Case Management and BPM

Case Management and BPM
Most business functions combine some amount of structured processes with
unstructured, ad hoc activities. This white paper examines how concepts of business
process management (BPM) and adaptive case management (ACM) can effectively be
applied together in order to manage a wide variety of business process types.

The Nature of Work: Exceptions are the New Norm
A key trend in business is the increased focus on knowledge worker productivity. In
part because more routine work is becoming completely automated. Keith Swenson, in
his book on adaptive case management, “Mastering the Unpredictable”, defines
routine versus knowledge work:

Routine work can be analyzed and a common pattern derived. This is not to say
that routine work is done mechanically, exactly the same way every time, but
rather that there is enough similarity in each instance of it that there is a benefit
in identifying a specific, detailed pattern for the work. Because routine work is so
repeatable, it can be automated by traditional process automation means.

Knowledge work is not routine – it does not have the level of repeatability found
in routine work. The detailed differences from case to case overwhelm the
similarity of different cases: it is not that similarities between cases do not exist,
but rather that the differences are greater than the similarities. When it comes to
work automation, any advantage gained from similarities is overwhelmed by the
additional costs of having to accommodate the differences.

Routine work, as his definition states, is about work that is performed the same way
every time. You can analyze it ahead of time, work out the pattern – or what we would
call a process model in business process management (BPM) terms – then execute it
the same way every time. The key thing here is that executing routine work the same
way every time is a good thing: we want it to be standardized and efficient, and there’s
not much room for creativity in these processes. This covers fully-automated straight-
through processing, but also transaction processing work that involved people in the
steps, for example, keying transactions from instructions on a paper document. In

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order to standardize and automate routine work, it takes some amount of analysis and
implementation up front, but the high volume of repeatable processes makes that
effort pay off.

Knowledge work, on the other hand, doesn’t have the same level of predictability as
the routine work; instead, the knowledge worker needs to be able to decide what
action to take next on a particular piece of work, and when to send it on to someone
else. Since the processes don’t happen the same way each time, it’s more difficult to
manage them using standard structured BPM methods as with routine work. If you
had to map out every possible path that could be taken in this sort of situation, it
would take forever to get something implemented, and it would never be complete. In
other words, it would be too expensive to even try to do that sort of modeling and
implementation for a process that is truly knowledge work. Furthermore, not only is it
not possible to remove all of the runtime variation in knowledge work, it may be that
variation – and the ability to manage it – that brings value to the process.

Deloitte Development, in a recent white paper entitled “Social software for business
performance”, highlighted this shift from routine to knowledge work:

“Increasingly, employees encounter non-routine issues which break the
standard processes. These “exceptions” impede operating processes and drag
down business performance across all parts of the organization... The current
technologies support standard business processes, but fail to support the
dynamic informal communications needed for resolving exceptions.”

Their conclusion: exceptions are not exceptional – they are the norm.

BPMS in a Dynamic Environment
Most modern BPM systems (BPMS) have their origins in the management of structured
processes, and excel at modeling, automating, executing, measuring and optimizing
business processes. Historically, the focus was on standardizing and automating high-
volume, repeatable processes: the business equivalent of a factory assembly line. The
only agility in these processes was not in the process topology, but in the rules that
governed the flow through the a priori model.

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An example of a high-volume, repeatable process is that of the data entry portion of
processing an insurance application: an application form is received on paper from an
external customer, and the information on the form must be keyed in from the form
before further processing. There are several steps involved – scanning the documents,
verifying the quality of the scanned image, entering the data, validating the data entry
– and workers performing in the tasks in this process have little room for creativity:
they are required to perform exactly those steps in exactly that order. The goal of the
process is to complete the steps as efficiently and accurately as possible.

For repeatable processes, a significant benefit comes from optimizing process
performance, in part by modeling the process in advance in order to make it explicit to
both business and IT: everyone sees the process model and understands what steps
are going to be done in what order. That also provides a basis for monitoring the
process, examining how many instances are in each step, or where a particular
instance is relative to the process model at a point in time. The model defines
everything: what you model is what you execute, but requires complete knowledge of
every step in the process in order to implement.

