operations Planning (S&OP). What should be a collaborative and fluid process – forward planning among a network of stakeholders – has been shoehorned into a traditional n-tier, database driven, enterprise solution. While an S&OP solution can provided significant cost saving, many companies find it too hard to fit themselves into the solution. It’s not surprising that S&OP has a reputation for being difficult to deploy and use, with many planners preferring to work around the system than with it.

I’ve been toying with a new taxonomy for a little while now, one that tries to reflect the decision, actor and collaboration centric nature of modern business. Rather than fit the people to the factory, which was the approach during the industrial revolution, the idea is to fit the factory to the people, which is the approach we use today post LEAN and flexible manufacturing. While it’s a work in progress, it still provides a good starting point for discussions on how we might use technology to support business in the new normal.

In no particular order…

Fusion solutions blend data and process to create a clear and coherent environment to support specific roles and decisions. The idea is to provide the right data and process, at the right time, in a format that is easy to consume and use, to drive the best possible decisions. This might involve blending internal data with externally sourced data (potentially scraped from a competitor’s web site); whatever data required. Providing a clear and consistent knowledge work environment, rather than the siloed and portaled environment we have today, will improve productivity (more time on work that matters, and less time on busy work) and efficiency (fewer mistakes).

Next, decisioning solutions automate key decisions in the enterprise. These decisions might range from mortgage approvals through office work, such as logistics exception management, to supporting knowledge workers workers in the field. We also need to acknowledge that decisions are often decision making processes which require logic (roles) applied over a number of discrete steps (processes). This should not be seen as replacing knowledge workers, as a more productive approach is to view decision automation as a way of amplifying our users talents.

While we have a lot of information, some information will need to be manufactured ourselves. This might range from simple charts generated from tabular data, through to logistics plans or maintenance scheduling, or even payroll.

Information and process access provide stakeholders (both people and organisations) with access to our corporate services. This is not your traditional portal to web based GUI, as the focus will be on providing stakeholders with access wherever and whenever they need, on whatever device they happen to be using. This would mean embedding your content into a Facebook app, rather than investing in a strategic portal infrastructure project. Or it might involve developing a payment gateway.

Finally we have asset management, responsible for managing your data as a corporate asset. This looks beyond the traditional storage and consistency requires for existing enterprise applications to include the political dimension, accessibility (I can get at my data whenever and wherever I want to) and stability (earthquakes, disaster recovery and the like).

It’s interesting to consider the sort of strategy a company might use around each of these categories. Manufacturing solutions – such as crew scheduling – are very transactional. Old data out, new data in. This makes them easily outsourced, or run as a bureau service. Asset management solutions map very well to SaaS: commoditized, simple and cost effective. Access solutions are similar to asset management.

Fusion and decisioning solutions are interesting. The complete solution is difficult to outsource. For many fusion solutions, the data and process set presented to knowledge workers will be unique and will change frequently, while decisioning solutions contain decisions which can represent our competitive advantage. On the other hand, it’s the intellectual content in these solutions, and not the platform, which makes them special. We could sell our platform to our competitors, or even use a commonly available SaaS platform, and still retain our competitive advantage, as the advantage is in the content, while our barrier to competition is the effort required to recreate the content.

This set of categories seems to map better to where we’re going with enterprise IT at the moment. Consider the S&OP solution I mention before. Rather than construct a large, traditional, data-centric enterprise application and change our work practices to suit, we break the problem into a number of mid-sized components and focus on driving the right decisions: fusion, decisioning, manufacturing, access, and asset management. Our solution strategy becomes more nuanced, as our goal is to blend components from each category to provide planners with the right information at the right time to enable them to make the best possible decision.

After all, when the focus is on business agility, and when we’re drowning in a see of information, decisions are more important than data.

Is the market for IT services and solutions shrinking or growing?

Here’s an interesting and topical question: is the market for enterprise IT services (SI, BPO, advisory et al) growing or shrinking? I’m doing the rounds at the moment to see where the market is going (a side effect of moving on), and different folk seems to have quite different views.

