biology as a model for enterprise systems

8/9/2019 Biology as a model for Enterprise Systems

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HEAD BIOTECH May 2010 Oslo, Norway. 1

Biology as a model

for Enterprise

Systems


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Abstract

The umbrella term for integrating information systems into any form of organization is

usually referred to as enterprise systems. To be defined as an enterprise system the packagedsoftware application must actively take part in the execution of business processes. The

discipline has become an important issue to large businesses success, or not especially in the

last decade. Chief Information Officer is the person in an organization that should be

responsible for the implementation of enterprise systems.

The main idea behind enterprise systems is to assemble business processes within an

organization and add value to them. Such business-oriented software applications can be

automated billing systems, online payment and online shopping processes. The variety of

business-oriented tools is many, but they all try to target processes that gives value to the

organization. The technical term to such services in modern enterprise systems is Software

Oriented Architectures (SOAs). The artificial intelligence that orchestrates the services

within a system is referred to as Event Driven Architectures (EDA).

The ultimate goal to enterprise systems is to create a self sustained system that can make

decisions superfluous to human resources. Enterprise systems create competitive advantage in

two ways. First, the system increases value to the firm by sharing information within the

organization faster than without the system. This increases the quality of decision making

processes. Second, by automate low level managerial levels it frees resources within the

organization to do strategic analysis and to add wisdom to the companys activities. One

phrase that is well known to describe the enterprise systems role is The Digital Nervous

System.

Almost all active cutting edge research in the field tries to better mimic solutions in the

biologic neural system to overcome the challenges enterprise systems meet. This could be a

clue that the human organism can function as a representative model for how enterprise

systems should perform in the future.


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1. Introduction1.1The information Systems Strategy Triangle

To implement an enterprise system one must consider the corporate organizational structure

and strategies. It is necessary to weave the system into an already established environment, or

to take a totally new look at the organization with the intention of modifying it from scratch.

This scenario illustrates how devoted the corporate management should be when applying an

enterprise system into their corporation. In addition, the enterprise system itself is very costly.

One measuring of success is how well the planned enterprise system balances theInformation

System Strategy Triangle (Figure 1). The design of an enterprise system should be driven bythe organizations business objectives, strategies, and tactics and using the firms business

mission as a guiding star [1 Page 23].

Figure 1. The Information Systems Strategy Triangle [1 Page 23].

Organizations that choose to implement enterprise systems can be governments as well as free

enterprises. Actually, one of the truly big markets to software vendors lies in governments

that needs better control systems over towns and countries. Earlier this year, IBMs chairman

summarized the huge potential to enterprise systems into one sentence; A smarter planet

[2].

The ultimate measuring of success to enterprise systems is the competitive advantage it

creates in the free market. Thus, to consider the competitive landscape to a business when

designing its enterprise system should be important in contrast to governmental systems.

The position in an organization that is responsible for the system implementation to become a

success is the Chief Information Officer (CIO).


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1.2 Porters competitive advantages and processes

To better understand the task to the enterprise system it is important to have a clear picture of

a business value chain and businesses goals in the market. Many of Michael Porters books

are used in the literature as definitions of important terms and modules that should be

important to a business [3].

The definition of competitive advantage according to Porter is when an organization picks up

a resource, or a combination of resources, which results in outperformance of competitors. It

can be a result of getting access to natural resources, or to highly trained and skilled personnel

(Human resources) [4]. Human resources can produce added value to the organization. These

include better organizational processes, information, knowledge, etc; which can enable the

firm to conceive and implement strategies that improve its efficiency in the market [1 Pages

62-63]. Differences between a good, and a less good CIO (Human resource) can have

tremendous effect on a firms competitive strength. This since when implementing the

enterprise system the tolerance for gain, or loss, in the market is slim.

Much of the potential in the enterprise system lies in handling the companys processes in

new ways that can improve the organizations value chain [1 Pages 147-152] (Figure 2). The

concept of the value chain, introduced by Porter, divides a corporation into the discrete

processes that makes the landscape for the enterprise system to function. That is, the value

chain model represents the elemental building blocks that can create potential competitive

advantage if cleverly optimized (Figure 2). It does not only mean a

businesss internal value chain but also includes the businesses suppliers and customers;

Supply Chain Management (SCM) and Customer Relationship Management (CRM)

respectively (Figure 3) [5].

