Tag Archives: Henry Ford

Manufacturing is not returning to the West

There’s many claims over the last year or so that “manufacturing is returning to the West” and “China’s days as the world’s factory are numbered”{{1}}. These claims are misguided.

[[1]]Vivek Wadhwa (23 July 2012), The End of Chinese Manufacturing and Rebirth of U.S. Industry, Forbes[[1]]

We’ve just reached a time where manual and skilled labour is no longer a major manufacturing cost, causing final assembly to slowly drifting toward the customer base it serves. This shift reduces the length of the supply chain from assembly to your front door resulting in a reduction in turn-around time which, in turn, reduces working capital requirements and allows manufacturers to push product updates through the supply chain faster.

Manufacturing isn’t leaving China and other low cost manufacturing centres. What has changed is that it now makes good sense to manufacture some high value but low volume and bulky products in other major markets, such as the U.S.

The problem with thinking that manufacturing is returning to the first world is the implicit assumption that this also means that the old manufacturing jobs will return. They won’t. They no longer exist. It also ignores that fact that the huge scale of manufacturing in China will help it to grab the lions share of the world manufacturing market for some time to come.

Manufacturing as a manual process

Consider Henry Ford’s assembly line from 1913: a complex, labour intensive process that created a large number of good, blue collar jobs.

566px-Ford_assembly_line_-_1913Source: Public Domain

When we think of manufacturing this is the image we usually have in head. It’s a bit like those train crossing signs that have a caricature of a steam engine on them. It might not be the current reality, but it’s the image we use to understand what’s going on around us.

As transport costs dropped, work moved to lower cost countries

Back in Henry Ford’s day transportation was expensive. Factories were often located close to the markets they served to minimise transport costs, with management struggling to ensure that enough raw materials arrived at the factory to keep it busy. However, the development of railroads, steam ships, and the shipping container network incrementally cut the cost of transport until it cost roughly the same to move a box across the world as it did to move it across the country.

As Marc Levinson points out in his book, The Box{{2}}:

[[2]]Marc Levinson, The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger. iBooks.[[2]]

As transportation costs decline relative to other costs, manufacturers can relocate first domestically, and then internationally, to reduce other costs, which come to loom larger. Globalization, the diffusion of economic activity without regard for national boundaries, is the logical end point of this process. As transport costs fall to extremely low levels, producers move from high-wage to low-wage countries, eventually causing wage levels in all countries to converge. These geographic shifts can occur quickly and suddenly, leaving long-standing industrial infrastructure underutilized or abandoned as economic activity moves on.

This is the shift we’re thinking of when we consider off-shore manufacturing: China as the source of cheap (and fairly unskilled labour).

Today, manufacturing is not a manual process

Apple released an interesting video the other day{{3}}. It shows the manufacturing process for the new Mac Pro.

[[3]]Greg Koenig (22 October 2013), How Apple makes the Mac ProAtomic Delights[[3]]

SourceApple

What’s interesting about this process is how few people are involved.

Manufacturing has changed a lot in the last few decades. What was once dominated by manual labour is now an automated and highly efficient process. Machines have replaced people. We can see this in many of the factories that are returning to the West: they’re all highly efficient, highly automated, capital intensive operations that require very little manual or skilled labour.

7395855880_053e6daede_cSource: Steve Jurvetson

Machines, however, have yet to replace engineers

While capital has won over manual and skilled labour, that same is not true for engineers: knowledge workers.

As Roger Martin found in his research for a recent HBR article{{4}}:

[[4]]Roger L. Martin (October 2013), Rethinking the Decision Factory, Harvard Business Review[[4]]

I vividly remember working with the CEO of one of North America’s largest bread manufacturers in 1990–1991. He had just replaced a labor-intensive and antiquated plant with the most advanced bread bakery on the continent. He proudly told me that the new computerized ovens and packaging machinery had reduced direct labor costs by 60%. But meanwhile, a throng of new and expensive knowledge workers had been added at both the head office and the plant—engineers, computer technicians, and managers—to take care of the sophisticated computer systems and state-of-the-art equipment. The new plant wasn’t quite the unalloyed good that it appeared at first sight. Variable costs of manual labor fell, but the fixed cost of knowledge workers rose, making it critical to keep capacity utilization high—which was possible in some years but not in others.

