A line of industry fights for survival — systemic strategy
development and implementation using the example of a lead
brokerage financial service provider
Paul FLACHSKAMPF, Klaus HENNING
Institute for Management Cybernetics (IfU) at RWTH Aachen University
Dennewartstr. 27, 52068 Aachen, Germany
Telephone: +49 241 80911 70
E-Mail: paul.flachskampf@ ifu.rwth-aachen.de
ABSTRACT
This paper examines systemic strategy development using the example of a lead
brokerage financial service provider. To do so, different elements of several systemic
and cybernetic induced theories are combined to a three step approach: 1) system
diagnosis to derive redesign actions, 2) identification of critical system variables, 3)
creation of a modular software prototype with the help of a control loop model. This
approach is induced by action research building on an interactive inquiry process that
balances problem solving and actions implemented in a collaborative context. Data-
driven collaborative analysis is implemented to better understand underlying causes
and to enable future predictions about organisations and processes. The results of the
approach application seem promising in two ways: 1) a real benefit for the lead
brokerage financial service provider was generated by the operationalisation of its
strategies, 2) the approach itself shows potential to be of general applicability to
successfully support business processes with IT.
1. INTRODUCTION
Initially, stock exchanges had a fixed function. Selected market participants met at
fixed times in fixed locations to trade standardised financial stocks in accordance with
firm rules (Gerke 2005, 216-230). But the last ten years have been a decade of radical
change and upheaval for the organised capital markets, sparked by vastly improved
communications technologies (Schmidt and Gramlich 2004).
In the past, the task of the lead brokerage financial service provider (LB-FSP) was to
undertake the role of intermediary between buyers and sellers of (financial) stocks. For
this purpose, the LB-FSP now administers an order book in which all buying and selling
orders for a specific stock are noted. Based on the value of an order in the book and the
existence of a reference market, the LB-FSP establishes the buying (asking) and selling
(bidding) prices for stocks and the corresponding quantity (volume), and displays this
information to the market. This specification of bidding and asking prices with a
corresponding volume of stocks will be referred to as a quote.
Vastly improved communications technologies, the management of organised capital
markets, the regulation and the handling of finance transactions (Baum 2004, 677-704),
as well as an increase in the automation of finance transactions, have all led to a change
in the role of the LB-FSP. As procedures in finance intermediation are essentially
remaining constant, the LB-FSPs now no longer act as mere facilitators of trade between
buyers and sellers, but now also act as buyers and sellers themselves. In this way they
provide additional liquidity to the market. At the same time, concerning buying and
selling orders, this ensures fast order execution, so that trade does not only come about
after an agreement is made. The LB-FSP carries out the order as soon as it is within the
quote that he displayed to the market. The LB-FSP role altered from pure facilitator to a
so-called market maker. For performing these functions, the LB-FSB generates revenue
through various order-flow or transaction-fee schemes. In addition to that, they generate
profit with the received inventory of stock, which can be traded as seen fit (Cataldo et
al. 2003, 10-13).
As a result of November 2007 change in the EU policy “Markets in Financial
Instruments directive” (MiFID), established stock exchanges like e.g. Frankfurt or
London turned out to be under increasing pressure from new off market trading
platforms such as Chi-X, Turquoise and Equiduct (FAZ 2008, 23). Due to sinking costs
for the buying and selling of stocks, first reactions to the new competition are already
noticeable. Established stock exchanges are losing more and more turnover, as investors
conduct their orders with automated, electronic trade or start using new off-market trade
platforms. Considering that order volume in the established stock markets is drastically
sinking, there is an important medium-term question for the LB-FSPs: that of the ability
and survivability of the markets’ current business models in the future.
Modern stock markets conform most closely to the theoretical model of the perfect
market (Wurm et al. 2007). In reality, it is apparent that this theoretical model stands in
stark contrast to many prominent real-world examples a recent one being the speculation
by the Société Générale (The Economist 2008). Despite technological advances, it is
evidently no longer possible to control the amount of complexity for market
participants. In this kind of situation, the technologies employed until recently have not
allowed the LB-FSP to react to fluctuation of the market through subtle regulation of the
quote. In addition to that, current technologies do not allow for market movement
consideration or the incorporation of gut feeling of the LB-FSPs, which is still a very
important factor for the actual placement of quotes.