  • It’s shrinking as the new normal is squeezing budgets and OPEX is the new CAPEX.
  • It’s growing as companies are externalising more functions than ever before as they attempt to create a laser like focus on their core business.
  • It’s shrinking as the transition from on-premsis applications to SaaS implies a dramatic reduction (some folk are saying around 80-90%) in the effort required to deploy and maintain a solution.
  • It’s growing as the mid market is becoming a lot more sophisticated and starting to spend a lot more on enterprise software (witness Microsoft Dynamics huge market share).
  • It’s shrinking as SaaS is replacing BPO, in effect replacing people with cheaper software solutions? (Remember when TrueAdvantage, and Indian BPO, laid off all 150 of its workers after being purchased by InsideView?)
  • It’s growing as the need for more mobility solutions, and the massive growth in the mobile web, is driving us to create a new generation of enterprise solutions.
  • It’s shrinking as cloud computing and netbooks remove what little margin was left in infrastructure services.
  • It’s growing as investment in IT is a bit like gas, and tends to expand until it consumes all available funds. (Remember integration? As the cost of integration went down, we just found more integration projects to fill the gap.)

Like of a lot of these questions, it depends.

Update: Gartner finds that the worldwide IT services declined 5.3% last year, while Computer World UK tells us to expect another year of decline. How much of this is cyclic, and how much is due to a definition of “services” which could be more inclusive?

Updated: It appears that some organisations are not happy with the size and dominance of the IT services industry.

The IT department we have today is not the IT department we’ll need tomorrow

The IT departments many of us work in today (either as an employee or consultant) are often the result of thirty or more years of diligent labour. These departments are designed, optimised even, to create IT estates populated with large, expensive applications. Unfortunately these departments are also looking a lot like dinosaurs: large, slow and altogether unsuited for the the new normal. The challenge is to reconfigure our departments, transforming them from asset management functions into business (or business-technology) optimisation engines. This transformation should be a keen interest for all of us, as it’s going to drive a dramatic change in staffing profiles which will, in turn, effect our own jobs in the no so distant future.

Delivering large IT solutions is a tricky business. They’re big. They’re expensive. And the projects to create them go off the rails more often than we’d like to admit. IT departments have been built to minimise the risks associated with delivering and operating these applications. This means governance, and usually quite a lot of it. Departments which started off as small scale engineering functions soon picked up an administrative layer responsible to the mechanics of governance.

More recently we’ve been confronted with the challenge with managing the dependancies and interactions between IT applications. Initiatives like straight-through processing require us to take a holistic, rather than a pieces-parts, approach, and we’re all dealing with the problem of having one of each application or middleware product, as well as a few we brewed in the back room ourselves. Planning the operation and evolution of the IT estate became more important, and we picked up an enterprise architecture capability to manage the evolution of our IT estate.

It’s common to visualise these various departmental functions and roles as a triangle (or a pyramid, if you prefer). At the bottom we have engineering: the developers and other technical personnel who do the actual work to build and maintain our applications. Next layer up is governance, the project and operational administrators who schedule the work and check that it’s done to spec. Second from the top are the planners, the architects responsible for shaping the work to be done as well as acting as design authority. Capping of the triangle (or pyramid) is the IT leadership team who decide what should be done.

The departmental skills triangle

While specific techniques and technologies might come and go, the overall composition of the triangle has remained the same. From the sixties and seventies through to even quite recently, we’ve staffed our IT departments with many technical doers, a few less administrators, a smaller planning team, and a small IT leadership group. The career path for most of us been a progression from the bottom layers – when we were fresh out of school – to the highest point in the triangle that we can manage.

The emergence of off-shore and outsourcing put a spanner in the works. We all understand the rational: migrate the more junior positions – the positions with the least direct (if any) contact with the business proper – to a cheaper country. Many companies under intense cost pressure broke the triangle in two, keeping the upper planning and decision roles, while pushing the majority of the manage and all the do roles out of the country, or even out of the company.

Our first attempt at out-sourcing

Ignoring whether or not this drive to externalise the lower roles provided the expected savings or not, what it did do is break the career ladder for IT staff. Where does you next generation of senior IT personnel come from if you’ve pushed the lower ranks out of the business? Many companies found themselves with an awkward skills shortage a few years into an outsourcing / off-shore arrangement, as they were no longer able to train or promote senior personnel to replace those who were leaving through natural attrition.

The solution to this was to change how we brake-up the skills triangle; rather than a simple horizontal cut, we took a slice down the side. Retaining a portion of all skills in-house allows companies provide a career path and on the job training for their staff.