While the West has been worried about losing it manufacturing capability, many of the off-shore manufacturing destinations have been investing in education. China, for example, now has a huge engineering workforce that companies can draw own to sort out their manufacturing problems.

It’s this incredible ability to mobilise huge workforces that is keeping many manufactures in China. An article in the New York Times from last year has an Apple anecdote that shows this in action{{5}}.

[[5]]Charles Dugigg & Keith Bradsher (21January2012), How the U.S. Lost Out on iPhone Work, The New York Times[[5]]

Another critical advantage for Apple was that China provided engineers at a scale the United States could not match. Apple’s executives had estimated that about 8,700 industrial engineers were needed to oversee and guide the 200,000 assembly-line workers eventually involved in manufacturing iPhones. The company’s analysts had forecast it would take as long as nine months to find that many qualified engineers in the United States.

Moving closer to the customer

The rapid pace of change in today’s market is driving companies to reduce the time between final assembly and when the product drops into the customer’s waiting hands.

Zara is the poster child for this shift, with a supply chain can create a new product and then have it in the stores in around two weeks. Zara has used this ability to disrupt the traditional annual, seasonal fashion cycle, resulting Zara becoming one of the largest retailers in the world.

Apple’s recent decision to make the Mac Pro in the U.S. is part of a trend to move the manufacturing of high value but low volume and bulky products closer to the customer. Elon Musk’s Tesla is also part of this trend.

Manufacturing automation technology has reached the point that it makes more sense to locate the manufacturing of these products closer to the customer, allowing transport costs and delivery times to be minimised.

We shouldn’t assume, however, that this trend will end with manufacturing returning to the West.

It’s easy to forget the more people live in Asia than in the entire rest of the world combined. If manufacturing is moving to be closer to the customer, then we need to remember that there are more customers in Asia than in the rest of the world. China’s position as a manufacturing powerhouse appears safe for the time being.

CK6aONG

Source: valeriepieris

What we mean by “export” is changing

So just where will this trend take us? (And, by extension, will our old export industries return, bringing their jobs back with them?)

The future of manufacturing and export seems – like to many industries – connected to the knowledge economy.

Those old manufacturing jobs are never coming back. They no longer exist. Similarly, thinking in terms of operating a factory and then exporting to another country is also looking somewhat antiquated.

Today (or perhaps, tomorrow) a manufacturer is a simply company that is run from one country and, from there, manages the sale of products in another.

Kogan{{6}} is a great example of this. The business is run from South Melbourne, Australia, which is where the products are designed. The products themselves are made in China and (in many cases) shipped directly to the United Kingdom where they are sold via the company’s UK web site (which is also managed from Port Melbourne, but hosted somewhere “in the cloud”).

[[6]]Kogan @ PEG[[6]]

An even more interesting example is another local business which sells safety barriers that are placed around robots in factories to ensure that workers aren’t accidentally injured. They recently started exporting to Europe. They did this by setting up a small, automated factory in Germany to service the European market. The barriers are designed in Australia and the designs are beamed directly to the machines in Germany, machines that consume resources from all over the globe.

So manufacturing – as we’ve traditionally understood it – is not returning to the West. The blue collar jobs that went overseas are not coming home to give our rather lacklustre economies a boost.

We can also expect China to remain an manufacturing powerhouse for the foreseeable future. The huge scale of operations over there, and the ability to rapidly redeploy these resources, will allow China to grab more than it’s fair share of the world manufacturing market.

Manufacturing, like so many industries{{7}}, is changing, and changing rapidly. What’s most interesting though, is how a new generation of companies are emerging that are finding ways to exploit this situation to “export”, and create new, knowledge intensive jobs at home in the process.

[[7]]The destruction of traditional retail @ PEG[[7]]

Source: Steve Jurvetson

What is innovation?

What is innovation? I don’t know, but then I’m not even sure that it’s an interesting question. The yearning so many companies have to be innovative often seems to prevent them from actually doing anything innovative. They get so caught up in trying to come up with the next innovation — the next big product — that they often fail to do anything innovative at all. It’s more productive to define innovation by understanding what it’s not: doing the same thing as the rest of the crowd, while accepting that there are no silver bullets and that you don’t control all the variables.