Since the placement of quotes is clearly the only possibility for the LB-FSP to appear
visible in the market, this plays a key role in the search for suitable strategies for the
actual quoting process. On the one hand, this must proceed mainly on an automatic
level, in accordance with the new requirements. On the other hand however, it should
also offer the manual input possibility to allow incorporation of gut feeling. That way,
when correcting variables, situations can be influenced. This aspect is important in order
to be able to react suitably to the ever-changing demands of a market that continues to
increase in complexity. This article is thus concerned with answering the following
questions:
1.) From a systemic perspective, which strategies can contribute to ensuring the
survival of the LB-FSP?
2.) What is the necessary approach when introducing strategies tailored to fit the
specific requirements of the LB-FSPs?
3.) With regard to the developed strategies, how can an automated quote be created,
which if required is also open to the influence of manually implemented
actuating variables?
After a short description of the methodology and the approach implemented, a system
for the development and implementation of strategy, as well as the resulting solution
approaches for an automatic quotation, will be exemplarily described. If required, this
will remain open to influence from actuating variables. An example will be given in the
form of a LB-FSP. Lastly, a critical evaluation will be made.
2. METHODOLOGY AND APPROACH DESCRIPTION
The approach for systemic strategy development and implementation combines
different elements of several theories. It is induced by action research building on an
interactive inquiry process that balances problem solving and actions implemented in a
collaborative context. Data-driven collaborative analysis is implemented to better
understand underlying causes and to enable future predictions about organisations and
processes (Reason and Bradbury 2001). In a first step the OSTO System Model was
used to diagnose the company and to derive redesign actions. In a second step, relevant
system variables were obtained by conducting thirteen in-depth interviews with lead
brokers. The cybernetic relationships between those variables were analysed with the
Sensitivity Model of Vester (Vester 1980). Based on the results of the sensitivity
analysis, a modular software prototype was developed in a third step for simulations and
testing of the effects on the quoting process. See Figure | for a summary of the
methodology and approach chosen.
Paragraph 3 and 4 will explain how the different steps of the approach are interlinked
and why in the specific case at hand the particular method or theory was applied.
System layer:
OSTO System Model:
Diagnosis and redesign
approach to analyse situation
and develop strategic response
Variable layer:
Sensitivity Model by Vester:
Identification of relevant system
(2) variables through interviews
and determination of cybernetic
effect of the variables
ssaooid Buiajos wajqoid yoseasa, uly
Process layer:
Creation of a modular
software prototype and start
(3) BWW © silations and testing of
the effects on the quotation
process x /
Figure 1: Methodology and Approach Description
3. SYSTEMIC STRATEGY DEVELOPMENT
Enterprises today are socio-technical systems that constantly interact with an
increasingly complex environment. The St. Gallen Management Model, the Viable
System Model and the OSTO System Model are the relevant theoretical approaches that
exist for a systemic strategy development and implementation for such systems.
The St. Gallen Management Model (SGM) (Riiegg-Stiirm 2002), (Schwaninger 2001,
1209-1222), (Bleicher 1991), (Ulrich and Krieg 1972, 54) stresses the importance of
ethical and normative dimension of management. A process-oriented view of the firm is
of great relevance. Also, much emphasis is placed on the interpretative, meaning-based
dimension of management. Compared to the OSTO System Model, the SGM lacks
diagnosing capabilities, but is more detailed at the structural level.
The Viable Systems Model, or VSM is a model of the organisational structure of any
viable or autonomous system (Schwaninger 2004, 411-431), (Tiirke 2008), (Christopher
2007), (Beer 1985), (Beer 1972). A viable system is composed of five interacting
subsystems which may be mapped onto aspects of an organisational structure. In
addition to the subsystems that make up the first level of recursion, the environment is
represented in the model. The model is derived from the architecture of the brain and
nervous system. One conclusion from operation research is that, the VSM is more
technical than human centred.
