Topic 5 Innovating with Technology, Systems and Information PDF

Topic 5: Innovating with Technology, System and Information ISP680 – CORPORATE STRATEGIC INFORMATION SYSTEM PLANNING Lecture Outline Understanding What it Means to Innovate with IT The Process of Digital Business Innovation Getting Management Attention for Ideas and Innovations Innovating by Leve...

Topic 5: Innovating with Technology, System and Information ISP680 – CORPORATE STRATEGIC INFORMATION SYSTEM PLANNING Lecture Outline Understanding What it Means to Innovate with IT The Process of Digital Business Innovation Getting Management Attention for Ideas and Innovations Innovating by Leveraging Information: Exploration and Exploitation The Big Data Challenge Discovering Strategic IS/IT Opportunities from Information Building an Analytic Capability Understanding What it Means to Innovate with IT Organizations often talk about being innovative but do not fully understand what this actually means. By seeking to be innovative, an organization is, in effect, becoming an early adopter of a new technology or application as a means of pursuing competitive or strategic advantage from IS/IT. Understanding What it Means to Innovate with IT Adoption timing Competitive Impact Know-Why Know-How Adopt early Competitive Shaping strategic Emergent High advantage move Adopt with Competitive parity Avoiding disadvantage Likely to be scarce RISK majority Adopt late (if al Competitive survival IS/IT a cost of doing Likely to be plentiful all) business Low The adopter’s dilemma: Balancing opportunity and risk Understanding What it Means to Innovate with IT Cutting-edge versus “Old” Technology: Busting the Innovation Myth Innovation is ONLY associated with deploying cutting-edge or bleeding-edge technology  The applications of ‘old’ IT can also impact process innovation  Agility – the use if existing IT capabilities to rapidly generate new business value, while limiting costs and risks  Information as a source of innovation The process of Digital Business Innovation Idea Generation Awareness Evaluation Implementation Assimilation The process of Digital Business Innovation This stage involves identifying, understanding and appreciating the innovation and the Idea Generation opportunity it potentially offers or the problem it solves. This stage is concerned with generating new ideas, discovering new technologies and envisioning how they could potentially be leveraged. For those ideas that emerge from the IS/ IT unit and deemed to have potential, getting the attention of management can be a challenge. This stage is concerned with Awareness ensuring that buy-in for the idea is achieved and might entail developing a prototype to 'prove' that it works and demonstrate the potential benefits.  The process of Digital Business Innovation This includes deciding whether, how and when to undertake the innovation and make resource commitments, which is normally based on business judgement - managers' opinions of the potential of the ideas, not just quantitative criteria. Those ideas not expected to have a major impact are filtered out. 1. Business relevance filter - Is the technology applicable to a current business problem or need? How novel is the new technology? Does it have the potential to provide a new source of competitive Evaluation advantage, or is its impact likely to be in the areas of improving operational efficiency and cost reduction 2. Technical compatibility filter - Is the technology compatible with existing IT infrastructure and business application investments? How easy or difficult will integration with existing IT components be? 3. Economic filter - Is the technology affordable or cost prohibitive within approved IT operational and capital budgets? 4. Supplier compatibility filter - Is the technology commercially viable or still in the early stages of development? Is the vendor a viable company and does it meet vendor acceptance criteria? Is this a company we want to do business with? The process of Digital Business Innovation This stage is concerned with undertaking a project or programme to deploy the technology and managing any change or diffusion that may accompany the Implementation implementation, which may include changes to be made by customers or suppliers within their organizations. This final stage is where the new innovation is absorbed into practices and Assimilation routines within the organization or fundamentally transforms the dynamics of competition within an industry or the structure of its ecosystem.  Factors Impacting the Process of Business Innovation with IS/IT Industry discourse around technology Industry Business Business cycle customers Supplier and business partners Analyst predictions Influences Influences Competitors Vendor promotions Company strategy Opportunities/ Risks Pull Firm Context Process for Innovating with IS/IT Innovation Outputs Business models Strategic posture of Products Idea Services organization Awareness Evaluation Implementation Assimilation Generation Process Management Strategic role of IT Customer experience Push Capabilities/ Constraints Smart technologies Skills and resources Mobility Technology Organization Financial commitments Collaboration Digital literacy of management Social Computing Influences Influences Management support RFID tags Company priorities Process of innovating with IS/IT and factors influencing it  Getting Management Attention for Ideas and Innovations  the proposed innovation lacks 'legitimacy’  an idea might be very relevant and offer significant opportunities, it can still fail to gain any traction in the organization. 