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Lesson 5

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as Prentice Hall

Chapter 12

New business models (e.g., Amazon, iTunes). New products and services (e.g., tablets, mobile banking). New or improved processes (e.g., ERP, supply chain). Cost savings (e.g., self-service, offshore sourcing).

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Comes about through organizational change

Frequently involves experimentation

Is necessary for long-term organizational survival

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Sustaining Innovation – improves a product or service for existing customers.

Disruptive Innovation – targets noncustomers and delivers a product or service that differs from the current product portfolio. It must create and capture new value.

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Continuous Change – Frequent, relentless and endemic to the firm.

Punctuated Equilibrium – assumes long periods of incremental change, interrupted by brief periods of radical change.

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Innovation in an organization lies at the intersection of the answer to three significant questions:

What is viable in the marketplace?

What is desirable to the business?

What is possible with technology?

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Figure 12.1 The Organization’s Strategic for Innovation with Technology

1. Ideation

2. Advocacy

3. Proof of Concept

4. Trial or Pilot

5. Transition or “go to market”

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Communication of value is essential to ensuring innovation is sustainable. From this perspective, value has two components:

1. Is it desirable?

2. Does it build our innovative capabilities?

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Motivate: Establish rewards for innovation.

Support: Create infrastructure to sustain innovation.

Direct: Manage innovation strategically.

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Experimentation is risky.

Incentives and rewards must be provided to support experimentation.

Good ideas can come from any source.

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Infrastructure is needed to support IT innovation and experimentation. Some organizations create formal centers (or laboratories). Intranets are being used to solicit new ideas. Financial support is frequently provided through internal venture support.

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Innovation centers’ strategies: Insulate – Create innovation centers where all lines of business can come together to address common problems. Seeks to take advantage of synergy.

Incubate – Innovation centers are placed within lines of business. Seeks to focus on specific problems or opportunities.

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Strategic IT experimentation must be directed to ensure it is relevant. Link innovation to customer value. Link experimentation to core business processes. Use venture funds to guide strategic initiatives.

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1. Strike the correct balance.

2. Create a sustainable process.

3. Provide adequate resources.

4. Reassess IT processes and practices.

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Focus on achievable targets.

Don’t rush to market.

Be careful with “cool” technology.

Learn by design.

Link innovation to business strategy.

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Incubate innovation.

Collaborate with vendors.

Integrate business and IT.

Send clear messages.

Manage the process.

Promoting learning agility.

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Organizations are starting to grasp the scope of continuous change that is being ushered in by technology and the innovative ideas that come with it.

“Innovation” is what is to come; thus addressing it thoughtfully and intentionally is the best way to ensure that an organization is ready for the future. 12-20

Chapter 13

Social media is the largest component of (online) data for organizations, but it is not valuable if not analyzed. Hence, the key question is:

“How can we use insights from the data we collect to improve our interactions with customers, suppliers or employees” (La Valle et al. 2011)

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Wikis Blogs Videos 3D user interface / visualization Presence awareness Instant messaging, Twitter Social networking communities (e.g., Facebook, LinkedIn) Reputation systems Gamified data

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Companies can then use data to:

Respond more quickly to the market by

making faster decisions.

Make patterns more evident, such as

problems with a new product.

Facilitate innovation in products and services,

based on customer and other types of

feedback.

Improve reputation and brand awareness. 13-25

Sensing – detection location Mass visibility – combination of real- time sensing of multiple entities and relationships. Experimentation – integration of real- time sensing and generate and gather data quickly. Coordination – combination of real-time sensing to adjust behavior.

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Governance

Business Strategy for

Data New Skills and Tools

Improved Data and

Information Capabilities Social

Media and Big

Data Use

Business Value

What are the biggest drivers of our profits?

How can we increase customer loyalty?

Do we have information that is easy to use

and useful?

Dashboards, visualization, trend analysis and simulations and traditional reports are technologies to make information more understandable and actionable.

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Determine what data to collect and how to

get it:

• Transition from siloed data to integrated data.

• Organize data and capture context and meaning.

Data Have four dimensions (Merchand et al. 2000):

• Unstructured

• Structured

• Internal

• External 13-29

Three level of analytics maturity in organizations:

Aspirational – support finance and supply

chain management.

Experienced – support holistic strategy,

marketing, and operations.

Transformational – day-to-day strategy and

operations in a planned and coordinated

fashion.

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Companies should have three sets of

competencies for dealing with big data

(Laney and white 2014; McAfee and Brynjolfsson 2012):

Information management expertise

Business analytic expertise

An analytic-oriented culture

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This process begins by asking the following:

Do we know what data people have socialized around our business and our product?

Do we have an inventory of the data streams in our ecosystem and those surrounding us?