This method of BPM works when the number of repeatable process instances justifies
the analysis and implementation efforts, such as automated processes or those
governed by strict procedural rules. However, many processes don’t fit well with a
structured process model: there is too much variability, and workers must either use
the defined process even though it is not optimal, or perform workarounds outside the
BPMS.

Traditional BPMS have been applied with excellent results to routine work, but it has
been more challenging to adapt these systems to handle knowledge work, where there
are dynamic processes, content and rules. This typically results in the requirement for
an undefined “hold” step where the process participant puts the item on hold while
they send email or make phone calls in order to resolve the issue at hand. In other
words, they step out of the audited and controlled BPM environment in order to do
what is necessary in order to achieve the goals of the process.

Many BPMS tools are adapting to more effectively handle the unique challenges of
knowledge work: more dynamic process definitions, better use of rules and external

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events, and inclusion of process-related content. And since many processes include
aspects of both structured and unstructured processes, many of the systems are
allowing these to be combined in a single process, either where a structured process
spawns a collaborative case for exception handling, or a dynamic case invokes
structured process fragments for standard procedures.

In our insurance application example discussed earlier, an application form that could
not be processed due to missing information is forwarded to an exception task where a
worker could decide what actions to take in order to complete the process, such as
contacting the customer to request the missing information. The presence of a less
structured task for exception handling doesn’t turn the entire process into an
unstructured or dynamic process: it just allows for a single point of unstructured work
in the context of a structured process. The possible paths through the exception
handling tasks are not modeled in advance, since they are relatively unpredictable.

Adaptive Case Management
The deficiencies of conventional BPMS’ in managing dynamic and unstructured
processes led to the rise of a new class of systems, called adaptive case management
(ACM) or dynamic BPM. Focused on supporting knowledge workers rather than
automation and efficiency, ACM includes a variety of functionality for problem solving
rather than transaction processing:

 The work is centered on a specific situation, or case, and a desired outcome for
that case. A case folder provides a persistent container for all tasks, rules,
content artifacts and history related to the case resolution.
 There may be little or no predefined process flow, with the worker defining the
flow as the case progresses.
 The worker may add new tasks at any time during case, either previously-
defined (including structured process snippets) or completely ad hoc.
 Business rules may constrain the selection of specific tasks, or trigger other
tasks and processes based on the user selection of tasks within a case.
 External events may impact the course of a case, either through automated
processing of the events, or user reaction to the events.

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Human-focused and content-rich, the goal of ACM is to assist, not replace, human
work. There are many business situations where we just don’t know the exact steps
that need to be taken in order to complete an assignment: we need to get started, then
use information that comes up during the process in order to determine which steps
to take next. Peter Drucker, the well-known management consultant, coined the term
“management by objectives” to describe how these processes – and the people who
participate in them – need to work: you set the goals, and let the person figure out the
best way to do things in order to achieve that goal based on their skills and
experience.

Case management systems must combine aspects of BPMS, enterprise content
management (ECM), business rules and collaboration in order to effectively support
knowledge workers, and maintain a solid history of the case in order to allow for
auditing and also to provide a reference for workers added partway through the case
timeline.

For an example of case management, consider an insurance claims process. Unlike
the insurance application process discussed earlier, which has a fairly structured
process with a few points of unstructured exception handling, claims processing is
primarily a dynamic process where the claims worker decides what tasks to perform,
and in what order. The claims worker may request information from the customer or
other involved parties based on their assessment of the claim, then wait for that
information to arrive in order to build up a complete, auditable claim file that supports
their final decision. The goal of the process is to resolve the claim, not to perform
specific tasks. However, even this dynamic, unstructured case management scenario
makes use of structured process fragments in order to complete some tasks: the
original claim form and other supporting documents, if they arrive via paper or fax,
will go through a structured data entry process before being seen by the claims
worker, as will other structured tasks such as processing payments once the claim is
resolved. However, the claims worker is unlikely to be performing those structured
tasks, but works purely within the adaptive case management environment.