The OSTO System Model (OSM) - a method to analyze, redesign, and monitor socio-
technical systems - has specifically been suggested and has been proven to be a very
promising approach (Hanna 1988), (Henning and Marks 1992), (Henning and Isenhardt
1992). OSTO stands for “open, socio-technical-economic system.” It builds on the
socio-technical system theory, which was considerably influenced by members of the
London Tavistock Institute of Human Relations. The OSM focuses on analyzing work
processes that are strongly interrelated. They are mainly the result of a combination of
technology and human communication on a higher level. The OSM understands systems
as “living systems” (open cybernetic systems). Such systems include humans with their
processes of work and life. Feedback processes stabilize and renew this open living
system. The system structure is characterized by different design elements that are
dependent on each other in many complex ways. The main elements are the technical,
social, and organizational subsystems: technology, people, and organization (Brandt et
al. 1999, 245-252). None of the three models mentioned has been applied before within
the context described in paragraph 1. The literature does not address if these approaches
could help the LB-FSPs facing a large economic downturn with strategy development.
For the case at hand the OSM was chosen. Compared to the other models, the OSM has
the advantage of great flexibility. Also the VSM and the SGM are much more complex
models compared to the OSM and therefore less easy to apply (Schwaninger 2001,
1209-1222) (Schwaninger 2001, 137-158) (Espejo et al. 1996) (Rapoport 1998).
The research was conducted at a lead brokerage financial service providing company,
at the stock exchange in Frankfurt Germany. According to the OSTO approach, in order
to derive an appropriate strategic response to the new forces that existed within the
relevant market environment (electronic order execution, alternative trading platforms,
etc.), it is necessary in a first step to perform a very detailed diagnosis of the company
(system) at hand. The seven steps of the diagnosis are described in detail in (Henning
and Marks 1992), (Rieckmann 1997). After the completed diagnosis, the five steps of
the redesign process have to be carried out. Within the process of the diagnosis, it
became quickly apparent that there are two main purposes why LB-FSP companies exist
today. The first is the demand from financial marketplaces (stock exchanges) for stock
orders to be carried out within the defined performance criteria. The second is the
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demand from financial investors (public, private, etc.) for the best price for their stock.
The problem with these two purposes was that in the past it was more important to
satisfy the needs of the Frankfurt financial marketplace, than to deliver the best price for
the investors.
By satisfying the needs of the Frankfurt marketplace, the company ensures the
number of stocks that they are responsible for. As investors had little choice in the past
between stock exchange places, it was not important for the LB-FSP to focus mainly on
their interest. As stated in the introduction, due to changes in the market environment,
the priority between these two purposes drifted in favour of the investors. The LB-FSPs
were, and still are, loosing order-flow. To summarise the above discussion, the
following can be diagnosed:
Diagnosis D1: Lead brokers did not focus on the investors’ interest.
Diagnosis D2: Worsening competitive situation for the LB-FSPs due to better
alternatives for investors and economic crisis.
The problem is that acting in the best interest for the investor is not always in the
interest of the LB-FSP. Giving the investors the best prices for their stock, reduces LB-
FSPs’ chances to make profits themselves. As the actual trade of stock is handled within
seconds, it is almost impossible for the management to control if the best quote is
always delivered to the investors. In addition to that, the lead brokers are paid their
bonus individually based on their profit making ability. They compete over a limited
amount of bonuses, reducing their willingness to share knowledge among each other.
Consequently, their ability to earn profits for the company varies. Therefore, they all
have a different quote making behaviour. Thus, it can be diagnosed:
Diagnosis D3: It is hard for management to control if the best quote is always
delivered to the investors.
Diagnosis D4: The bonus is paid individually based on profit making ability of
the lead broker.
Diagnosis D5: Lead brokers compete over a limited amount of bonuses.
Diagnosis D6: Lead brokers have no interest in sharing their knowledge among
each other.
Diagnosis D7: The ability to earn profit varies among the lead brokers.
Diagnosis D8: The quote making behaviour varies among the lead brokers.
The complete diagnosis and the interrelations of the findings are depicted in Figure 2.
D2: Worsening
D7: The ability to earn competitive situation for
profits varies among the f-- the LB-FSP due to better
lead brokers. alternatives for investors
and economic crisis.
D6: Lead brokers have no
interest in sharing their
D4: The bonus is paid
individually based on profit DB: The quote making
behaviour varies among
Reduced order-flow
making ability of the lead knowledge among each H
baker pe the lead brokers.