A second, improved, go at out-sourcing
A second, improved, go at out-sourcing

Many companies have tweaked this model, adding a bulge in the middle to provide a large enough resource pool to manage both internal projects, as well as those run by out-sourced and off-shore resources.

Factoring in the effort required to manage out-sourced projects
Factoring in the effort required to manage out-sourced projects

This model is now common in a lot of large companies, and it has served us well. However, the world has a funny habit of changing just when you’ve everything working smoothly.

The recent global financial criss has fundamentally changed the business landscape. We are experiencing not merely another turn of the business cycle, but a restructuring of the economic order. Many are even talking about the emergence of a new normal. The impact this will have on how we run our businesses (and our IT departments) is still being discussed, but we can see the outline of this impact already.

Companies are becoming more focused, while leaning more heavily on partners and services companies (BPO, out-sourcers, consultants, and so on) to cover those areas of the business they don’t want to focus on. We can see this from the global companies who have effectively moved to a franchise model, though to the small end of town where startups are using on-line services such as Amazon S3, rather than building internal capabilities. While this trend might have initially started as a cost saving, most of the benefit is in management time saved, which can then be used to focus on more important issues. We’re all finding that the limiting factor in our business is management time, so being able to hand off the management of less important tasks can help provide that edge you need.

We’re also seeing faster business change: what used to take years now takes months, or even weeks. The constant value-chain optimisation we’ve been working on since the 70s has finally cumulated in product and regulatory life-cycles that change faster than we can keep up. Nowhere is this more evident than the regulated industries (finance, utilities …), where updates in government regulation has changed from a generational to a quarterly occurrence as governments attempt to use regulation change to steer the economic boat.

Money is also becoming (or has become) more expensive, causing companies and deals to operate with less leverage. This means that there is less capital available for major projects, pushing companies to favour renting over buying, as well as creating a preference for smaller, incremental change over the major business transformation of the past.

And finally, companies are starting to take a truly global outlook and operate as one cohesive business across the globe, rather than as a family of cloned business who operate more-or-less independently in each region.

We can draw a few general conclusions on the potential impact on IT departments of these trends.

  • The increase reliance on partners, the broader partner ecosystem this implies, and an increasingly global approach to business will create more complex operational environments, increasing the importance of planning the IT estate and steering a company’s IT in the right direction.
  • The need to reduce leverage, and free up working capital, is pushing companies toward BPO and SaaS solutions, rather than the traditional on-premisses solutions, where the solution provider is paid per-seat, or might even be only paid a success fee.
  • The need for rapid project turn-around is pushing us toward running large portfolios of small projects, rather than a small number of large projects.
  • A lot of the admin work we used to do is now baked into web delivered solutions (BaseCamp et al).

This will trigger us to break up a the skills triangle in a different way.

A skills/roles triangle for the new normal
A skills/roles triangle for the new normal

While we’ll still take a slice down the side of the triangle, the buldge will move to the ends of the slice, giving it a skinny waist. The more complex operational environment means that we need to beef up planning (though we don’t want to get all dogmatic about our approach, as existing asset-centric IT planning methodologies won’t work in the new normal). A shift to large numbers of small projects (where the projects are potentially more technically complex) means that we’ll beef up our internal delivery capability, providing team leads with more autonomy. The move to smaller projects also means that we can reduce our administration and governance overhead.

We’ll replace some skills with automated (SaaS) solutions. Tools like BaseCamp will enable us to devolve responsibility for reporting and management to the team at the coalface. It will also reduce the need to develop and maintain infrastructure. Cloud technology is a good example of this, as it takes a lot of the tacit knowledge required to manage a fleet of servers and bakes it into software, placing it in the hands of the developers. Rumor has it that that a cloud admin can support 10,000 servers to a more traditional admin’s 500.

And finally, our suppliers act as a layer through the middle, a flex resource for us to call on. They can also provide us with a broader, cross-industry view, of how to best leverage technology.

This thinning out of the middle ranks is part of a trend we’re seeing elsewhere. Web2.0/E2.0/et al are causing organisations to remove knowledge workers — the traditional white collar middle layers of the organisaiton – leaving companies with a strategy/leadership group and task workers.

Update: Andy Mulholland has an interesting build on this post over at the Capgemini CTO blog. I particularly like the Holm service launched by Ford and Microsoft, a service that it’s hard to imagine a traditional IT department fielding.