Case Management: Combining Knowledge With Process

BPTrends ▪ July 2009

Case Management: Combining Knowledge with Process

Case Management: Combining Knowledge
With Process

Executive Summary
Case Management is critical to the work of many organizations but is often intensely manual,
paper-driven and plagued by delay and poor visibility. Primarily this is because Case
Management requires supporting knowledge work, where many of the important steps take place
in people’s heads or through collaboration with colleagues, making knowledge intensive
processes difficult to analyze and structure. Also, because cases are primarily driven by human
participants reacting to changing context, cases do not follow a predetermined path defined in
advance – they lack predictability, making them difficult to automate.
Case Management is important because knowledge workers are important. Between 25% and
40% of the workforce can be classified as knowledge workers today, and this proportion will
increase. Knowledge workers also have a disproportionate impact on the success and growth of
the organizations they work for. The most important processes in most organizations involve
knowledge work – they add the most value and have the greatest impact on long-term success.
But processes and the knowledge required to execute them have generally been badly
integrated.
Various technologies have been proposed for supporting Case Management, including Customer
Relationship Management and Content Management Systems. While these technologies play a
role, they are not sufficient to address the key requirements of these types of processes.
Specifically, they can’t handle the requirement to initiate arbitrary new processes during the
progress of a case based on the discretion of the human participants.
Case-oriented Business Process Management [BPM] is the ideal way to help knowledge workers
become more effective in their work. Case-based BPM enables organizations to strike the
appropriate balance between creating procedures for repetitive and mundane aspects of
knowledge work while providing scope for the creative and discretionary elements. BPM-based
Case Management can combine knowledge and process effectively, support the ad hoc and
unpredictable nature of cases, and coordinate a range of other technologies to appropriately
support knowledge intensive processes.
In this white paper we define case management in more detail, relate it to the broader subject of
how knowledge workers do their jobs, and identify the characteristics that have made knowledge
intensive processes difficult to automate in the past. We show how a Business Process
Management approach with specific support for knowledge intensive processes provides the
most appropriate solution to Case Management.


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BPTrends ▪ July 2009

Case Management: Combining Knowledge with Process


What is Case Management?

“For about fifteen years I’ve been doing research on business processes and how they can be
improved. I’ve come to the conclusion that the most important processes for organizations today
involve knowledge work. In the past, these haven’t really been the focus of most organizations –
improving administrative and operational processes has been easier – but they must be in the
future.”
Tom Davenport, “Thinking for a Living”i
Case Management is critical to the work of many organizations, and is a common approach to
supporting knowledge intensive process. Case management, also known as case handling,
describes the way organizations such as government agencies, banks, big legal firms and
insurance providers handle complex customer and service interactions. When a customer
initiates a request for some service, the set of interactions with that customer and other relevant
participants from initiation to completion is known as the ”case”. In the past, cases would have
been managed using a manila folder of documents and records, with the folder moving through a
department or organization from one in-tray to the next while the case was evaluated and
progressed. Evaluation of the case would involve correspondence, phone calls, meetings and
notes being appended to provide a record of the progress of the case. The staff working on the
case, known as ”case workers”, would be knowledgeable about their organization and how
previous cases had been progressed, and would be empowered to use their judgment and
discretion when deciding how some part of the current case should be handled. Cases might
follow a general pattern, but each particular case would take its own unique path from initiation to
resolution depending on the circumstances of the individual whose case was being handled.
Case management is often intensely manual, paper-driven, plagued by delay and poor visibility,
with isolated parts of the process automated by legacy systems or spreadsheets. There are two
main reasons why case management is so poorly supported. Firstly, it is inherently more difficult
to automate than other processes because of the extent to which cases processes must support
human knowledge, judgment and discretion to determine their outcome. It is harder to manage
the complexity and unpredictability of a case than, say, automating payroll processing or credit
card transaction processing. Secondly, the available technology simply hasn’t been able to
support the requirements for dynamic-user driven changes to cases as they progress.
Let’s look at the characteristics of case management a little more closely before considering how
it can be properly supported by technology.
Side-Bar: Defining Case Management
There are no universally accepted definitions available for case management. We define it as
follows:
Case Management is the management of long-lived collaborative processes that coordinate
knowledge, content, correspondence and resources to progress a case to achieve a particular
goal; where the path of execution cannot be predetermined in advance of execution; where
human judgment is required to determine how the end goal can be achieved; and where the state
of a case can be altered by external out-of-band events.