The so called hypercompetitive environmenta business faces in todays market is unique in

our time. To sustain competitive advantage in todays markets demands much more intense

strategic thinking compared to 20-30 years ago [1 Page 30]. Consequently, the new situation

increases the strain on management to constantly come up with new strategies. Hence, time

saved by automate processes in a business is one of the most valued benefits from

implementing enterprise systems. In this way strategic thinking to cope with the ever

intensive market situation receives more resources.

The second main competitive advantage enterprise systems give is fast processing of

information by itself. Fast exchange of information enables a corporation to make quicker


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and more meaningful responses to changes in the market [6].

The general satisfaction to customers and suppliers are also affected by enterprise systems.

Any business partner will always note the difference between two businesses in how well they

handle daily routines. Slow processes will most certainly annoy, because it will indirectly

affect business partners competitive advantage as well [7].

Figure 2. Porters value chain model. The bottom silos cultivate primary activities. The

supporting activities over the silos processes the actions needed to drive the chain

forward [Modified from 8].

To break down the enterprise system into more manageable pieces would be into Service

Building Blocks (SBB). Many Service Building Blocks that are loosely coupled are

orchestrated into a system that solves Porters business processes. This service driven approach

results in systems that are referred to as Service Oriented Architectures (SOAs). SOAs are

based on Event Driven Architectures (EDAs), which represent the intelligence within

SOAs. That is, EDAs makes the decisions to who service(s) to invoke, or not to invoke, in

the system [9] (More on this in 2.2 and 2.3 see also figure 5).


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Figure 3. The potential to an Enterprise system is to consider not only internal

processes, but also to include suppliers and customers (SCM and CRM respectively)

[Modified from 8].

A successful result of implementing an enterprise system are due to the total time-cost benefit

often referred to as eitherzero latency enterprise or the digital nervous system (See next

paragraph).

2 The vision of a digital nervous system

2.1 One main difference between neural systems and enterprise systems

As mentioned over, saved resources and fast decision making in a business, was the two main

competitive advantages enterprise systems added to a businesss value chain. It gives the

corporate the chance to respond earlier to lucrative opportunities in the market, while also

saving human resources.

Enterprise systems are at the moment issues for large organizations. A recent survey of

satisfaction levels relative to corporate sizes reports better satisfaction - the bigger the


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organization. Smaller organizations seemed to have problems taking benefit of the increased

information mobility within the company [10]. This survey indicates that the more

information that needed handling, the more advantage would be gained from implementing an

enterprise system. Interestingly, this trend can also be seen in evolutionary biology. The more

complex the organism the more need for a sophisticated evolved nervous system [11].

It is necessary to highlight one feature in the human neural system that cannot be found in

enterprise systems. The usage of different types of channeling hardware (Wirings) that

regulates channeling speeds itself, is not important to an enterprise systems success, yet.

On the whole, computer systems do still base their channeling on metal components that

provides approximately the same relative transportation speeds. In comparison, to biology

real-time speed is important since neural systems have evolved several sophisticated

designed channeling hardwares (E.g. different neuron cell designs).

The human organism can regulate channel speeds by at least four different mechanisms that

directly, or indirectly, involve the nervous system. They are neuron thickness, transmission

mechanisms between neurons, gas signaling and molecular diffusion signaling. Hence, to

channel data from point A, to point B, the human body uses at least four different hardware

types [11].

In contrast, the IT system must juggle with two channeling hardware types, the electric wire

and wireless signals. However, wireless equipment is foremost implemented to increase

comfort and practical issues, and not real time speed on the hardware itself [12]. A

disadvantage is a decrease in security due to easier invasion of the network.

This issue illustrates the difference in sophistication between the two systems, and thereby

the huge potential for future enterprise systems.

2.2 EDAs and SOAs have their analogues in the human nervous system

The human neural system has many different sized modules in its system that really is

crossroads to incoming dataflow. One such example is interneurons that can project

responses from the sensory system (E.g. the skin) into movements of the limbs (Via nerves to

muscles) (See figure 4). These interneurons are clustered centrally located in the spine [13].

This location is not a coincidence; it is well designed during the course of evolution.

When we are talking about integration of information we are essentially talking about system

architecture. Since, different types of information must be channeled to their respective


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engines in which they belong. This to add meaningful value to the business processes in the

value chain (See figure 5).

To the enterprise system Service Oriented Architecture (SOA) is a way of knotting relevant

informations together and put out a system of services as a response. A service in this

sense can be seen as a small application, or program code that provides a service to the

system. Same kind of system can actually be argued to exist in the human neural system, even

though their respective services differ. At the core of SOA we find Event Driven Architecture

(EDA) which is the intelligence that underlies the actions within a SOAs. EDA decides the

fate (Or bring life) to the services that are available to the system. Likewise in the touch-limb

movement example described over, the touch to the skin produces a service movement of

the limb. What brings this service to life is the intelligence in how nerve transmission is

coupled and how its data is interpreted.

