let’s delve into what we consider the highest value stream in information systems. We’re essentially talking about IT-created value. If you think about it, pretty much every paper that’s related to information systems has IT value as its underlying theme. Because if IT doesn’t create value, then what are we doing studying it? That would mean we’re not very valuable as researchers, right? Dealing with a technology that doesn’t enhance value would be a futile endeavor.
The IT value stream is fundamental to what we do. When we talk about value, we’re mostly referring to economic value. Now, certainly, IT can affect quality of life, improve process efficiency, and influence various intermediate variables that lead to economic value. But the value stream is largely about one key question: Does IT create economic value?
Now, a lot of these research streams started gaining traction around the 1980s—let’s say around 1987. We had a series of studies known as the productivity studies. Many of these were championed by Erik Brynjolfsson at MIT—he’s at Stanford now, but back then he was at MIT. He conducted numerous studies examining how IT improves productivity. And during that time, a common phrase emerged: the “productivity paradox.”
The Productivity Paradox
The productivity paradox refers to the observed disconnect between substantial investments in information technology and the lack of corresponding growth in productivity metrics. In 1987, economist Robert Solow famously stated, “You can see the computer age everywhere but in the productivity statistics.” This paradox was further highlighted by Stephen Roach of Morgan Stanley in the 1980s. He observed that despite the widespread adoption of computers across various industries—including manufacturing, services, and banking—there was no corresponding increase in productivity statistics.
So, we had this big push towards computerization, not just in manufacturing but also in the service industry and the banking sector. Companies were investing heavily in technology. The question was: Why aren’t we seeing a significant increase in productivity in these industries, despite all this IT investment?
It was very curious. Dozens of studies were conducted by highly qualified researchers—economists, information systems scholars—but they consistently found no significant productivity improvements linked to IT investments. This led to a lot of confusion and debate. The dilemma often centered around the question of measurement.
The Measurement Dilemma
So, let’s delve into this measurement dilemma. How do we accurately measure productivity in the context of IT? Let’s take the banking industry as an example.
Banking Industry Example
In the banking industry, a common productivity metric used was the number of checks processed per hour. The idea was that the more checks you process, the more productive you are. Now, with the introduction of technology like ATMs, what happens to the number of checks processed? It decreases.
Why? Because ATMs provide customers with convenience—they can withdraw cash 24/7 without needing to write or process checks. So, the traditional metric—the number of checks processed—actually goes down with the advent of technology.
This presents a problem: If our productivity metrics don’t capture the benefits that IT brings, then we’re not measuring productivity accurately.
Impact on Traditional Metrics
This is the measurement dilemma. If we use traditional productivity measures, we might find a negative relationship between IT investment and productivity. That’s because while customers are gaining significant benefits—like convenience and improved service—these benefits aren’t reflected in the traditional productivity statistics.
Traditional Metrics: Number of checks processed per hour.
IT Impact: Introduction of ATMs reduces the number of checks processed.
Result: Productivity appears to decline using traditional metrics.
Reassessing Productivity Measures
So, what’s happening here? The productivity measures we’re using are not capturing all the benefits that IT provides. They’re easy to measure—it’s straightforward to count the number of checks processed—but they don’t account for the intangible benefits like customer satisfaction, convenience, and service quality.
Consumer Benefits Not Captured
- Convenience: Customers can access cash anytime.
- Service Quality: Faster and more efficient transactions.
- Customer Loyalty: Improved services can lead to increased customer retention.
These benefits are tough to measure using traditional productivity metrics.
Advancements in the 1990s: Improved Data and Lagged Models
Moving into the early 1990s, the data we had improved significantly. We had access to panel data, which allowed us to track individual companies over time. This meant we could get better metrics on IT dollar investments and their impact on the bottom line, such as revenue and profitability.
Mixed Findings Persist
However, even with this improved data, the studies showed mixed findings:
- Some found positive relationships between IT investment and firm performance.
- Others found negative or non-significant relationships.
This inconsistency led researchers to consider the timing of the benefits.
Lagged Models and the Lag Effect
Researchers posited that when you look at IT investment in year X and try to measure the benefits in the same year, you might not see the true impact. That’s because the benefits of IT investments may not accrue immediately. There may be a lag effect.
Why the Lag?
- Organizational Adjustment: Implementing new technology requires changes in workflows and processes.
- Training: Employees need time to learn and adapt to new systems.