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BPTrends ▪ July 2009

Case Management: Combining Knowledge with Process

Side-Bar: Examples of case management
Area
Case type
Government
Social welfare benefits applications
Licensing and permits management
Freedom of Information Enquiries
Planning applications
Industrial Health and Safety Enforcement
Immigration applications
Regulatory monitoring
Law enforcement
Firearms licensing
Investigations
Forensics management
Financial Services
Corporate customer on-boarding
Regulatory compliance management
Insurance claim processing
Trade Settlement exception management
Telecommunications
Customer provisioning
Fault reporting and resolution
Billing issue resolution


Characteristics of case management
Case management scenarios share a lot of common characteristics. Case workers need to
manage a complex set of steps from the start of a case through to its completion, usually
involving interaction with others in their organization and with external agencies, and requiring the
generation of correspondence, documents and records. The key characteristics of case
management include:
• Knowledge-intensive: Typically case management processes require the intervention of
skilled and knowledgeable personnel. Staff acquire their knowledge through their
experience of working on similar cases and through collaboration with more experienced
colleagues, becoming thoroughly familiar with the tacit and explicit rules governing how
cases should be managed. These staff have to deal with issues that can be ambiguous
and uncertain and that require judgment and creativity. Managing knowledge so it stays
within the organization and is passed quickly to new members of staff is a challenge.
• Variability: While a particular type of case will share a general structure (e.g. handling
benefits applications), it is not possible to predetermine the path that a particular instance
of a case will takeii. A case can change in unpredictable, dynamic and ad hoc ways as it
is progressed through an organization. Certain elements may be fixed (e.g. the end-to-
end duration for completing a case may be set to 18 months, or a fixed budget may be
allocated to each case) but there can be considerable variation in how steps are
executed, based on the particular circumstances of the case.
• Long Running: cases can run for months or years, and are generally much longer
running than the shorter interaction cycles handled by standard customer relationship
management (CRM) systems. Because a case is long running, it changes hands over
time, different people work on different aspects and no single individual has an accurate


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BPTrends ▪ July 2009

Case Management: Combining Knowledge with Process

view of the case as a whole. This drives the need for a supporting case management
system that can provide a single consolidated picture of the case.
• Information Complexity: Case management almost always entails the collection and
presentation of a diverse set of documents and records. Emails, meeting notes, case
documents and correspondence related to a case must be easily accessible to the
appropriate case worker at the right time. This is often difficult for case managers to
organize and manage efficiently, with the danger that an important record, note or file will
be unavailable, lost or overlooked when it is needed. Retrieving the correct information
required at a particular decision point usually depends on the knowledge of the case
worker and an adequate physical filing system.
• Collaboration and Coordination: case workers usually need to co-ordinate interviews
and meetings among interested parties, e.g., scheduling an interview with an applicant,
with other staff in the organization, with legal representatives. Many cases require a
team-based approach, with different specialists working on different aspects of a case or
acting as consultants to their colleagues. These team members need to be able to
access case information and discuss it with each other. Collaboration is particularly
important in knowledge-based case management because workers rely on each other’s
advice and experience when making decisions on a case.
• Multiple Participants, Multiple Roles: There are often a range of involved parties, either
directly or indirectly related to a case, who play different roles during the lifetime of the
case – e.g. applicant, witness, claimant, injured party, appellant etc. There can also be a
large range of staff roles required to complete a case end-to-end. And case workers can
fulfill different roles in different types of cases.
• Cases Can Be Interrelated: The outcome of separate cases may have an impact on
each other. For example, an application for citizenship by an individual may be affected
by the success or failure of an application by a spouse or immediate relative. Cases can
be explicitly linked or they may be linked by inference and conducted with this inferred
link in mind.
• Critical Nature of Timescales: While cases may have great variability in how they are
completed, very often there are inflexible requirements for end-to-end timescales, driven
by legislation or Service Level Agreements.
• External Events Affect cases: external, out-of-band events and intervention can change
the state of a running case, e.g., a phone call from a lawyer or the unscheduled arrival of
compliance documentation.
• Difficulty in Gaining Visibility of Case Progress: This is a common characteristic of
case management as it is implemented today, although it is not an inherent
characteristic. While case workers may have a good understanding of how they are
progressing individual cases, it is often difficult to monitor progress when work has been
passed to colleagues within their own unit or to an external department. At a higher level,
managers usually have poor visibility of how long it takes to progress a case on average,
how much a case costs to process, and what the expected completion time is for a
particular case. It may also be difficult to obtain information on which cases are stalled
waiting for an external communication and which steps in a case are repeatedly causing
bottlenecks. The result is that processing of cases is often serialized, because to run
them in parallel, while more efficient, is just too difficult for many organizations to
manage.
• Strong Reporting Requirements: There is usually a significant requirement to report on
and analyze information derived from case handling, both at operational and
management levels, for example workload analysis of cases by stage, by individual and
by department and case performance versus target. Managers want gain insight into
operational performance and quickly identify exceptions.