It was probably this similarity of orchestration in biologic and computational systems that

came to Bill Gates mind, and his audience, during his declared vision of the The digital

neural system in the late 1990s [14]. Both systems also culminate in the same advantages to

the biologic organism and corporate business.

Figure 4. The service of moving a limb in response to a painful experience is understoodin the engine (Or in the interneurons) [Modified from 15].


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EDAs analogue in the human system brings us to the binary nature of neuron cells.

Dependent on the incoming data to a neuron cell (E.g. an interneuron) it will respond by

propagating the incoming signal further into the nervous system, or not. The cell fires to

send the signal further, or do not fire. If a cell fires it is usually denoted as a 1. If it does not

fire, it is denoted as a 0 [16]. This binary nature of the neural system is probably the

motivation behind Judith Dayhoffs phrase the digital neural system, phrased in her book

Neural NetworkArchitecture published in 1990 [14]. Thus, the fundamental logic between

neuron systems and EDA is illustrative. This is also widely accepted within the industry,

especially when it comes to cutting edge research within the field (See 2.4 Complex Event

Processing). As already mentioned, e.g. interneurons in biologic systems play key roles in

making decisions in response to incoming data [13]. Such functional places in the neural

system have their counterparts in the EDAs called event processors or engines (See also

figures 4 and 5). For the neural system to be able to make predictable decisions there must be

a set of rules that controls a neuron cells response to incoming data. To the neural system

these rules are set during evolution. The same can actually be said about EDA, since they also

evolve essentially in a free competitive environment, as biology has.

2.3 Event-driven architectures

As already mentioned, at the core of Service Oriented Architectures (SOAs) lies Event

Driven Architectures (EDAs).

For any intelligent system to respond it needs an event, and something that is constructed to

process the event into a service. The initial event, produced outside the system, must be an

expected event to the system. It must be a notable thing that is in the systems interest. The

filtering of notable and not-notable events is a key issue to enterprise systems. In addition to

the incoming information flow to the enterprise system a downstream flow of events adds to

the initial events (Figure 6). For the enterprise to make intelligent decisions it need not only to

process the initial events, but also to analyze the result from relating the events to each other

and its downstream consequences (Complex event processing See 2.4). Due to its many

challenges, EDA is divided into three phases (Or logical layers);Event generator,Event

channeling, andEvent processing (See below) [17].


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EVENT GENERATOR

First, an initial event needs to be generated. For the event to enter the system it needs two

requirements. First, the event must be detected by the system. Second, the event needs to be

absorbed properly. That is, the initial event-format needs to be transformed into the systems

format standard for faster information processing between services. The detection and

absorption of an event is achieved via so called agents. Its biologic counterpart would be the

receptor. Whether the initial events format is variations in temperature, touch, sounds or light

they are transformed via receptors into the systems standard format, which are electric

propagations down neuron cells.

EVENT CHANNEL

After the initial event is generated, received and transformed into the standard-format, some

type of hardware is needed to distribute the incoming data within the system. As mentioned in

2.1 over, the biologic system uses at least four different methods to regulate channeling speed

itself. Enterprise system does not seem to have found the need to exploit such real-time-speed

regulation in its wiring system. Wireless channeling is an option. E.g. Bluetooth is one but

such channeling is not important to increase the performance to the system itself when it

comes to real-time-speed, but rather to make its usage more practical due to great distances

etc [12].

EVENT PROCESSING

This is where the magic takes place within both types of systems. Event processing belongs

in the field ofcontrol theory, which ultimately finds ways to produce the intelligence in

systems. It is an interdisciplinary field that combines mathematics and engineering to handle

dynamical systems in both biology and electronic computational systems [18].

The integration of independent information types, to create non-independent responses givesa higher meaning to the system. Actually, this feature of producing something new and

meaningful from different parts, is essentially what qualifies to call something a system in

general [19].

Event processing is itself divided into three phases simple event, stream eventand complex

eventprocessing. Further, the service that results from event-processing takes us to the next

topic, Service Oriented Architectures, or SOAs.


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Figure 5. The basic principal of intelligence is similar in ES and humans. The number of

inputs to the engine can range from 1 and up.

2.4 Service Oriented Architectures (SOAs)

Event processing are places in the system architecture often referred to as engines.