1. Build the trust of those who are likely to be affected Gaining 2. Be honest about upsides and downsides 3. Understand your audience well Legitimacy for 4. Work toward win/win 5. Use more than information Ideas… Innovating by Leveraging Information: Exploration and Exploitation Exploration is using information to generate new knowledge, for example about customers, operations, the supply network or the marketplace. This information may be internally generated from operational and transactional data or result from direct interactions with customers, suppliers or the wider ecosystem. Sometimes it may come from external sources, such as comments about products or services posted on Facebook or tweets on Twitter. Some of the ways that data is being explored include: modelling risk, conducting customer churn analysis, predicting customer preferences, targeting ads, and detecting threats and fraudulent activity. This often requires datasets from diverse sources to be combined and examined.  Innovating by Leveraging Information: Exploration and Exploitation Exploitation is harnessing information to reduce Example: Just-In-Time transaction costs or to take advantage of information asymmetries. Manufacturers often hold stocks of raw materials to buffer against uncertainty in their supply chains - often referred to Asymmetries arise when one party to a transaction/ as 'safety stock'. This uncertainty is caused by having an incomplete picture of production processes, schedules and interaction or potential transaction/interaction has stock levels al suppliers. Making this information available more or better information than the other party. to the manufacturer reduces uncertainties caused by these information asymmetries. Armed with this information, By identifying where these asymmetries exist, an manufacturers no longer need to tie up working capital in organization can create opportunities to change what raw material inventories and can execute a Just-In-Time (JIT) the organization does via a system, providing a strategy. JIT is essentially about replacing inventory with information. source of competitive differentiation.  Innovating by Leveraging Information: Exploration and Exploitation Data Operational The relationship between Exploration Exploitation exploration and exploitation Competitive advantage Knowledge discovery/ insight Improved decision making New value propositions New business models The Big Data Challenge Powerful analytical tools can now enable the processing, modelling and synthesis of vast quantities of data, which together with visualization tools can help in the process of discovering new knowledge. Manager + Information = Decision or insight Requires Manager + More/ Better Information = Better Decision or Insight Decision- Insight making May lead to Discovering Strategic IS/IT Opportunities from Information Being competitive in marketplaces that are increasingly global, volatile and uncertain requires companies to be innovative to prosper, not just in their products and services but also in how they compete in their chosen market. They therefore need to know in considerable depth what their customers and competitors are doing or are likely to do, and also how to leverage this knowledge into concrete actions. As more and more products and services become commoditized, the more 'know-how' about customers' and potential customers' needs and preferences becomes the added-value an organization must have in order to be a chosen supplier, rather than straightforward 'product excellence'. Discovering Strategic IS/IT Opportunities from Information Creating New Knowledge and Learning Socialization - sharing of tacit and explicit knowledge by individuals through observation, imitation and practice (i.e. without verbalisation). Combination - combining sets of explicit knowledge held by individuals through social processes. Externalization - involving interaction between explicit and tacit knowledge through social dialogue to create ·shared concepts, normally within a team and often involving the use of metaphor. Internalization - is seen as closest to traditional organizational learning, although action is seen as an important component.  Discovering Strategic IS/IT Opportunities from Information Techniques for Discovering Strategic Opportunities Data Known Unknown Known knowns - things we know we Known unknown - things we know we know don’t know Defined E.g. Dashboard and report E.g. Assessing whether a new product Question will be a success Unknown knowns – things we don’t Unknown unknowns – things we don’t Undefined know we know know we don’t know e.g. Roll Royce e.g. Google  Discovering Strategic IS/IT Opportunities from Information Defined question/ known data. This is where the questions to be answered are already known and the data needed to help answer the questions have Data Known Unknown already been identified. Known knowns - things we know Known unknown - things we know we Defined we know don’t know These are the known-knowns - things that we know we know. Standard or E.g. Dashboard and report E.g. Assessing whether a new product Question will be a success regular reports can often provide answers to these types of questions. Unknown knowns – things we don’t Unknown unknowns – things we know we know don’t know we don’t know Undefined e.g. Roll Royce e.g. Google Example - Financial reports, sales reports