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Case Management: Combining Knowledge with Process

• History: Every action performed, every decision taken and every piece of
correspondence received has to be tracked, not just for audit purposes, but also to
provide guidance for future similar cases. Case workers need access to this history
when making decisions, while auditors need the history to ensure policies are being
adhered to. The case history is the organization’s defense mechanism against any
allegations of failure to perform, particularly in cases which have high cost or personal
impact.
• Security: There is a requirement to provide fine-grained control over who has access to
particular information and functionality. In certain environments, these security
requirements assume particular significance e.g. policing, health care and child
protection.
• Isolated Pockets of Automation: This is a characteristic of case management as it is
generally implemented today, rather than an inherent characteristic. Case management
is usually only partly automated and there is disjoint between those pockets of
automation. Legacy systems automate slices of the processes, but the end-to-end
management of a case still relies too heavily on paper documentation, physical folders,
spreadsheets and email.
While this list of characteristics is not exhaustive, it captures the essential aspects of managing
cases. But what are the practical implications? Why should people care about the characteristics
of cases or the issues raised when trying to automate them?

Box: When Case Management Goes Wrong: 44 bereavement contacts with government
A 2005 UK Cabinet Office Report presented an example of what one typical family had to go
through following a bereavement. Unfortunately, a member of the family died in a road traffic
accident in September 2004. Following the accident the family had a total of 44 contacts with
government over 180 days trying to make the necessary arrangements.
Upon his death the individual and his widow were in receipt of a retirement pension, disability
living allowance, council tax benefit and housing benefit. The majority of the 44 contacts
concerned amending these benefits and nearly half involved the family having to contact
government regarding the same issue rather than government contacting them.
The family encountered many examples of a disjointed public service including the widow
receiving unexplained payments and two separate letters on the same day providing conflicting
information about entitlements and the family having to contact the local authority multiple times
regarding the life insurance payment before it was taken into account for housing benefit
purposes. After 180 days, the Passport Agency still had not contacted the family to collect the
passport and issues around housing benefit had not been resolved."
See http://www.hm-treasury.gov.uk/media/4/F/pbr06_varney_review.pdf

Why is Case Management important?
Case Management is important because knowledge workers are important. Case Management
is the most common approach to supporting knowledge workers with technology, but it is not
done well. First, we’ll discuss just why knowledge workers are so important.
Tom Davenport has defined knowledge workers as “people whose primary job is to do something
with knowledge: to create it, distribute it, apply it.”iii
Knowledge workers think for a living. They solve problems, they understand and meet
the needs of customers, they make decisions, and they collaborate and communicate
with other people in the course of doing their work.iv