- Integration: New systems need to be integrated with existing infrastructure.
Implementing Lagged Models
So, researchers started using lagged models, where:
- IT Investment: Measured at time X.
- Benefits: Measured at times X+1, X+2, X+3.
By accounting for this lag, they began to find more positive results. A number of papers in the 1990s concluded that we had resolved the productivity paradox—at least partially—by recognizing that IT benefits are often realized over time.
The 2000s: Emphasis on Process Change and Reengineering
Now, moving into the 2000s, more work was done on IT and firm performance within this value stream. Studies published in top journals like MIS Quarterly and Information Systems Research began to show that IT creates value, especially when considering contextual factors.
Contextual Factors
- Organizational Change
- Process Change
- Management Practices
This was the era when reengineering was a big buzzword in corporate America and around the world. Companies were reengineering business processes to become more productive because they realized that their traditional processes were built for markets that no longer existed.
Business Process Reengineering (BPR)
There was a realization that to truly get the benefits from technology, you had to change the process to match the technology.
Key Thought Leaders
- Michael Hammer
- Thomas Davenport
They wrote important books on reengineering in the 2000s. The mantra was:
“If you automate a mess, all you’re going to get is an automated mess.”
In other words, if you take a bad process and automate it, you’re not going to see significant productivity impacts. The only way to see productivity improvements is if you reengineer the process to take advantage of technology.
Case Study: Mutual Benefit Life
Let’s look at a classic example: Mutual Benefit Life, an insurance company.
Traditional Process
- Sequential Steps: Claim processing involved multiple specialized steps handled by different people.
- Underwriter: Person 1
- Verifier: Person 2
- Medical Expert Consultation: Person 3
- Disbursement Officer: Person 4
- Specialization: Each person focused on a narrow task.
- No Ownership: No one took responsibility for the entire application.
Why Was It Designed This Way?
- Efficiency Models: Influenced by Frederick Taylor’s principles of scientific management.
- Specialization: Belief that doing the same task repeatedly increases efficiency.
Problems with the Traditional Process
- Customer Service Issues: When customers called to check the status, no one knew the entire picture.
- Inefficiency: Passing the application through multiple hands caused delays.
- Lack of Accountability: No single point of contact for the customer.
Reengineering at Mutual Benefit Life
New Process Design
- Case Managers: Assign a single case manager to each claim.
- Technology Support: Provide powerful IT tools to assist case managers.
- Expert Systems: For underwriting and verification.
- Communication Tools: Email, messaging systems.
- Responsibility: Case managers handle the claim from start to finish.
Outcomes
- Improved Customer Service: Customers had a single point of contact.
- Increased Productivity: 75% increase in productivity.
- Efficiency Gains: Reduced delays and errors.
Case Study: Ford Motor Company
Traditional Accounts Payable Process
- Large Workforce: 500 people in the accounts payable department.
- Specialized Tasks: Multiple steps with specialized functions.
- Paper-Intensive: Manual processing of invoices and payments.
Reengineering at Ford
- Common Database: Integrated departments into a shared database.
- Process Automation: Leveraged IT to automate repetitive tasks.
- Staff Reduction: Reduced staff from 500 to 100.
Outcomes
- Cost Savings: Significant reduction in labor costs.
- Efficiency: Streamlined processes and reduced errors.
- Improved Data Accuracy: Centralized information reduced discrepancies.
Key Takeaway
The critical point here is that IT and process change together create performance benefits. If you just throw IT at a problem without changing the underlying process, you’re not necessarily going to create dramatic impacts.
Complementary Assets and Competitive Advantage
Now, another key conclusion from numerous studies is that IT creates value under certain conditions.
What Are These Conditions?
- Right People: Skilled workforce capable of leveraging IT.
- Right Management: Leadership that understands and supports IT initiatives.
- Right Culture: Organizational culture that embraces change and innovation.
- Right Knowledge Assets: Data and expertise that can be harnessed by IT.
- Right Structure and Policies: Organizational structures that support agility and responsiveness.
These are known as complementary assets.
Why Are Complementary Assets Important?
Because IT by itself is often undifferentiated. It’s a commodity.
- Accessibility: Hardware and software are available to everyone.
- Non-Differentiating: If I can buy a network or a PC, so can my competitor.
So, where does competitive advantage come from? It’s from how you integrate IT with complementary assets to create unique IT capabilities.