DS: Lead brokers compete D1: Lead brokers did not H
over a limited amount of focus on the investors’ --
bonuses. interest.
—— strong influence
wees > weak influence
Figure 2: Findings Diagnosis
As order-flow is dramatically reduced due to better alternatives for investors, the
existence of the LB-FSPs in Frankfurt is in danger. This was clear to the management.
Therefore, the management wanted to implement a new best price strategy. Their
bidding and asking prices (quote) should be at least as attractive to investors as the
quote of the competitors. The problem with this strategy is that making the quote as
attractive as possible to investors reduces directly the profit margin of the LB-FSP. Still,
the management believed that even under the new circumstances their best performing
lead brokers are able to earn profit for the company. To that end, their intention was to
encourage knowledge sharing among their brokers. Accordingly, a teambuilding process
was started and the bonus system was adapted to reward team oriented behaviour. The
team process should lead to profit making strategies based on explicit knowledge, which
can then be incorporated into an assistance decision support system for all lead brokers
to use. In summary, the management’s decision was to implement three system redesign
actions:
Redesign Action RA1: — Start teambuilding process with lead brokers.
Redesign Action RA2: Change the bonus system to encourage team oriented
behaviour and knowledge sharing.
Redesign Action RA3: — Ensure through an assistance decision support system that
the quote delivered is just as attractive to investors as the
competitors’ quote.
Figure 3 shows the interrelation of the diagnoses with the redesign actions.
D2: Worsening
D7: The ability to earn competitive situation for
profits varies among the the LB-FSP due to better [4
lead brokers, alternatives for investors
and economic crisis.
DA: The bonus is paid D6: Lead brokers have no .
indvaualy based on promt (ZAZA interest in sharing ter 8: Te gists raking Teduoed order
making ability of the lead knowledge among each Re leao bate 0
broker. other. CAE eS: i
DS: Lead brokers compete D1: Lead brokers did not H
over aimed amount of | focus onthe investors :
bonuses interest
[RAI [RAZ
sonar TA) racdeaty ma ZZ] oveaorn wit oer RA
eee > weak influence
Figure 3: Redesign Actions
These are the diagnosis findings and proposed redesign actions that were the outcome
of a systemic strategy development process. Reflecting on the results of the first step, it
can be concluded that in this case, the application of the OSTO System Model proved to
be helpful. The diagnosis and the resulting redesign action were developed within three
workshop days over a period of two month. In the first workshop day the diagnosis of
the company was conducted. In the second workshop day the redesign actions were
developed.
These two workshops were done with top management participants only. In a third
workshop day the developed results were presented and discussed with the whole lead
brokerage team resulting in commitment for a stepwise implementation of the redesign
actions. The following paragraph will deal with the implementation of the proposed
strategies (steps 2/3 Figure 1).
4. Strategy implementation at a LB-FSP (step 2 and 3)
Having decided upon what actions need to be taken to ensure the survival of the
company, the next step was to implement the redesign actions. RAI and RA2 were
implemented using state of the art methods and already existing models. For the
implementation of RA3 we first have to look closer at the present conciliations of the
quote process itself: First the lead broker is subject to certain regulations and policies
which define his job. For instance she/he may not use special knowledge for his/hers
own advantage and profit. In a second step the lead broker verifies constantly the order
book. In a third step, based upon the order book status a quote (bid and ask price of a
stock) is displayed to the market. At the same time the quotation itself is also subject to
certain regulations and policies set by the stock exchange where the stock is traded.
How the quote process works is depicted in Figure 4 in a control loop model.
Regulations
from Stock
Exchange
Laws and
Provisions Verifies Status Quote
Lead Broker — [74] Quotation ry Market orders
XETRA Data
Corporate Information
Figure 4: Quotation Process Control Loop Model
This model is the basis form which the implementation of RA3 (ensure through an
assistance decision support system that the quote delivered is just as attractive to
investors as the competitors’ quote) started. How the actual quote is set by the lead
broker in each and every case depends upon a number of different interrelating variables
which have to be analysed at first. If the assisting decision support system would be
built on a too narrow rule description and logic, it would reduce the possibility of
implementing the lead brokers’ tacit knowledge on stock behaviour. However if the
system would be too great in complexity, it cannot help to ensure that the best quote is
always delivered to the investors. In order to find those critical variables, thirteen
interviews with lead brokers were conducted.' Figure 5 shows the variables that
influence the quote process.
