My posts on Enterprise 2.0 have attracted several very thoughtful comments.  I want to excerpt and emphasize one from Sean Park, who works at DrKW and maintains the Park Paradigm blog.  He wrote (emphasis added by me):

My feelings exactly.  I’m actually not a big gadget user; most of them are too hard to learn, too hard to use, have too many features, and don’t give me the productivity boosts I crave.  And I usually can’t be bothered to take the time to learn all the time-saving features of hardware and software gadgets; these features aren’t obvious enough to me and so never get activated.
 
But the Socialtext wikis that I use (full disclosure:  Socialtext lets me use their software for free.  I have no financial stake in the company) and my del.icio.us bookmarks and tags have become as indispensable to me as email, Google, and my Blackberry.  They ace both of the classic criteria for user acceptance of IT:

• Ease of Use:  To start editing a page on Socialtext, I double-click on the page.  This is so convenient that I’ve set up a one person wiki (which must be a taboo of some kind) with my to-do lists on it.  I can access it from anywhere, and add to it in seconds.  With the del.icio.us browser toolbar I can bookmark a new page with one click, and go to my collected bookmarks with another.  
• Usefulness:  I’ve set up wikis for all of the collaborative projects I’m working on, and email alerts and/or RSS tell me when any of my colleagues have advanced the work.  Del.icio.us frees me up from having to remember URLs or keep my bookmarks consistent across the computers I use, and its tagging feature lets me organize sites and pages the way I want to.  The social features of del.icio.us are, for me, icing on the cake.  I use them to learn about new sites and voices devoted to topics I’m interested in.

Nick Carr points out accurately that new IT tools always have early adherents, usually geeks.  I’m definitely geekier than most of my colleagues and executive education students, but my MBA students are actually pretty close to me in their affinity for new tech tools. 

HBS MBA students are, of course, much different than the general population along many dimensions, but when I look at them as another class of busy knowledge  workers they actually seem pretty typical.   They try to keep a lot of balls in the air at once, have lots of professional and personal interests, and face a rolling set of deadlines.  Sound familiar?

We spent some time talking about and demonstrating Web 2.0 technologies in class this past semester.  They thought chicagocrime.org and dartmaps were cool, but I don’t think any of them signed up for the next mashup camp.  I do think, though, that some of them started using Blogger, Socialtext, Writely, Digg, del.icio.us, Wikipedia, and a lot of the other tools we went over.

I wouldn’t be a bit surprised if they started evangelizing for tools like these at the companies they’re going to, or at least alerting their coworkers to them and trying to get some grassroots enterprise 2.0 going.  If so, they wouldn’t be evangelizing mainly because they want what’s best for their companies; they’d be doing so because they want good tools for themselves. 

The most fundamental grounds for optimism about the future of enterprise 2.0 technologies is that they provide enduring benefits to companies and groups while providing immediate benefits to individuals.  This sharply differentiates these technologies from applications like classic knowledge management systems where individuals were essentially ‘taking one for the team’ when they contributed.  They did so because of incentives or very strong norms, or because of an expectation that if everyone else behaved as they did the system might one day have some useful information for them.

People use enterprise 2.0 technologies, on the other hand, because they make work easier as soon as soon as new adopters get over Park’s ‘energy barrier.’  And everything I’ve seen makes me agree with him that the barrier is only going to get lower over time as the tools themselves get easier to use, as new people with very different tech skills and expectations enter the workforce, and as we fogies get used to the ideas of posting, tagging, editing Web-based content by double-clicking, etc.

I predict that for a lot of knowledge workers the elements of enterprise 2.0 are going to become what I call ‘ratchet‘ technologies —  tools where there’s no going back.  Can you imagine working (or even living) without the Internet, email, Google, and a mobile phone?  If not, these are ratchet technologies (if so, congratulations on achieving satori).  My car GPS, Tablet PC, wikis, and del.icio.us collection are among my ratchet technologies, and this blog is quickly becoming one.  I think a few more are coming.

Many scholars believe that IT is the latest in a series of general purpose technologies (GPTs), which are innovations so important that they that they cause a positive jump in an economy’s normal march of progress.¹  Steam power, electric power, the transistor, the laser, and modern IT have all been identified as GPTs.  Some of these technologies are incorporated into products and some into processes, but they all share three characteristics:²

• Improvement and elaboration:  GPTs themselves are not static —  they improve significantly over time
• Wide applicability:  They have a huge variety of potential uses, which get discovered over time as people gain familiarity with them, realize their power, and let go of old ways of thinking.
• Strong complementarities with parallel innovations that increase the value of the GPT

Product complements are easy to understand —  hamburgers and hamburger buns are classic examples.  But history shows that process complements are also tremendously important.  