These engines process either simple events, stream events or complex events to provide a

service to the system. All three levels of processing have their analogue in the human neural

system. It is best to divide both systems into two broad disciplines; none-conscious or

conscious services (Figure 6). That is, some services are meant to fulfill management

automatically (Autonomous) and other are meant to only enlighten the management for

further processing (Conscious). Of the three levels of processing the two first levels, simple

and stream event processing belongs to the none-conscious discipline and complex event

processing into the conscious discipline. However, in some cases both events can happen at

the same time. E.g. an incoming event in an enterprise system tires low in stock can trigger

two services; Order product ID and Notify personnel. Thus, two independent services

results, one to the non-conscious and one to the conscious part of the system. This can happen

in the biologic system as well. E.g. a person can respond in a non-conscious way to a strong

experience. At the same time, the total experience (Where, what and was) is processed in


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other parts of the system (Mainly in hypothalamus) for the episode to be recalled later to the

conscious mind if that person approaches the same type of situation again [11, 15]. Hence, the

stimuli (Or event generator) has been processed consciously and non-consciously.

3 Discussion

The functional framework that makes up an enterprise system is EDA and SOAs. SOAs

provides small services which can be reused, and are not that unique to the organization. In

contrast, EDAs is the intelligence within the system and must be unique to make it suite an

organization well. Up to this point, this text has illustrated that it is in the EDAs of theenterprise that have its most similar counterpart in biologic neural systems. As mentioned in

2.4 EDAs are based on three levels of event processing. These levels main responsibilities,

and their counterparts in the human neural system, are discussed below.

SIMPLE EVENT PROCESSING

It is most natural to think of simple event processing as a simple response(s) to a notable

event to the enterprise system. Its most fundamental way of adding value to the system is due

to lag time avoidance in the real-time work flow. It is where a business is most likely to put its

no-brainer problems, and have a low risk of becoming a bad investment.

This levels analogue in the human system would be basic autonomous decision making such

as reflexes. Such as simple responses that keeps the organism from dying and at the same time

releases the conscious brain from workloads. In addition, the event can be saved, and/or be

channeled into complex event processing at a later stage.

In conclusion, to implement simple event processing is a safe way to add value, and hence

competitive advantage, to any business. Main security issues should be prioritized first

(Dangerous situation that can damage the business forever).

STREAM EVENT PROCESSING

In stream event processing the delegation of information to the most meaningful places in the

system is key. To make each engine in the system to respond with a meaningful service

without errors, it is important to not make the decision process more complex than is needed.

Thus, to correctly control meaningful flow of information to the right engines in the system,will add value in two ways. First, it will gather meaningful information at the correct places


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within the system, enabling fast decision making at the semi managerial level. Second, it will

decrease the risk to make errors in each individual engine due to intelligent filtering of data.

Its analogue in the human system would be the well planned design behind the nervous

system which distributes information to the right places. This coupled to the rapid processing

of information optimizes the human body for multitask processing within the system. Hence,

it can also be seen as a prerequisite for accomplishing complex event processing (See the

following section).

In conclusion, to implement stream event processing is a semi-risk decision. However, it

depends on the size of the organization. It needs well planning for it to be optimized and to

add maximal gain to the value chain.

COMPLEX EVENT PROCESSING

Complex event processing is the most diffuse and hence challenging field to a system [20]. It

has probably the most to gain by using the human nervous system as a guide. I choose

to make two subdivisions of the word; complex event processing and too complex event

processing. However, it is hard to see an end to how complex a processing procedure can be.

Complex processing must consider spatial, temporal and causal relations between events

before it takes action in the form of a service. The basic point that should be considered is the

risk involved in making services. As a general rule, the more complex processing the more

uncertainty is the risk involved. Further, an action taken can also simply be to store reports of

complex events to be used in later analysis by the human management. To lower the risk in

the decision process they can add wisdom. Hence, too complex event processing should be

sent to the conscious part of the system before a final decision is made (Figure 6).

To push the limit to where to set probabilistic bounds in complex event processing (Where to

set the border between complex and too complex processing) new inventive methods are

constantly being developed. One area that is expected to give complex event processing a

push forward is within the field ofmachine learning and artificial intelligence. Many of these

systems are actually electronic simulations of biological neural networks [19]. E.g. IBM does

research with adaptive agents that can learn from experiences, to achieve so called enterprise

system optimization [21]. However, instead of optimizing each individual component they try

to optimize the interactions among systems components. IBMs vision is to increase

system robustness (Lowering decision risk), self configuration, and to develop self-repairing

systems that can further expand the enterprises responsibilities.2 years ago HP labs (Hewlett-Packard labs) presented a switching memristor[12]. It is


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develop to be used in nanoelectronic computing, logic memories, and neuromorphic. The

field ofneuromorphic is perhaps the next step to take enterprise systems up to the next level.