1 ‘
A full version of the questionnaire used in the interviews - in German - can be obtained from the author of this paper.
=
J
. |Description
Liquidity of the paper
Spread width of quote
Quote volume
Spread width of reference market
Volume of reference market
Number of purchase orders in the order book
Number of sales orders in the order book
Number of purchase orders on XETRA
Number of sales orders on XETRA
Short positioning
Long positioning
Market volatility
Paper volatility
Correlation with index
Position limit
Individual volume of orders
Individual order limit
Seriousness of individual orders (origin)
Last ascertained course
Price of oil
21 {Price of gold
22 |Dollar rate
23 |Market tendencies / trends
24 |Branch tendencies / trends
25 |Paper tendencies / trends
26 {Prime rates
ee
Solo] H] EO] S]S]O]P]™]H] oy] & | co)no
Figure 5: Variables that Influence the Quotation Process
In order to analyse the cybernetic relationship between these variables, the Sensitivity
Model by Vester (Vester, 1980) was applied. The lead brokers estimated the mutual
influence of each pair of variables within a matrix of influence (Figure 6).
[affect of on
Liquidity of tho paper
Spread width of quole
uote voiums
Spread width of eforence market
Volume of reference market
urnber of purchase orcers inthe order Hook
Nurnbar of salac erdare m the order book
Number of purchase urders on XETRA
Nurnbar of salas ards on XETRA
70 | Shor positionng
17 [Lang positioning
“2 [ares vat
72 |Paser valetity
“2 [Dovelation with index
14 [Position iit
76 [rdvidual sclurre of anders
“7 [incvidual ore iit
1 [Seriousnass of Indwaual erdors [angha)
79 |Last ascertained couree
20-[Price of oi
21 [Price af gold
22 [Dollar rate
23 [Market tendencies /rends
24 [Branch tendencies /trends
25 [Paper tendencies / trends
26 [Prine rales
2|=|=/e]5|=/e}5|=]e}s|e|>]e[e|=|=/el=|a}
a-|=1==[>[el=le[=Flelelelel=l=|=[=[=[=[eF 3]
=[e/>[=|e|=]=]e|=]=/5/>]>]=/e]5]=]o|a|al=|=|ale|y
hol lelelel=fee (=e flslelel= Eloise bia
e= == eele-e---Feh---F-F-e-R)
Fi fsle[=Flel=Fel-[2F/-21e|-F lee -|-Fisl>
hls l2[2[-[>[2[2/2[2[=!sI\ele|=]- 8 ]>|-|=[- Fea
EPR PEPREEEEEERREEEEEEEEEECE
FEFEENS Perris F=Plelellel[/5/5|
= )o]=|-]eIeleleleletele|=|=|s]elel= a)
3 strong affect; 2= medium effect; 1 = wesk affect; 0= no affect
Figure 6: Matrix of Influence
kritisch |
|
active variables |
critical variables |
Figure 7: Character of Variables
Here, variables which have an effect on other variables are listed line by line, while
those influenced by other variables are listed column by column. By forming the line
and column total (the active and passive sum), the identification of active or passive
variables becomes possible. The result of this sensitivity analysis is shown in a graph,
which illustrates the variables according to their character. Critical variables can be
found in the upper right hand sector of the graph (Figure 7). Critical in this context
means that these variables have a strong effect on other variables, while at the same time
remaining enormously influenced by others. Within this graph, the column total is
shown on the x-axis, while the line total can be seen on the y-axis.
10
This analysis is a critical input for the further development of the intended decision
support system for the lead brokers as only this systemic analysis of the cybernetic
relationships of the variables ensures a truly holistic view of the situation. In addition to
that, simulations can be run to see how changes in one variable affect the others.
Looking at the situation of the lead brokers it is clear that only the clever setting of
the quote ensures profit for the broker and the institution he/she works for. The only
variables the broker can actively influence are those that correspond directly with the
quote itself (spread width of quote and quote volume). However, as this must be done
very quickly and for a great number of stocks simultaneously (sometimes only 60
seconds time for the execution of an order and over 30 stocks per broker) a supporting
system should help the broker to adapt these variables more quickly to changes in the
market situation. In order to achieve that certain modules were developed that can be
used to store pre-regulations and —settings by the broker. How these modules work is
described in the following paragraph.