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Have we thought about the data streams we produce? Could they be valuable outside our organization?

How many of our organizational systems could be architected easily to provide data in real time?

Are we keeping an eye on the changing value of our digital assets?

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The answers to these questions can be used to develop new strategic opportunities, such as:

Data generation – create new products.

Aggregation – create a data platform.

Service – create new and/or improve services.

Efficiency – optimize internal operations.

Analytics – develop superior

insight/knowledge.

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Short business horizons Business leaders have shorter time horizon in their thinking than IT and are often not prepared to anticipate new technologies.

Resources Social computing requires support and facilitation to make it effective.

Changing the culture

Organizational behavior must change if the value of social computing is to be realized.

Initial adoption rates are usually high but continuous participation often drops off.

The Vision The IT Manager’s Challenge

Blurred process & org. boundaries Collaboration and sharing Situational applications

Mass participation and accessibility Transient information Supports social behavior Innovation and creativity Viral Dynamic Situational roles Social governance and etiquette Collective intelligence; bottom-up innovation Anywhere/anytime connectivity Ad hoc applications and inquiries

Firewalls and structured processes Intellectual property and privacy protection Maintaining transactional applications and operational integrity Authentication and authorization Creating a permanent record Support business behavior Efficient use of resources Secure Backup Regulatory accountabilities Organizational governance and policy Top-down business strategy Managed data environments Controlled communication Scalable applications

1. Focus – Identify specific problems and then use data and/or social media to solve them.

1. Develop business-savvy IT staff – Promote business-IT rotation programs, and hire power users into IT.

3. Become a “data factory” – Work to improve data quality, usability, and integration.

4. Listening and engaging– Build deliverables that will engage customers with the company and provide superior customer service.

5. Consider hiring a graphic designer – Support IT in developing intuitive and easy interface designs and efforts.

6. Support actions that improve use – Communicate the link between use and value to keep teams focused on usefulness and ease of use in social media/big data applications.

Social technologies and big data will create new information platforms on which ideas that we never dreamed of will surface.

Companies should adopt these technologies in an evolutionary fashion rather than in a “big bang”.

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While all organizations give their customer an “experience” – either positive or negative – few as yet have committed the time and resources to analyze, manage, and improve it on an ongoing and holistic basis (Davies and Thompson 2009).

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Customer encountering new products, services and experiences…are growing less loyal to their brands…Reputations can be built and burned by opinions shared online, “texted” by friends, bloggers and advocacy groups. CEOs told us they need to re-ignite customer interest and loyalty or risk losing ground to competitors (Kortsen 2011).

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Excellent customer experience positively impacts an organization’s bottom line.

Customer experience can be a strong company differentiator –both positive and negatively –thereby affecting sales.

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Consistency and reliability – Products and services that deliver consistently across channels, over time, and as promised.

Knowledge and data – Knowledge about customers’ experiences in order to better understand and act to improve them.

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Timeliness – The longer it takes to accomplish a customer service, the less likely a customer will be satisfied.

Innovation– IT can help the organization improve its customer experience and become a strategic differentiator.

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Cumulative Customer

Experience

Perceptions &

Expectations

Rational experiences

Demo- graphics

Consistency, Reliability, Timeliness, Knowledge, Innovation

Feedback & Action

Product

Price

Channel

Promotion Process

IT is a significant component of the customer experience. Examples of these technologies are:

Customer relationship management (CRM). Interactive voice recognition (IVR). Online and mobile self-service applications. Underpinning technologies (e.g., master data management, knowledge management, metrics, analytics).

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However, the use of technology by no means guarantees a positive customer experience.

Technology often substitutes people resulting in a less satisfying or negative experience.

Technology should be used to create more meaningful and positive experiences.

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1. Visioning – The ability to envision a more creative customer experience.

2. Customer focus –The business and IT functions need to come more customercentric. This will redefine large parts of business process and systems.

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3. Designing for utilization – Three key aspects with IT projects in customer experience: “it must be useful”, “it must be useable”, “it must be used”.

4. Data management–The delivery of complete, current, and accurate data is central to the ability to provide high- quality customer service with IT.

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5. Delivery– Execution is where it all comes together. It is important to have both good technology and knowledgeable and caring staff, who are themselves supported and empowered by good technology.

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Have a central management. Appointing a single senior executive with responsibility to improve customer experience provides executive sponsorship.

Have a clear customer relationship management strategy and value proposition.

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Follow an integrated business and IT strategy to develop a roadmap for improving the customer experience. “One view of the customer and one common set of business rules”.

Identify and develop new capabilities to deal with customers, not just business users.

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Keep working away at the basics – common data, integration across applications and channels and reliability. These are essential to delivering a consistent experience!