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BPTrends ▪ July 2009

Case Management: Combining Knowledge with Process

In the late 1950s and 1960s the economist Fritz Malchup first tried to formalize the size of the
knowledge sector of the economy, suggesting it was growing two times faster than other sectorsv,
and management author Peter Drucker highlighted the growing importance of knowledge workers
and their productivity.vi More recently, research in the US, Canada and the UK suggests that
between 25% and 40% of the workforce can be classified as knowledge workers, and that this
proportion will increasevii.
Knowledge workers are important not just because they make up a growing proportion of the
workforce, but also because of their disproportionate impact on the companies and economies
they work in.
Even if they’re not a majority of all workers, they have the most influence on their
economies. They are paid the most, they add the most economic value and they are the
greatest determinant of the worth of their companies. Companies with a high proportion of
knowledge workers – let’s call them knowledge intensive – are the fastest growing and
most successful in the United States and other leading economies, and have generated
most of these economies’ growth in the past couple of decades.viii
Knowledge workers tend to be closely aligned with the organization’s growth prospects.
Knowledge workers in management roles come up with new strategies. Knowledge
workers in R&D and engineering create new products. Knowledge workers in marketing
package up products and services in ways that appeal to customers. Without knowledge
workers there would be no new products and services, and no growth.ix
Over the past hundred years the automation of work focused first on automating manufacturing,
then automating clerical work with the introduction of computers at the second half of the
twentieth century, through to automating knowledge-centric work today. For much of the past
four decades computer automation was directed at areas that were clearly defined and fairly
predictable at ”design-time”, mainly operational and administrative processes. Examples include
bank automation, airline booking automation and manufacturing production automation. These
kinds of processes could be complex, but the complexities could be analyzed, anticipated and
accommodated at the design phase. When we went to execute these processes, the ”system”
dictated most of the sequence of events to the human participants, based on logic embedded in
software. This kind of automation has meant that old-fashioned clerical roles are largely
disappearing. However, as these roles have reduced, there has been an increase in roles that
demand greater skills and knowledge. But despite the growth in the number of knowledge
workers and their importance to organizational success, there has been limited effort made to
improve knowledge centric processes:
Process improvement has mostly been for other workers: transactional workers,
manufacturing workers, people in call centers. All the serious approaches to improving
work have largely escaped knowledge work.x
A recent report by McKinsey reinforces this message
Companies have been automating or offshoring an increasing proportion of their production
and manufacturing (transformational) activities and their clerical or simple rules-based
(transactional) activities. As a result, a growing proportion of the labor force in developed
economies engages primarily in work that involves negotiations and conversations,
knowledge, judgment and ad hoc collaboration – tacit interactions, as we call them. By
2015 we expect employment in jobs primarily involving such interactions to account for
about 44 per cent of total US employment, up from 40 percent today. Europe and Japan
will experience similar changes in the composition of their workforces. The application of
technology has reduced differences among the productivity of transformational and
transactional employees, but huge inconsistencies persist in the productivity of high-value
tacit ones. [our italics]”xi
So, knowledge workers are the most important and fastest growing section of the workforce, but
the processes they use in their work are not well supported by technology; and generally they
haven’t been the focus of systematic process improvement initiatives.


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Case Management: Combining Knowledge with Process


Box: Tom Davenport on Managing Knowledge Workers
• Knowledge workers differ from other kinds of workers in their autonomy, motivations
and attitudes.
• Knowledge work tends to be unstructured. Specifying a detailed flow of work is
sometimes possible, but is probably not the best way to improve a knowledge work
process.
• Knowledge work often needs to be observed in some detail and at some length before it
can be truly understood.
• Knowledge workers are usually intelligent, so be careful about assuming that a
particular work task is unnecessary or that a work process can be improved upon
easily.
• Commitment matters to knowledge work. Don’t do anything to damage the knowledge
worker’s commitment to the job and the organization.

From “Thinking for a Living”, Tom Davenport

The Importance of Combining Process and Knowledge
It is self-evident that there should be good linkage between knowledge-centric processes and the
underlying knowledge needed to carry out those processes.xii However, process and knowledge
are generally not well integrated. In a 2005 article, L.Russell Records of CSC Consulting
discussed the parallel evolution of business process reengineering and Knowledge Management,
highlighting the lack of integration between the two:
There was (and still is) a general lack of understanding of how valuable the fusion of
processes and knowledge can be. The thought of actually taking the distilled knowledge
and making it easily available to people executing the process was somehow overlooked.
Employees would only stop to access the available knowledge base when the process
execution came to a screeching halt due to an inability on the part of the employee to
continue. Many times this would involve looking up information in an offline source like a
procedures handbook or calling a friend who might know the answerxiii
It’s worth providing a little historical background to this issue. Paul Harmon, editor of BPTrends,
described in a 2006 article how approaches from cognitive psychology and computer science
were used in the 1980s to capture and embed knowledge in software systems (known as ”expert
systems”)xiv. According to Harmon:
Ultimately expert systems have not proven very viable. It turns out that human expertise –
if it’s worthy of the name – needs to be constantly maintained. Human experts attend
conferences, read books and research papers, and constantly interact with peers while
trying to solve hard problems. All this leads to their reformulating their knowledge. It turns
out that it is expensive to capture human knowledge from an expert system, but it is much
more expensive to maintain that knowledge.
The next major attempt to focus on the use of knowledge in work was the Knowledge
Management movement, which gained momentum in the late 1990s. Knowledge Management
aimed to capture knowledge effectively, categorize it and then make that knowledge available
across an organization.
For the most part, it wasn’t particularly successful, because we didn’t look closely at how
knowledge workers did their work…. Most organizations simply created one big repository
for all knowledge and all workers. The only way to get people to use knowledge on the job
is to understand how they do their jobs and then figure out some way to inject knowledge
into the course of their day-to-day work, not make it a separate thing you have to consult