Economic historians have shown that there was a fairly long delay between the introduction of electric power for industry in the US and significant industrial productivity increases.³  They found that at first the new electric motors were used in existing factories, replacing the old water wheel or steam engine.  

These old power sources were connected to a single large driveshaft several floors high; the shaft was in turn connected to all the factory’s machines by a series of belts.  In order to keep machines close to this ‘group drive’ power source, factories were typically tall and narrow.  

At first, the new electric motors were bolted on to the old group drive factories.  Eventually, though, clever business leaders began connecting motors not to driveshafts, but to individual machines.  This switch from group drive to ‘unit drive’ decoupled machines from the driveshaft, and therefore from each other.   Companies started building long, low factories instead of high narrow ones, and started arranging machines linearly into configurations that became assembly lines.

In these new configurations the machines might have been less tightly coupled, but the workers became more interdependent.  Research also shows that the new style factories required workers who were more skilled, and more able to make decisions and take action on their own.  Once all these were in place, American industrial productivity really took off.

In summary, the GPT of electric power required the following complements to realize its full potential:

• More skilled workers
• Higher levels of teamwork / interdependence
• Redesigned workflows
• Greater autonomy / freedom to make decisions at lower levels of the organization.  

Amazingly enough, research on how to maximize the benefits of IT has identified almost exactly the same set of complements.⁴  It seems that both GPTs can greatly increase productivity, and that the increase is greatest when a set of complementary practices is adopted along with the technology itself.

And this, I find, is where things get really interesting.  

It’s pretty clear that information technologies differ from each other, but it’s a lot less clear how.  Is front office vs. back office the right distinction?  Strategic vs. transactional?  Mainframe vs. client-server vs. n-tier?  Mac vs. Windows?  All of these categorizations resonate with some people (although I have my doubts about the ’strategic’ label), but do any of them help business leaders understand which technologies are going to be comparatively easy or hard to adopt, or where they should focus their efforts when trying to maximize the value of IT they purchase?

The concept of complementarities helps answer these questions, as does the insight that some types of IT internalize relevant complements, while others don’t.  Some information technologies, in other words, are the digital equivalents of electric motors, while others are much more like entire digital factories.

Digital Motors
Function IT (FIT), which assists with discrete tasks, falls into the former category.   Spreadsheets and word processors are perhaps the most common FITs; they help analysts and writers, respectively, with their work.  Function technologies also exist for specialists such as design engineers, geneticists, statisticians, architects, photographers, and poker players.

FIT is similar to an electric motor in that both GPTs are used more productively once the above complementarities are in place, but adoption of both technologies can be separated from adoption of the complements.  It is easily possible to start using new FITs without changing anything else, just as it was possible to start using electric motors in pre-existing factories.  Furthermore, the GPTs themselves do not indicate appropriate complements. Spreadsheets and other FITs do not specify the workflows or organizational designs that make best use of their power, just as electric motors didn’t include blueprints for new factories.

My colleagues Alan MacCormack and Marco Iansiti studied how the contestants in the 1995 America’s Cup race used simulation software to help them design their boats’ keels.  Most teams worked with top universities and aerospace companies to build the most sophisticated simulations possible, using either mainframes or supercomputers.  They were all beaten by Team New Zealand, which used much less powerful workstations and actually brought them down to the docks where its boats were being finalized.  Simulation specialists interacted with the boat’s designers and racing crews at the docks, then incorporated their ideas and feedback into a new round of simulations each day.  If the results of these simulations showed that a change made the virtual boat faster, the modification would be made to the real boat in time for the next day’s tests.

Team New Zealand was the first to redesign workflows, increase interdependence, and push decisions downward in the organization.  In other words, it was the first America’s Cup syndicate to  implement the full set of complementary work changes around the GPT of simulation software.  The other syndicates took longer to catch on, in part because it was quite possible to use cutting edge FIT in the old system of work.   

Digital Factories
Enterprise IT (EIT), on the other hand, imposes entirely new systems.  ERP, CRM, SCM, eProcurement, and the wealth of other enterprise systems now available internalize all the complements listed above, with the exception of higher skill levels.  They define entire business processes, increase interdependence among the people involved in executing them, and allocate decision rights, as the following example shows:

In 2002 the retail drugstore CVS became concerned about poor service and long wait times at the pickup counters of its pharmacies.  The first step in its prescription fulfillment process, an automated safety check for drug interactions, occurred one hour before the desired pickup time.  This was immediately followed by an automated insurance status review.  Both of these steps generated many exceptions; drug safety exceptions were handled by pharmacists in consultation with prescribing physicians, while insurance exceptions were managed by technicians in consultation with customers, payors, and physicians.  Many of these exceptions were not resolved by pickup time, leading to customer frustration and dissatisfaction.