So, what is innovation? This seems to be a common question thats comes up whenever a company wants to innovate. After all, the first step in solving a problem is usually to define our terms.

Innovation is a bit like quantum theory’s spooky action at a distance,1)Spooky action at a distance? @ Fact and Fiction where stuff we know and understand behaves in a way we don’t expect. It can be easy to spot an innovative outcome (hindsight is a wonderful thing), but it’s hard to predict what will be innovative in the future. Just spend some time browsing Paleo-Future2)Paleo-Future (one of my favourite blogs) to see just how far off the mark we’ve been in the past.

The problem is that as it’s all relative; what’s innovative in one context may (or may not) be innovative in another. You need an environment that brings together a confluence of factors — ideas, skills, the right business and market drivers, the time and space to try something new — before there’s a chance that something innovative might happen.

Unfortunately innovation has been claimed as the engine behind the success of more than a few leading companies, so we all wanted to know what it is (and how to get some). Many books have been written promising to tell you exactly what to do to create innovation, providing you with a twelve step program3)Twelve step programs @ Wikipedia to a happier and more innovative future. If you just do this, then you too can invent the next iPhone.4)iPhone — the Apple innovation everyone expected @ Fast Company

Initially we were told that we just needed to find the big idea, a concept which will form the basis of our industry shattering innovation. We hired consultants to run ideation5)Ideation defined at Wikipedia workshops for us, or even outsourced ideation to an innovation consultancy asking them to hunt down the big idea for us. A whole industry has sprung up around the quest for the big idea, with TED6)TED (which I have mixed feelings about) being the most obvious example.

As I’ve said before, the quest for the new-new thing is pointless.7)Innovation should not be the quest for the new-new thing @ PEG

The challenge when managing innovation is not in capturing ideas before they develop into market shaping innovations. If we see an innovative idea outside our organization, then we must assume that we’re not the first to see it, and ideas are easily copied. If innovation is a transferable good, then we’d all have the latest version.

Ideas are a dime a dozen, so real challenge is to execute on an idea (i.e. pick one and do something meaningful with it). If you get involved in that ideas arms race, then you will come last as someone will always have the idea before you. As Scott McNealy at Sun likes to say:

Statistically, most of the smart people work for somebody else.

More recently our focus has shifted from ideas to method. Realising that a good idea is not enough, we’ve tried to find a repeatable method with which we can manufacture innovation. This is what business does after all; formalise and systematise a skill, and then deploy it at huge scale to generate a profit. Think Henry Ford and the creation of that first production line.

Design Thinking8)Design Thinking … what is that? @ Fast Company is the most popular candidate for method of innovation, due largely to the role of Jonathan Ive9)Jonathan Ive @ Design Museum and design in Apple’s rise from also-ran to market leader. There’s a lot of good stuff in Design Thinking — concepts and practices anyone with an engineering background10)Sorry, software engineering doesn’t count. would recognise. Understand the context that your product or solution must work in. Build up the ideas used in your solution in an incremental and iterative fashion, testing and prototyping as you go. Teamwork and collaboration. And so on…

The fairly obvious problem with this is that Design Thinking does not guarantee an innovative outcome. For every Apple with their iPhone there’s an Apple with a Newton.11)The story behind the Apple Newton @ Gizmodo Or Microsoft with a Kin.12)Microsoft Said to Blame Low Sales, High Price for Kin’s Failure @ Business Week Or a host of other carefully designed and crafted products which failed to have any impact in the market. I’ll let the blog-sphere debate the precise reason for each failure, but we can’t escape the fact the best people with a perfect method cannot guarantee us success.

People make bad decisions. You might have followed the method correctly, but perhaps you didn’t quite identify the right target audience. Or the technology might not quite be where you need it to be. Or something a competitor did might render all your blood sweet and tears irrelevant.

Design Thinking (and innovation) is not chess: a game where all variables are known and we have complete information, allowing us to make perfect decisions. We can’t expect a method like Design Thinking to provide an innovative outcome.

Why then do we try and define innovation in terms of the big idea or perfect methodology? I put this down to the quest for a silver bullet: most people hope that there’s a magic cure for their problems which requires little effort to implement, and they dislike the notion that hard work is key.