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Case Management: Combining Knowledge with Process

when you need knowledge. … The best way is to use technology to bake the knowledge
into the job.xv
This inability to access the right information at the point in a process when it is needed is a
problem:
Process execution normally stops when someone has to retrieve knowledge that has not
been provisioned for them to use. When this occurs in a customer-facing process, the cost
to execute the process skyrockets.xvi
While it seems obvious that integrating knowledge at the correct points in a process is a good
idea, what has this got to do with Case Management? Singularity believes that an effective Case
Management solution based on Business Process Management technology provides the best
mechanism for supporting the appropriate creation, dissemination and retrieval of knowledge for
knowledge workers within a process. The goal is to provide the information the worker needs at
the point in a process when he needs it, rather than force him to go searching for it when he hits a
problem. We also believe the supporting technology should help capture useful, shareable
knowledge from workers so it can be distributed to others doing the same kind of work. L.
Russell Records states that the goal
“…is to diligently and selectively move the knowledge into the IT infrastructure so that it can
be used to improve the execution of key business processes. xvii
We would emphasize the word ”selectively” here. It should not be a goal, stated or implicit, to try
to move all knowledge out of workers heads and into the IT infrastructure. As Paul Harmon
pointed out, knowledge is constantly being created, knowledge workers are constantly learning,
so only certain elements of the knowledge relevant to a particular type of work can be transferred
to automated systems. But we should provide tools that let the knowledge worker capture new
insights and information so that it can be reused by themselves and their colleagues at
appropriate steps in a process, and that gather knowledge about how processes are performed
for analysis and ongoing improvement of knowledge processes.
The Challenges of Automating Case Management
The characteristics of Case Management we outlined earlier indicate where the challenges lie
when trying to more fully automate this style of work. As with the automation of any business
processes, the technology has to support “exception handling, collaboration, decision making,
unstructured information, negotiations and paper flows”xviii. But the fundamental challenge in
automating case management is using the technology to support the unpredictable ways cases
progress and people work in practice. Traditional automation assumes that a sequence or
pattern can be determined in advance by careful initial analysis and catered for by good design.
More formally, it assumes that the logical flows can be understood a priori. As noted by van der
Aalst et alxix, in a traditional approach the designer has to specify what is permitted. Any routing
that is not specified at design time will not be supported by the system at runtime. However,
when seeking to automate cases, there is no predetermined sequence, and new tasks and
processes can be added at any point during the life cycle of the case as the need for them arises.
The emphasis must be on supporting the ad hoc nature of cases. As Lucy Suchman puts it
“The trick …. is to introduce bits of automation that will fit in to the work and do useful
things, and then make it possible for people to work with those bits of automation
embedded in the systems while leaving them the discretionary space to exercise the kind
of judgment they need to exercise to really get the work done”xx

The challenges specific to automating Case Management include:
• Striking a balance between Practice and Procedure:
Almost any job today has both clearly defined, predictable elements and less well
defined, more ambiguous aspects where workers exercise their judgment. Different
types of job, and the activities within a particular job, can be thought of as a spectrum


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running from ”well defined procedure” to loosely defined ”discretionary practice”.
Someone working in a call center generally doesn’t exercise great discretion in how they
carry out their job, while a senior investment analyst probably does.