Proponents of ACM compare their offerings with a specific definition of BPM that
focuses on structured processes, although this is a somewhat unfair comparison: they

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are actually comparing conventional BPMS tools based on older workflow and
application integration approaches with a dynamic planning approach. There is
nothing inherent in the definition of BPM – either as a management practice or the
tools used to assist it – that prevents BPMS tools from including ACM functionality.
Ultimately, both BPM and ACM are about managing business processes.

A Spectrum of Capabilities
Routine work and knowledge work are very different in terms of the degree of structure
and a priori knowledge, as well as the skills and level of responsibility of the people
who actually do the work. In reality, however, few business processes are purely
structured or purely dynamic: instead, we see a spectrum of functional requirements
between these two endpoints, and a spectrum of capabilities required to assist users
in managing these activities.

On the structured end of the spectrum are repeatable processes that are mandated by
regulations, part of a strict compliance process, or mostly automated. At the adaptive
end are processes that are unpredictable, or for which there is so much variation that
there is no benefit in modeling all possible permutations; instead, the knowledge
worker must select operations based on external events and case content. The goal
and focus at either end of the spectrum are different, too: structured processes are
typically focused on transactions with the goal of maximizing efficiency, whereas
adaptive processes are focused on knowledge with the goal of problem/case resolution.

The structured processes are clearly the target of conventional BPM systems, whereas
the adaptive processes are better handled by the emerging class of ACM systems.
However, the reality of business is rarely that simple: between these two extremes, we
see scenarios such as structured processes that require case management for
exception handling, and ad hoc processes that require some structured process
segments if the knowledge worker includes a task that is governed by specific rules.
The earlier examples, of insurance applications and insurance claims handling,
showed how a seemingly structured process actually has unstructured steps, and a
seemingly dynamic case management situation may include structured subprocesses.

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Structured Structured with Adaptive with Adaptive
•e.g., regulatory ad hoc structured •e.g., investigations
process exceptions snippets
•e.g., financial back- •e.g., insurance
office transactions claims

Through the course of their lifecycles, most cases will be handled by a variety of
different kinds of workers, some of whose work is very structured, and others whose
work is more unstructured, even ad hoc. In order to achieve efficient, consistent case
management, organizations need to support the entire gamut of “caseworkers” –
whether they are called that or not – and the various kinds of work they do to process
and resolve a case. And they need to do this in a way that doesn’t involve awkward
hand-offs that risk losing key pieces of context and case information in the transition.

Process may also migrate along this spectrum over time, once some analysis can be
performed on running instances of the processes. Applying process discovery and
analysis to ad hoc processes may detect patterns that allow some portions of the
process to be standardized into structured processes. Alternatively, moving from more
to less structured, the analysis of a structured process may show such a high degree
of exceptions and workarounds that portions of the process are converted to a more
dynamic style.

Summary
Recent discussions that position BPM and ACM as competitive approaches or
technologies don’t account for the complexity of real-life processes, where many
processes include aspects of both routine and knowledge work. It’s critical to position

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an organization’s business processes along that spectrum to gain an understanding of
what degree of structure and flexibility are required, and thereby be able to select the
best approaches for managing those processes.

Biography
Sandy Kemsley is an independent analyst, application architect and blogger,
specializing in business process management and Enterprise 2.0. During her career of
more than 20 years, she has started and run successful product and service
companies, including a desktop workflow and document management product
company and a 40-person services firm implementing BPM and e-commerce solutions,
and held the position of BPM evangelist for a major BPM vendor.

Currently, she practices as a BPM industry analyst and architect, performing
engagements for end-user organizations and BPM vendors. She writes the popular
“Column 2” BPM blog at www.column2.com, is a contributing author on other
business and social media-related blogs, and is a featured speaker on BPM and its
impact on business.

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Case Management and BPM

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