A team at CVS headquarters decided to change the order of the two steps, and to perform the insurance review during prescription dropoff while the customer was still present.   This let technicians work with customers to correct simple exceptions such as date of birth errors and employment changes, and to tell customers if more complicated problems would prevent reimbursement.  The change also allowed pharmacists to conduct the safety check as part of their normal quality control work on each prescription, instead of as a separate step.  

The change was easy to make in the centralized enterprise systems that supported CVS’s pharmacy operations, and it was also unignorable —  even if pharmacists were unhappy with the new process, they couldn’t continue to follow the old one once the supporting EIT had been changed.  The new fulfillment process was quickly rolled out across CVS’s more than 4,000 stores, and led to substantial improvements in customer satisfaction.

EIT internalizes the complements of changes in workflows, interdependence, and decision rights, and does so all at once, as soon as the technology is introduced.  Configuring an enterprise system is, to a large degree, the work of defining the new workflows, interdependencies, and decision rights, and  introducing an enterprise system is the work of guiding people into their changed jobs.  None of this is easy work, which helps explain why somewhere between 30-75% of enterprise IT efforts fail, or at least disappoint.

In addition to FIT and EIT, my third category of work-changing IT is Network IT, which lets people interact without specifying the terms of their interactions.  Network IT platforms like blogs, wikis, Wikipedia, flickr, del.icio.us, prediction markets, etc. also internalize the complements listed above, but they do so in a very interesting way.   

They don’t impose new workflows or decision rights up front; they instead let them emerge over time as a result of  interdependencies and preferences among users.  As described in a previous post, Wikipedia’s predecessor Nupedia had a seven-step expert review process for all entries.  When this was abandoned in favor of an almost completely egalitarian and free-form process for generating and refining content, good things started to happen very quickly.  

Within network IT platforms, processes, roles, identities, hierarchy, etc. emerge over time to the extent necessary.  Wikipedia, for example, eventually found that it needed some defined roles and hierarchy among its members, but it hasn’t yet imposed a lot of workflow on entry creation and editing.  Because this blog is starting to attract some comment spam, I’m probably going to have to impose a bit of workflow (I’ll review comments before they get posted).  The best traders in a prediction market aren’t identified in advance based on their status; they’re revealed over time based on their results.   

These examples and many others demonstrate a few key points.  First, network IT platforms internalize the complements of new workflows, interdependencies, and decision rights, just as Enterprise IT does.  Both technology types are closer to digital factories than digital motors.  Second, adopting new EIT and NIT is inseparable from addressing these complements.  A company can buy a novel  function IT and not concern itself with changing workflows and decision rights or making its employees more interdependent (most 1995 America’s Cup competitors, in fact, did just that).  But there’s no way a company can adopt ERP or eProcurement and not confront the fact that workflows are being changed, decision rights are being allocated, and interdependence is increasing.  Similarly, a company like DrKW or Motorola that puts in place an enterprise-wide wiki is going to have to deal with changes in all three areas.  EIT and NIT platforms come equipped with complements.

Third, although Enterprise and Network technologies both internalize complements, they do so in almost precisely opposite ways.  EIT is used by authorities to define  new workflows, interdependencies, and decision rights up front, then impose them quickly across  a sometimes large ‘footprint’ (e.g. 4000+ CVS pharmacies).  NIT creates egalitarian and free-form environments in which workflows are not specified and decision rights not allocated up front; they instead emerge over time to the extent required.  Both types of technology create digital factories: EIT factories are full of orderly assembly lines from day one, while NIT factories start as big empty workshops and eventually get some order.  Perhaps the most important difference between the two technology categories is that most workers welcome the construction of a digital factory of the NIT variety, and are hostile to efforts to build EIT digital factories.  The former give them new freedoms; the latter impose new constraints.  The former are ‘non-credentialist;’ the latter place them into tightly defined hierarchies and roles from the start.  The former let them collectively figure out how work will be done; the latter define it for them.