At a nano scale, neuromorphic should become capable of mimicing actual neuro-biological

architectures, identical to how they work in the nervous system.

In conclusion, it seems that the industry agrees on using biologic systems as a model to

optimize enterprise systems [7].

Analogue to complex event processing in the human neural system

Due to the above we have also moved the analogue situation to the more complex, and

centralized part of the brain (See figure 6 to the right). The best analogue to complex

processing in the human system would most probably be to the hypothalamus.

However, this brain part needs to cooperate with other parts of the brain to achieve its role.

One of hypothalamuses unique roles is the processing of complex events and to later combine

and store them as one single episode, or as one experience [15]. Such complex fragmented

episodes are stored in a way that makes recall of the episode loosely coupled to the whole

episode (Now as an episode service). Only one, or a few events that are identical fragments in

the episode (or even only similar), can trigger the total episode to be recalled in the conscious

mind. E.g. to see an apple stalk, can recall a huge amount of related data. The reason the data

is functionally related is because the brain (Working in synchrony with Hypothalamus) has

made its own business report about everything that is important to know about an apple

stalk. First, it will recall the vision of an apple, which again could remain the person that he,

or she, is allergic to apples. The horror of getting ill after eating an apple could have amplified

that important bit of information before other issues knotted to the piece of information (The

apple). A second service, which is not as important to the individual, could be that apples are

not as expensive as oranges are.

Amygdale is a section in the brain that is important to the way hypothalamus handles

incoming information as a response to emotional responses. What actually happens is that

events which triggers emotion in the brain increases the chance of that episode to find its

place into the brains database (Emotional learning) [1].

The essential emotion center in a corporate would almost certainly be the stake holders of the

business. If earnings go down, without good reason, they will stress the management whichagain will stress the remaining system to improve results. This concept is interesting because


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it reminds of how amygdale actually pushes the neural system to act in an intelligent manner.

In the future, the new development at IBM and Hewlett-Packard can be combined with a

continuous reward/punish system that can supervise their systems learning behavior directly

to corporate income. If the next generation of electronic systems can truly start to mimic a real

biologic neural system in function, to build modern SOAs on top of such event driven

architectures could potentially truly make huge business to be driven by not many biologic

heads with wisdom.

In conclusion, complex event processing is one of enterprise systems most challenging

bottlenecks. However many new and exciting research studies should prepare the industry for

the next level of enterprise systems. It should not be a surprise that almost all active research

in the field tries to better mimic the biologic neural system in how to best process large

amounts of information. To use the human organism as a representative model for how

enterprise systems should perform, could very well become a standard in the future.

Figure 6. When the processing becomes too complex the risk increases for doing errors. In

such cases the overview picture is sent to management for further analysis.


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Conclusion

The umbrella term for integrating IS into any form of organization is usually referred to as

enterprise systems. To be defined as an enterprise system the packaged software application

must actively take part in the execution of business processes. The discipline has become an

important issue to large businesses success or not, especially the last decade. CIO should be

the person in an organization that should be responsible for the implementation of enterprise

systems.

The main idea behind enterprise systems is to assemble business processes to an organization

and add value to them. Such business-oriented software applications can be automated billing

systems, online payment and online shopping processes. The variety of business-oriented

tools is many, but they all try to target processes that gives values to the organization. The

technical term to such services are usually referred to as Software Oriented Architectures

(SOAs). The artificial intelligence that activates the services within SOAs is referred to as

Event Driven Architectures (EDA).

The ultimate goal to enterprise systems is to create a self sustained system that can make

decisions superfluous to human resources. Enterprise systems create competitive advantage in

two ways. First, the system increases value to the firm by sharing information within the

organization faster than before. This increases the quality of decision making. Second, by

automate low level managerial levels it frees resources within the organization to do strategic

analysis.

One phrase that is well known to describe the enterprise systems role is The Digital Nervous

System. Almost all active cutting edge research in the field tries to better mimic the biologic

neural system to overcome the challenges enterprise systems meet in Event Driven

Architectures. This could be a clue that the human body can function as a representative

model for how enterprise systems should perform in the future.


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HEAD BIOTECH May 2010 Oslo Norway 17

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biology as a model for enterprise systems

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