Examples of Complementary Assets in Action
Otis Elevators
- Technology: Installed cellular boxes in elevators for remote diagnostics.
- Complementary Asset: Vertically integrated maintenance services.
- Competitive Advantage: Ability to fix elevators remotely and provide superior service.
Walmart’s Supply Chain
- Technology: Advanced inventory management systems.
- Complementary Asset: Long-standing relationships with suppliers.
- Competitive Advantage: Efficient supply chain that’s difficult for competitors to replicate.
Thomson Holidays
- Technology: User-friendly website offering various holiday packages.
- Complementary Asset: Negotiated deals and relationships with hotels, airlines, and service providers.
- Competitive Advantage: Ability to offer unique packages and pricing.
Causal Ambiguity and Sustainable Advantage
Causal Ambiguity: When the exact reasons for a company’s success are not clear to competitors.
- Visible Assets: Competitors can see and replicate the technology.
- Invisible Assets: Complementary assets like culture, relationships, and expertise are hard to copy.
- Result: Competitors can’t easily imitate the full value proposition.
Value Creation vs. Competitive Advantage
There’s a difference between IT-based value creation and IT-based competitive advantage.
Value Creation
- IT can create value by improving efficiency, customer service, and more.
- Example: Introducing an ATM improves customer convenience.
Competitive Advantage
- Sustainability: Competitive advantage is about sustaining value that competitors can’t easily replicate.
- Commoditization: Over time, technologies become standard and lose their differentiating power.
- Example: ATMs became a competitive necessity, not a competitive advantage.
Value Appropriation
Value Appropriation: Capturing the value created so that it benefits your organization.
- Risk: Competitors may copy your innovations and dilute your advantage.
- Strategy: Protecting your unique complementary assets is key.
- Advice: Be strategic about launching new IT products—ensure you can appropriate the value.
Latent Value and Option Thinking
IT Value Could Be Latent
- Definition: The value may not be immediately apparent or realized.
- Building Options: Investing in IT to create future opportunities.
Option Thinking
- Analogy to Financial Options: Similar to buying call or put options in the stock market.
- Minimal Investment: Spend a little now to keep the option open for future gains.
- Example: Investing in a new technology standard before it’s widely adopted.
Advancing the IT Value Stream
To continue advancing this research stream, we need to focus on:
1. Co-Created Value
- Definition: Value created collaboratively among multiple organizations.
- Example: Citibank partnering with retailers to offer double miles on purchases.
- Research Focus: How is value co-created and distributed among partners?
2. Vision-Driven Capability Development
- Traditional Model: IT Investment → Value
- New Approach: Business Capability Vision → IT Investment → Value
- Example: An insurance company envisioning customers filing claims at the accident site via mobile apps.
- Research Focus: How do organizations develop visions and configure IT to achieve desired capabilities?
3. Value Expansion
- Beyond Profitability: Value includes flexibility, agility, customer satisfaction, etc.
- Example: IT that enables a company to respond quickly to market changes.
- Research Focus: How do expanded notions of value contribute to overall performance?
Event Studies and Stock Reactions
Researchers are also examining stock market reactions to IT investments.
Methodology
- Event Studies: Analyze stock price reactions to public announcements.
- Tools: Software like Eventus for data analysis.
Application
- Example Research Question: Does announcing an AI investment lead to positive stock reactions?
- Data Sources: Public announcements, 10-K reports, press releases.
- Analysis: Link characteristics of IT investments to stock performance.
Conclusion
In summary, the relationship between IT and value is multifaceted and evolving.
Key Points
- IT Does Create Value: Especially when combined with process change and complementary assets.
- Competitive Advantage: Arises from unique configurations of IT and complementary assets.
- Multi-Level Impact: IT affects individuals, groups, organizations, markets, and society.
- Strategic Considerations: Value appropriation and option thinking are critical for sustained advantage.
- Future Research: Should focus on co-created value, vision-driven capabilities, and expanded notions of value.
By understanding these dynamics, organizations can better leverage IT investments to achieve sustainable value and competitive advantage in today’s digital landscape.
Final Thoughts
So, as we move forward in this field, it’s crucial to recognize that IT value creation is not just about the technology itself. It’s about how technology is integrated with people, processes, and organizational structures. It’s about strategic vision and the ability to adapt and innovate. By focusing on these areas, we can continue to unlock the full potential of IT in creating economic value.
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