The point of this post is not to argue that one type of digital factory is better than the other (or more humane, rational, smarter, enlightened, etc.).  There are clearly times when each is appropriate; an ERP system is not great for eliciting tacit knowledge, and a wiki is a lousy way to ensure Sarbanes Oxley compliance.  I also don’t want to give the impression that digital factories (EIT and NIT) are better than digital motors (FIT).  Excel is incredibly useful to me the way it is; HBS and I don’t need to adopt any complements to realize value from this GPT.

My point here is that business leaders have different roles to play when they’re introducing new digital motors than when they’re building new digital factories.  And because EIT and NIT factories are so different, leaders have to do different things to ensure their success.  Their appropriate roles are much more front-loaded and directive with EIT, and more low-key and supportive with NIT platforms.  Once they realize this and act accordingly, IT success starts to become less like a black art and more like part of the normal work of organizational change and business leadership. 

Nick Carr had some thoughts about my Enterprise 2.0 article and post on the same topic.  As always, he got to the heart of the matter, and it’s worth quoting him at some length:

The word ‘strategic’ in IT discussions reminds me a lot of the use word ‘lean’ within my home discipline of operations management.  Both are frequently used, clearly positive, and often held up as goals.  And both are vague, and used so frequently and loosely that they’ve ceased to have any clear meaning.

I firmly believe that IT can be an irreplaceable contributor to competitive advantage, but I don’t believe that this advantage comes from slapping the ‘strategic’ label on a particular system or application, even one that’s valued by customers, revenue enhancing, and necessary for the rollout of new products or services.  A system with all these attributes can be a strategic necessity, which is very different than a strategic resource.

Eric Clemons and Michael Row pointed out that bank ATM machines allowed retail banks to offer a new service (24 hour access to cash), are beloved by customers, and bring in additional revenue¹.  They pretty quickly became strategic necessities; banks had to get ATM networks to stay in business. 

So they got them, either by building their own or joining alliances.  Once they became widespread ATM networks could no longer be called strategic resources, which need to be not only valuable, but also rare, inimitable, and non-substitutable –  the so-called ‘VRIN’ attributes².  Oil wells and diamond mines are perhaps the ultimate strategic resources. 

The VRIN attributes define a high bar, and most information systems just don’t get over it.  A study William Kettinger, Varun Grover, Subashish Guha, and Albert Segars examined thirty companies that put in place ‘strategic’ systems and found that only seven of them were associated with above-average revenue and profitability in two later time periods.³  A recent survey by Peter Weill and Sinan Aral found an interesting reversal.  While ATM machines were losing their status as strategic resources, “much of the advantage [in financial services companies now comes] from higher efficiency in executing basic transactions and providing infrastructure to foster innovation.”⁴  It seems, in other words, that strategic resources can be very hard to identify in advance.

Of course, there are some examples of IT that starts as a strategic resource, and stays that way.  Google’s combination of smart algorithms, vast storage capacity, and processing muscle gives it the ability to return high-quality search results, even in the presence of many attempts to game the system.  This infrastructure is clearly a strategic resource for the company.  I wrote a case on the Japanese cab company MK Tokyo, which developed a system to let consumers find immediately find and dial the closest cab using their Web-enabled phones.  MK has been awarded a patent in Japan for the system, thus taking care of the imitability issue. 

I also wrote a case about Spain’s Inditex, which owns the worldwide chain of more than 750 Zara stores.  These stores are tightly synchronized with Inditex’s vertically integrated production and distribution facilities, allowing great variety, flexibility, and speed while keeping costs low (Kasra Ferdows, Michael Lewis, and Jose Machuca wrote an HBR article about the Zara business model).  The IT that facilitates such tight synchronization, however, is simple to the point of being primitive.  For example:

- Point-of-sale terminals in stores run on DOS and are not networked
- One terminal has a dial-up modem, which is used to transfer files (via the ftp protocol) to and from headquarters
- The same modem is used to transmit digital order forms to and from PDAs, which employees carry through the stores while deciding what to order
- Short-supply clothes are allocated to stores manually, not by an algorithm.
- Back-office activities (purchasing, manufacturing, distribution, accounting, etc.) are not supported by a comprehensive ERP system.

In short, it’s very hard to identify any technology at Zara that meets the VRIN criteria, but the company’s IT supports a business model that has generated enormous value (Inditex’s market capitalization is higher than that of the Gap, a company with more than twice as much revenue) and so far proven impossible to imitate.  This suggests that as we think about strategy and IT we might want to focus less on individual systems, applications, or other discrete pieces of technology and more on two topics:  the capabilities IT provides once it’s up and running, and how these capabilities are folded into business successful business models and competitive strategies.