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Customer experience is today recognized as being critical to organizations’ current and future success.

IT plays an integral part in almost all customer experience initiatives.

IT function should become more customercentric – customer in mind!

Chapter 15

A set of information manipulation practices, such as query mining, reporting, and interactivity that is linked to but separate from information management practices (including master data management, information architecture data, data quality, data integration).

(Bitterer 2010)

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An evolving ecosystem around the data vision.

Organizational capability that could be used to bring the right data, information, knowledge, and intelligence to bear on a business problem, opportunity, or decision.

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Anticipate the future, instead of reacting to the past. Empower employees’ memory, insight. Sense what is happening in the organization’s environment. Connect internal and external functions and resources. Question the status quo and create new opportunities. Focus on the most relevant information.

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• Transaction data

• Internal structured data

• Internal unstructured

data

• External structured data

• Master data

• External unstructured

data

• Real time data

• IM strategy and

principles

• Enterprise information-

architecture

• Metadata

• Data management

• Data integration

• Data quality

• Data administration

• Reports

• Dashboards

• Data mining

• Information – enhanced

processes

• Queries

• Graphics and

visualization

• Real-time analysis

• Historical, current, and

predictive analysis

• Information – enhanced

products and services

Data Information

Management

Intelligence

Creation

1. The explosion of data – Amount and type of data are increasing exponentially. It is essential to be able to use IT tools and skills to capture, manage, and exploit these new forms of information.

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2. Changing information needs – Increased pressures to deliver “just-in- time” information to make better and faster decisions.

3. Competitiveness – Organizations that are “sophisticated exploiters of data and analytics” are three times more likely to be top performers (Hopkins et al. 2010).

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Perspective – Changing organizational mind-sets and culture regarding data is the biggest challenge.

Lack of business knowledge – “We don’t know what we don’t know and it’s difficult to be perceptive about BI without a full range of knowledge”.

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Lack of sponsorship – In spite of the demand for better information, businesses have been slow to invest in BI.

Silo thinking – This thinking has been exacerbated by the lack of governance and enterprise perspective and has resulted in fragmentation and duplication of data.

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Lack of BI skills – BI sits between the IT function and business and requires both business and technical skills, a combination that is hard to find.

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1. BI strategy and planning – BI plans and strategies need to be inclusive at the high level. BI must integrate both with other business strategies and with the technology and information architectures used by IT to guide its work.

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2. Data acquisition and management – The ‘holy grail’ of IT is to have a single authoritative source for all data. Duplicate data, multiple data marts, and inflexible data warehouse cannot incorporate new forms of data.

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3. Information management – This involves improving the value that can be obtained from data by developing a framework within which information can be developed from it (e.g., data integration, information architecture, data integration, aggregation, quality, privacy).

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4. Intelligence delivery – This delivery cannot be done in a structured way because the business environment is too dynamic. While IT can provide the data, the tools to manipulate it, and the mechanisms to present it, the right questions or doing the right analysis still need to happen.

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Learn from the past – Learning about how people utilize knowledge for action and then using this as the basis for improving an organization’s intelligence is critical for successful BI.

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Have a strategy for continuous improvement – Successful BI initiatives consistently anticipate the need to maintain and improve the quality and type of information provided.

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Focus – BI initiatives are challenging; therefore, a clear focus on targeted difficult points where BI can make a difference is essential. Successful initiatives take “a relentless focus on a very limited set of burning business questions to guide users to BI-enabled decisions with maximum impact” (Roberts and Meehan 2010).

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Cross-functional governance – Effective governance processes (e.g., data governance, BI governance) are central to BI success. BI governance is needed to focus BI and develop a plan for its evolution.

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Acquire new IT and analytics skills – IT staff need the skills to bridge the gap between traditional business and technical areas of expertise. Examples of skills include: analytical to test hypotheses, to predict future trends, and to discover new patterns; visualization and simulation skills.

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Take process views – The key to success is to focus on a process that really matters to the business and to design the analytic capabilities needed to enhance it.

Move from the inside out – BI is still maturing and should be implemented as an experimental approach. It should grow organically rather than as one-time initiative.

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Tell stories to articulate value – The value of BI is still difficult to document with quantitative benefits. Thus, the value is best articulated qualitatively.

Watch out for implementation– Access to intelligence is not enough, managers need “practical wisdom” to make prudent judgments.

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BI is not a new idea, but it is one that constantly gets renewed due to new powerful technologies and constantly- increasing data.

The holistic view of BI includes both IT foundations of data and information management and the uses to which these can deliver value.

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IT has the opportunity to take a leadership role in BI, but its ability to do so will depend on how much it understands about the business and the integration of technical and business knowledge.

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