Source: adapted from Derek Miersxxi and Paul Harmonxxii
There is a danger of aiming to fully proceduralize processes when reengineering
knowledge work, ignoring the ”Practice” side of the spectrum. However, this is counter
productive, because when a case occurs that doesn’t match the rules prescribed in the
procedure, workers are either brought to a halt or forced to create an unofficial
workaround.xxiii A careful balance must be maintained between prescribing defined
procedures for fully understood and repeatable aspects of work, while respecting the
parts of work that should be left to the discretion of knowledge workers.
Every effort to change how work is done needs a dose of both process – the
design for how work is to be done – and practice, an understanding of how
individual workers respond to the real world of work and accomplish their
assigned tasks.xxiv
It should be a goal that as particular workers become more experienced, they will be able
to formalized and standardize aspects of what they do, and these standardized
procedures can then be made available for use by colleagues.xxv
• Capturing Implicit Rules and Tacit Knowledge: This challenge is related to the point
made about Practice versus Procedure. Many case management processes will never
have been previously automated. They rely on paper forms and tacit and implicit rules
governing how cases should be managed in addition to documented and explicit policies
and procedures. Examples of implicit rules will include how staff cope with particular
exceptions, how they make decisions at particular stages of a case and how they deal
with unstructured information. The challenge here is to discover these implicit rules and
tacit knowledge and, where appropriate, try to support their automation, while leaving
room for those steps and decisions that should continue to depend on individual
discretion.
• Formalizing Experience – Supporting Learning: A good Case Management solution
should help an organization learn from previous cases. This learning could be exhibited
in the definition of new processes, new procedures, better online help etc., where lessons
learned by knowledge workers during a previous case were quickly applied to process
definitions to improve them. We use the phrase ”formalizing experience” to describe this
process of changing a practice into an automated step where appropriate, or supporting
some other action that will assist in the processing of future cases.
There is a related area of research, called Case Based Reasoning (CBR), which has
some obvious applicability to Case Management. Case Based Reasoning is the process
of solving new problems based on the solution of similar past problems: it’s based on two


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tenets, “similar problems have similar solutions. Consequently, solutions for similar prior
problems are a useful starting point for new problem-solving” and “the types of problems
an agent encounters tend to recur. Consequently, future problems are likely to be similar
to current problems”xxvi. CBR consists of four steps – look at a given case or problem and
try to think of a previous case or cases it might match; consider how the solution to the
previous case could be applied to the current case; test the solution on the existing case
and revise it if necessary; then record the new case, and the solution that eventually
worked, for future reference.
• Supporting Ad Hoc Change: It is not possible to fully analyze and define at design time
how a case will actually unfold at ”runtime”. While the overall pattern of a typical case
may be known, any case management system must allow for entirely new and
unpredictable process paths being required at execution time. This is due to the nature of
cases, where a range of outcomes may arise at each stage in the case, unpredictable at
design time, and these outcomes then determine the next stage or stages. Also because
cases are long-running, change may be introduced into the policies governing how cases
are handled while previous cases are being processed. For example, mid way through
the execution of an application for social welfare benefits, an entirely new set of steps
may be initiated to comply with new procedural guidelines, or to cope with an unplanned
external event such as the completion of a related case.
• Involving Participants in the Design of Knowledge Processes: the challenge here is
to let knowledge workers influence the design of those processes they participate in,
helping them make changes to processes or innovating new ones. Any solution needs to
support fast, easy change initiated by a worker.
• Supporting Collaboration : Collaboration is a key requirement, but it is not simply a
matter of enabling instant messaging or document sharing. Case workers need to share
everything related to a case, including history, discussions, correspondence and previous
decisions. The collaboration support for case management must ensure that the correct
information is made available to team members at the correct time, without losing the
context or current state of progress of the case. This requires a ”smart” system that
knows who needs what when. Conversely, it is important that irrelevant information is not
provided at the wrong time, and that confidential information is not made available to
inappropriate recipients.
• Supporting Decisions: Case workers are the key decision makers in determining how a
case will progress, supported where appropriate by automated rules. Automation of
cases must recognize that control will continue to reside with human case participants,
rather than seeking to encapsulate everything in an increasingly complex rule-base.
• Effectively Coordinating Participants: related to the point above, effective case
management requires that work is routed to participants at the appropriate time and in the
appropriate sequence, given the history of the case to date. This coordination requires
sophisticated workflow routing, synchronization of process flows at various points,
ensuring overall milestones are monitored and met, and ensuring that delays are
identified and exceptions raised where necessary.
• Managing Complexity: Information and data has to be organized and presented to all
case workers in a useful way so they do not become overwhelmed or confused by the
various pieces of documentation, records and notes related to a case. The interface used
by case workers to interact with automating systems is a key determinant of the success
of any automation.
• Managing Artifacts: Beyond the presentation of case information to the user, there is a
need to effectively store, manage and retrieve information related to a case. Case history
and associated records may need to be retained for specific periods, as a result of
legislation or organizational policy. Content may be structured or unstructured, and may
reside on multiple supporting systems such as databases, content management systems
and electronic record management systems. Any case management solution must
manage this content efficiently and effectively.


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