This is true in many of life’s facets. We prefer diet pills and magic foods over exercise and eating less. If I pay for this, then it will all come good. If we just can just find that innovative idea in our next facilitated ideation workshop. Or hire more designers and implement Design Thinking across our organisation.

Success with innovation, as with so many things, is more a question of hard work than anything else. We forget that the person behind P&G’s Design Thinking efforts,13)P&G changes it’s game @ Business Week Cindy Tripp, came out of marketing and finance, not design. She chose Design Thinking as the right tool for the problems she needed to solve — Design Thinking didn’t choose her. And she worked hard, pulling in ideas from left, right and centre, to find, test and implement the tools she needed.

So innovation is not the big idea. Nor is it a process like Design Thinking.

For me, innovation is simply:

  • working toward a meaningful goal, and
  • being empower to use whichever tools will be most beneficial.

If I was to try and define innovation more formally, then I would say that innovation is a combination of two key concepts: obliquity14)Obliquity defined at SearchCRM and Jeet Kune Do’s15)Jeet Kune Do, a martial art discipline developed by Bruce Lee @ Wikipedia concept of absorbing what is useful.

Obliquity is the simple idea that the best way to achieve a goal in a complex environment is to take an indirect approach. The fastest and most productive path to the top of the mountain might be to take the path that winds its way around the mountain, rather than to try and walk directly up the steepest face.

Apple is a good example of obliquity in action. Both Steve Jobs and Jonathan Ives are on record as wanting to make “great products that we want to own ourselves,” rather than plotting to build the biggest and most innovative company on the planet. Rather than try and game the financial metrics, they are focusing on making great products.

Bruce Lee16)Bruce Lee: the devine wind came up with the idea of “absorbing what is useful”17)Absorbing what is useful @ Wikipedia when he created Jeet Kune Do. He promoted the idea that students should learn a range of methods and doctrines, experiment to learn what works (and what doesn’t work) for them, “absorb what is useful” while discarding the remainder. The critical point of this principle is that the choice of what to keep is based on personal experimentation. It is not based on how a technique may look or feel, or how precisely the artist can mimic tradition. In the final analysis, if the technique is not beneficial, it is discarded. Lee believed that only the individual could come to understand what worked; based on critical self analysis, and by, “honestly expressing oneself, without lying to oneself.”

Cindy Tripp at P&G is a good example of someone absorbing what is useful. Her career has her investigating different topics and domains, more a sun shaped individual than a t-shaped one.18)T-Shaped + Sun-Shaped People @ Logic + Emotion Starting from a core passion, she accreted a collection of disciplines, tools and techniques which are beneficial. Design Thinking is one of these techniques (which she uses as a reframing tool).

I suppose you could say that I’ve defined innovation by identifying what it’s not: innovation is the courage to find a different way up the hill, while accepting that there are no silver bullets and that you don’t control all the variables.

Updated: Tweeked the wording in the (lucky) 13th paragraph in line with Bill Buxton’s comment.

For every Apple with their iPhone there’s an Apple with a Newton. Or Microsoft with a Kin.

References   [ + ]

The rules of enterprise IT

As I’ve pointed out before (possibly as I’m quite fond of games{{1}}) the game of enterprise IT has a long an proud history. I’ve also pointed out that the rules of this game need to change if enterprise IT — as we know it — is to remain relevant in the future{{2}}. This is triggered a few interesting conversations at the pub on just what are the old rules of IT.

[[1]]Capitalise: A game for the whole company to play![[1]]
[[2]]People don’t like change. (Or do they?)[[2]]

Enterprise IT, as we know it today, is an asset management business, the bastard son of Henry Ford’s moving production line. Enterprise IT takes the raw material of business processes and technology and turns them into automated solutions. From those first card tabulators through to today’s enterprise applications, the focus has been on delivering large IT solutions into the business.

The rules of enterprise IT are the therefore rules of business operations. After a fair amount of coffee and beer with friends, the following 4 ± 2 rules seems to be a fair minimum set (in no particular order).