and reports showing actual performance against target indicators (KPis)  Discovering Strategic IS/IT Opportunities from Information Known data/ Un-defined question. This situation exists where there is data in the organization chat might reveal something about customers, operations, Data Known Unknown suppliers or even competitors, but the question to uncover this knowledge Defined Known knowns - things we know we know Known unknown - things we know we don’t know has not yet been posed. E.g. Dashboard and report E.g. Assessing whether a new product will be a success Question Unknown knowns – things we don’t Unknown unknowns – things we know we know don’t know we don’t know Undefined e.g. Roll Royce e.g. Google Example: Rolls-Royce - collects terabytes of telemetry data on the performance of its aero-engines. The company knows that in this data there is knowledge that has not yet been revealed about the engines. The challenge is to construct an inquiry to uncover this, as these are the unknown-knowns,  Discovering Strategic IS/IT Opportunities from Information Defined question/ un-known data. In this scenario there is something that we wish to know and a reason for wanting to know it - 'if we knew x, then we Data Known Unknown could y’. Known knowns - things we know Known unknown - things we know we Defined we know don’t know However, the data to provide· an answer to this question has not yet been E.g. Dashboard and report E.g. Assessing whether a new product Question will be a success identified; this is the known-unknown - things we know that we don't know. Unknown knowns – things we don’t Unknown unknowns – things we know we know don’t know we don’t know Undefine d e.g. Roll Royce e.g. Google Sometimes this will demand refining the question as well as identifying potential sources of the required data and how it might be obtained or accessed. lt may take a number of iterations to find the question/data combination that can deliver an answer that is at least a close approximation to what is needed to be known in order to proceed. This is traditionally the domain of market and consumer research.  Discovering Strategic IS/IT Opportunities from Information Undefined question/ un-known data. This situation acknowledges that there is new knowledge to be discovered but hat we have yet to either pose the Data Known Unknown question or identify the relevant data. Known knowns - things we know Known unknown - things we know we we know don’t know Defined These are the unknown unknowns. E.g. Dashboard and report E.g. Assessing whether a new product Question will be a success Unknown knowns – things we don’t know we know Unknown unknowns – things we Example - Google announced some time ago that it was collecting as much don’t know we don’t know Undefine d e.g. Roll Royce e.g. Google data as it could even though at this stage it didn't know how it was going to use it or what it might tell them.  Discovering Strategic IS/IT Opportunities from Information This is all about challenging existing decision making and knowledge What are the questions that we don' t have answers for? discovery processes and data (in reports, dashboards, databases etc.) Why do we not have answers to these questions? Are we asking the right questions? What data do we need lo answer these questions? Are we using the right data to support decisions? If no constraints What data do we already collect? What new data do we over information available, would different data set be used? need? What biases/assumptions are in the data that we are using to answer these questions? What biases/assumptions are in the decision making process/knowledge discovery process? Can decision making be automated (e.g. prognostic ·and diagnostic tools)? This is where you really need to be creative! What does company not know that it doesn’t know? Organization probably has data that could potentially be valuable What is the data the we currently collect revealing? What biases/assumptions are in the data? What questions should we be asking of the data? Mapping a big data initiative to Does the data enable us to rethink the value proposition to customers? discover knowledge. Building an Analytic Capability Make sense Manage data Act of understanding of information Data Information Knowledge Action Result Three components of an analytics capability  Building an Analytic Capability Make sense of information: within the Manage data: having accurate, timely and organization the data/ information must be quality data is the foundation of an analytics interpreted and meaning ascribed. It is capability. Without this, its utility and through this process that new knowledge is ultimate value is diminished. discovered and understanding given to Act on understanding: the events and situations. organization must have the An analytical capability requires a solid ability to act on insights foundation of information, requiring It is people, not technology, who ultimately and make appropriate standardized data management practices, give meaning to data and assess its decisions. It must be able to common architecture for integration, relevance. respond to the sense that portability and storage plus strong people make of data and take information governance mechanisms. Sense making is also a social process where real action. collaborating employees, often from different This competence provides areas of the business and with different the foundation for sense making. specializations, together discover new insights.