4.1 Module description
The broker is subject to certain laws and provisions that build a framework for the
setting of the quote. In addition to that certain regulations and policies exist that are
specific to the stock market. This framework varies form stock to stock according to the
liquidity and volatility of each paper. Combining this framework with the actual state of
the order book does usually not lead to a competitive quote as it is too broad, but it leads
to a quote that satisfies the regulations and is from that point of view correct. This is our
first module (M1) that satisfies the minimum standard according to the stock markets
regulations. The second module (M2) reduces the quote spread by the LB-FSP’s fee (the
so called courtage) to give back the order fees to the investors in the form of a better
quote.
The third module (M3) builds on the findings of the sensitivity model that show that
the variables “Liquidity of the paper” and “Paper volatility” are most critical to the
quotation process. A so called risk-factor was derived form the papers liquidity and
volatility. That risk-factor can also reduce the quote’s spread even further. The forth
module (M4) builds on the same logic to raise the minimum order volume according to
calculated risk-factor. As the LB-FSPs hold themselves positions of the stocks they
trade (long positioning), or they trade stocks they do not own at the moment of trade
(short positioning) they have to keep in mind these positions while stetting the quote.
Therefore the fifth module (M5) gives the lead broker the possibility to reduce the
spread width automatically even further, if a certain rate of return set by the broker is
reached. With that module it is possible to automatically reduce or increase the own
positions of stocks. The sixth module (M6) builds on the same logic to raise the
minimum order volume. In this module the held volumes of the positions owned by the
LB-FSP are incorporated automatically in the quote. The seventh module (M7) allows
incorporating the broker’s market trend assessment, by setting the quote slightly above
or below the reference market within the given regulations of the stock exchange.
The development of these modules has been guided by the matrix of influence. The
critical variables liquidity and volatility have incorporated in the modules M3 and M4.
The modules M5, M6, M7 deal all with the spread width and the order volume, which
are the variables that are directly linked with the quote process as stated before. As these
variables were found to be reactive to numerous other variables the modules help the
broker to react faster in a turbulent market environment. The module M2 can be viewed
as to ensure the baseline of the company’s strategy (that the quote delivered is just as
attractive to investors as the competitors’). Module M1 is just the basic input factor for
11
all other modules. How the modules work within the quotation process is depicted in
Figure 8.
Sets / Resets Pre-
regulations and Settings Regulations
from Stock
Exchange
Laws and Pree
Provisions Verifies Status [Sopot [aucte Quote
uppor i
Lead Broker i Order Book |—#—* cyctemmi-7 [a2] Quotation an Market —_orders|
XETRA Data
XETRA Data
Corporate Information
Figure 8: Quotation Process Control Loop Model with Pre-Regulating Modules M1-7
The active variables show further automation potential which could be explored
within further research. Here, it has been shown how a systemic approach can add value
for the strategy development and implementation in software. The modules have been
developed and tested and results have shown promising effects.
5. CONCLUSIONS
The increasing automation of the finance does not only concern the LB-FSPs, but
rather all banks on a worldwide scale. Just as the invention of the steam engine in the
1800s meant the replacement of many professions by machines, lead brokers in stock
exchanges will also be replaced by machines in the medium-term due to great progress
in information and communication technology. It is thus necessary for affected
enterprises to adapt to these developments. The article develops strategies that enable
affected groups to deal with these expected developments. The established stock
markets, and therefore the LB-FSPs, will only be able to exist in the market if they
provide better quotes for the stocks they deal with than the competition - this is the only
way orders will be placed. If sufficient differentiation is not attainable, the LB-FSPs can
only attempt to undertake influence on the markets themselves, for example by effecting
the development of additional services.
The developed control loop model for the quote process shows the automation
possibilities and offers a good link to further development in the form of software.
At the same time a system was proposed to combine strategy development and
realization. The use of systemic approaches has proved to be helpful in this case.
Examples include the OSTO model and the sensitivity model for the development of an
automated quote, that if required, stays open to manual input should the variables need
correcting and at the same time does not consciously disregard human influence.
12
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