Keep the lights on. Or, put more gently, the ticket to the strategy table is a smooth running business. Business has become totally reliant on IT, while at the same time IT is still seen as something of a black art run by a collection of unapproachable high priests. The board might complain about the cost and pain of an ERP upgrade, but they know they have to find the money if they want to successfully close the books at the end of the financial year. While this means that the money will usually be found, it also means that the number one rule of being a CIO is to keep the transactions flowing. Orders must be taken, products shipped (or services provided), invoices sent and cash collected. IT is an operational essential, and any CIO who can’t be trusted to keep the lights on won’t even have time to warm up their seat.

Save money. IT started as a cost saving exercise: automatic tabulation machines to replace rooms full of people shuffling papers, networks to eliminate the need to truck paper from one place to another. From those first few systems through to today’s modern enterprise solutions, applications have been seen as a tool to save time and money. Understand what the business processes or problem is, and then support the heavy information lifting with technology to drive cost savings and reduce cycle time. Business cases are driven by ideas like ROI, capturing these savings over time. Keep pushing the bottom line down. These incremental savings can add up to significant changes, such as Dell’s make-to-order solution{{3}} which enabled the company to operate with negative working capital (ie. they took your cash before they needed to pay their suppliers), but the overall approach is still based on using IT to drive cost savings through the automation of predefined business processes.

[[3]]Dell’s make to order solution leaves competitors in the dust.[[3]]

Build what you need. When applications are rare, then building them is an engineering challenge. You can’t just go to the store and by the parts you need, you need to create a lot of the parts yourself in your own machine shop. I remember the large teams (compared to today) from the start of my career. A CORBA project didn’t just need a team to implement the business logic, it needed a large infrastructure team (security guy, transaction guy …) as well. Many organisations (and their strong desire to build – or at least heavily customise – solutions) still work under this assumption. IT was the department to marshal large engineering teams who deliver the industrial grade solutions which can form the backbone of a business.

Ferrero Rocher
Crunch on the outside, soft and chewy in the middle.

Keep the outside outside. It’s common to have what is called a Ferrero Rocher{{4}} approach to IT: crunchy on the outside while soft and chewy in the middle. This applies to both security and data management. We visualise a strong distinction between inside and outside the enterprise. Inside we have our data, processes and people. Outside is everyone else (including our customers and partners). We harvest data from our operations and inject it into business intelligence solutions to create insight (and drive operational savings). We trust whatever’s inside our four walls, while deploying significant security measures to keep the evil outside.

[[4]]Ferrero[[4]]

It’s a separate question of whether or not these rules are still relevant in an age when business cycles are measured in weeks rather than years, and SaaS and cloud computing are emerging as the dominate modes of software delivery.

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
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.

Innovation [2009-11-16]

Another week and another collection of interesting ideas from around the internet.

As always, thoughts and/or comments are greatly appreciated.

  • Warren Buffett’s bet against innovation [BusinessWeek: Innovate]
    In proclaiming an “all-in wager on the economic future of the United States, Warren Buffett just paid $44 billion for a 19th century technology platform, a railroad, that carries 20th century goods—coal, agriculture, imports from Asia, petroleum. This is a vision of an America mired in the past and in economic and political decline. And Buffett just might be right. He has a great track record betting against innovation.
  • Embracing Innovation: a new methodology for feature film production in Australia [Centre for Screen Business]
    Do too many Australian films fall into a budgetary ‘no-man’s land’ – not big enough to compete with the US studios, yet too big to stand a chance of commercial viability in a market flooded with independent films? Robert Connolly’s recommendations provide us with valuable grist for the mill as we, in the IT industry, work our way through the current evolutionary phase our industry is going through, driven by the shift from large, on premises applications to a future increasingly dominated by cloud solutions. His approach to the problem is also an excellent model of how to engage with the wholesale transformation of an industry.
  • 10 examples of minimum viable products [Venture Hacks]
    Brilliant products are rarely the result of brilliant ideas. Most products start small, as minimum viable products, and then grow as the customers and developers work together to learn what the product should be.
  • What do the crowds know about innovation? [Innovate on Purpose]
    Companies use different strategies and techniques for crowdsourcing ideas. All of these approaches help gather ideas from the crowd, but they also serve as trend spotting and public relations opportunities as well, and some companies might be more interested in these secondary effects. As Henry Ford pointed out, “If I had asked my customers what they wanted, they would have said a faster horse.”