1.4. The Business Vision for the Information-Enabled Enterprise

As we’ve discussed, the future information environment will have unprecedented volumes and velocity, creating a virtual and constant influx of data, where enterprises that leverage this information will gain a significant competitive advantage over those that do not.

What does the information-enabled enterprise look like? What new capabilities set it apart and above the information powers of today? Looking forward, we can envision new characteristics for an information-enabled enterprise that empower it to combine vast amounts of structured and unstructured information in new ways, integrate it, analyze it, and deliver it to decision-makers in powerful new formats and timeframes, and give the organization a line of sight to see the future and anticipate change.

We can think of this as an evolution from traditional reporting to advanced predictive analytics. Many organizations still struggle with becoming effective reporters, meaning that even their weekly, monthly, or quarterly views of the past are not reliable or complete enough to help them fix what is broken. Some firms are beginning to advance to a level of being able to “sense and respond” where they can measure and identify performance, risks, and opportunities quickly enough to take corrective action based on a workable level of immediacy that is responsive to business stimuli. Then there are a few of the most sophisticated who are on a path to advance to the next step in analytic maturity that involves having the capability to “anticipate and shape.” In this mode, they leverage information in order to predict the road ahead, see future obstacles and opportunities, and shape their strategies and decisions to optimize the results to their ultimate advantage. This concept is shown in Figure 1.2 where you can see the evolution of the information-enabled enterprise.

Figure 1.2. Information-enabled Enterprise Maturity

In an information-enabled enterprise, these capabilities are achieved through better intelligence that is obtained through the sophisticated use of data, empowered by a new analytical vision of Enterprise Information Architecture. Table 1.2 describes characteristics of each phase of this evolution.

Table 1.2. Phases of Evolution

Focus Area	Historical Reporting	Sense and Respond	Anticipate and Shape
Information sources	Information is collected from internal transactional systems.	Event-based information is collected and integrated from transactional, planning, CRM, and external data providers.	Actionable data is analyzed and collected from many sources, including external sources, new instrumented data, and unstructured and societal data.
Processing	Some large databases are processed in batches and create snapshots of the past.	Large quantities of data process and deliver information quickly.	Large quantities of Structured and Unstructured Data are processed in real time.
Source of insight	Personal experience and informed guesswork are used to make decisions.	Many of the most important decision points are supported by data-driven facts.	Analytical tools are pervasive and user-friendly. Information is delivered anytime, anywhere, over the channels and devices of the user’s choice.
Ability to see backward and forward	Historical data is used for “post-mortem” reporting and tracking.	Insights garnered through events enable decision makers to smartly consider future actions.	Sophisticated simulations and modeling are performed to more accurately predict outcomes.
Events	Events are identified and analyzed “after the fact.”	Events are tracked in real time, and sophisticated rules enable the automation and rapid speed of response.	Events are anticipated and actions are taken before the event occurs.
Performance and risk	Although some performance measuring is in place, there is minimal measurement of risk factors.	Action is taken after a risk event occurs.	Actions are taken that mitigate risk and improve performance.
Knowing the facts	Information is coded and interpreted differently by Line of Business (LOB) and departments.	Many departments have integrated views of information.	The organization has “one version of the truth,” which is defined and understood in the same way across the enterprise.
Summaries and details	Information has limited levels of detail and summary.	Information has many levels of detail and summary.	The needs of the individual and the environment are understood at different levels and delivered in personalized views.
Unstructured Data	Content and unstructured information is used only transactionally. For example, it is used for its primary purpose and then discarded or archived.	Vast stores of content are managed and analyzed, including e-mail, voice, Short Message Service (SMS), images, and video on a standalone basis.	Unstructured information is integrated with structured data and used for decision making and as knowledge at the point of interaction/use.
Wisdom and knowledge	Expertise and wisdom are products of experience and networking.	Information is gathered, stored, and accessed through knowledge systems.	New collective wisdom is generated via information and collaboration.
Lifetime of insight	Information is used for monthly, quarterly, and annual reporting.	Relevant information is used across the enterprise, having implications both up and down the value chain (for example, the flow from suppliers to customers).	Information is turned into institutional knowledge and accessed and used in new ways across the extended enterprise.
Integration	Linking of information across boundaries is difficult.	Key systems are integrated to capture important events.	People, systems, and external entities constantly connect and “speak” to each other seamlessly.
Timeliness and access	Users are not provided the information they need to make timely decisions.	Information is delivered in ways that are useful to the context of the situation.	Analytical results are timely, personalized, and actionable.
People	Significant time is spent “chasing and reconciling” data.	Time is spent responding to events as they occur.	People focus on planning, innovation, performance improvement, and risk mitigation.
Innovation	Innovation is seen as a discrete function of research and development or product managers.	Knowledge workers provide innovative responses to events.	Innovation is derived from all segments of the enterprise and from external sources.
Resource management	The enterprise continues to deploy more people to information management.	The enterprise actively seeks to optimize performance by making information more readily available.	Skills and culture are focused on improved analytical decision making at all levels of the organization.
Decision approval	Most decision making is top down and based on financial results.	Formal decision-making processes are in place to expedite approvals and executive sign-off.	Decision-making authority is delegated to more people and requires less managerial and administrative oversight. Employees are encouraged to solve issues immediately and locally.
Incentives	Incentives are aligned to key financial measures.	Incentives are performance- and decision-based.	Incentives are aligned to balanced performance measures with an emphasis on innovation.

 

These characteristics begin to “color in” the information-enabled enterprise. This said, the specific characteristics and capabilities for each enterprise are defined and built based on the needs and priorities of each organization. Determining this mix and establishing a vision for becoming an Information-Enabled Enterprise are the first and most important steps an organization can take on their enterprise information journey.

Case in Point: Smarter Traffic in Stockholm Traffic is a global epidemic. For example, U.S. traffic creates 45 percent of the world’s air pollution from traffic and in the UK, time wasted in traffic costs £20B per year. Stockholm was faced with similar challenges and decided to take action to reduce city traffic and its impact on the environment, especially during peak periods. Critical to addressing this challenge was providing the city of Stockholm with the ability to access, aggregate, and analyze the traffic flow data and patterns required to develop an innovative solution. State of the art information integration capabilities for structured and unstructured (for example, video streams from traffic cameras) data are, thus, a key technical foundation of the solution. As a result of performing this analysis, a new strategy was created that included “congestion charges” to influence the levels of traffic at peak times by using cost incentives to drivers. To accurately apply these charges, the city knew that the system had to be accurate on day one. Eight entrances were equipped with cameras that photograph cars from the front and back. These images are sent to a central data system to read the license plates via an optical character recognition (OCR) system to ensure the right cars are charged. Information is collected, aggregated and analyzed with the resultant simulations and algorithms used to determine fee structures based on road usage and traffic patterns. Stockholm was able to implement the system within two months, and the results have been quite impressive.[5] Over 99 percent of cars are identified correctly. The traffic has gone down 22 percent and air pollution has improved by 14 percent since deployment of the system. Besides innovating a new traffic business model, these improvements were made possible with an information-centric approach and by providing advanced and predictive analytical models to better understand and improve traffic patterns, especially during peak periods. Other cities and countries are interested in the system. The “Smarter Traffic” system does more than paint a picture for the future; it demonstrates how information can be leveraged in new ways to help “drive” a Smarter Planet.

^[5] See [5] for more information on this scenario and its results.