Can transformation outsourcing be a “win-win”?

Performance Volume 2 Issue 4

Author: Evgeny Akseno,  General Manager of the service science consulting company ISSP Energy GmbH.

Keywords: transformation outsourcing, transformation process, service level agreement, service provider, service infrastructure, SLA






printed article see, please, here.


 When a business decides to upsize or downsize in response to market changes or changes in the global economy, or in a desire to improve its business performance, many  take the opportunity to test a new model for such internal services as accounting, HR, IT, etc. 

Some choose an outsourcing model, while others decide on a shared service center or in-sourcing model.

Over the last ten years, the Russian power engineering giant – RAO EES has been transformed from a regional-based structure into a structure (before transformation process RAO EES include regional subsidiaries (daughters company), each of which had the set of power engineering businesses – from generation and transportation (grid) – to distribution and sale. After reformation instead RAO EES appeared national greed company, holding of milti-regional distribution companies, several big (wholesale) generation company and a numerous selling companies). It was during this time that the Russian energy market was established.

 As part of the same process, in 2004,  the transformation of the subsidiary, RAO EES IT  – the company’s main computer center into a commercial IT-provider began.  The main reason for this was that the restructuring of  RAO EES in 2008 led to the business being split into a number of separate parts that are intended to be merged with other companies at a later date (eg, grid, generation, distributing, etc).  RAO EES’s Board of Directors decided that, in such a situation, a shared IT service center sourcing model was the most appropriate way to keep main computer center services running reliably.

 Until that point, the main computer center activities were largely unstructured. During the transformation of the unstructured IT activity into services,   the existing management model was transformed into a pro-activity model with built-in service efficiency and quality management processes. This was the key condition for commercial survival.

 In this article, we describe the transformation process at RAO EES main computer center and the gains that were made as a result.


Cross of innovation


Companies of all sizes need to be able to respond to the demands of a dynamic market with the  dexterity of a rapid response unit in the military. Success hinges on the ability to quickly switch to a more effective business strategy, the appropriate resources bases and technological infrastructure in response to changing demands. A modern business structure needs to continually adapt to its business environment in a way that gives the largest, most reliable and quickest returns.

As the pace of customer demand increases, so must the resource and infrastructure elements lifecycle. This is why in the current environment companies need to talk about active adaptation, which needs continuous innovative proactive behavior. 

Changing customer demands, regulatory changes and the rapid development of technology can place significant strain on a complex IT infrastructure that can easily catch an internal or external service provider unawares and result in inefficiency or even chaos. Consequently,  many companies have already reached innovation crisis state, which is illustrated in picture 1.

In the active adaptation zone (green zone) the services provided undergo continuous innovation via the different improvement projects. Continuous evolution results in the growth of maintenance fees.  But where maintenance is inefficient,, once the maintenance fee reaches the level budgeted (passive adaptation zone – yellow zone), innovation stops. The cause is clear: to drop the innovation initiatives we need a solution. But in order to drop the maintenance fee, it is necessary to make special arrangements, which need additional effort, time and budgets. Guess who will be the first victim?  The idea is: you can stop some projects in work or a services provided (including maintenance operations). Projects provides future needs fulfillness, but services – current operations consistency and reliability. If we stop the innovations we will failed in a concurrency tomorrow, but if we will failed in consistency or reliability – it will bring problem today.  We can not to stop services, but optimized it. We can bye, for example, offshore resources instead onshore, we can optimize infrastructure etc. But all this needs a lot of efforts. Often more efforts, then needs freezing the project. That’s why more often projects is more easy victim for cost killers, then services.


If these “special arrangements” are not fulfilled on time, the no adaptation zone (the red zone) will be reached. In this zone, the level of risk increases dramatically and process reliability permanently decreases up to a stagnation point.

Being in the passive adaptation zone is very risky: in a context of the economic crisis, non-core service budget level expectation can be drastically cut, changing the zone borders and adaptation regime (see picture 2). A bleak outlook (red bullet on picture 1 and 2 can suddenly become a terrible reality (black bullet on picture 2).

Those companies that constantly work to maintain their position in the active adaptation zone will be better prepared to select, focus on and fulfill effective strategies, giving them significant competitive advantage over their competitors.

Increasing the size of the budget is not a long-term solution to the problem. This will not compensate for poor maintenance management. What is needed is a range of activities including quick identification of inefficient zones (resource black holes) and  the restoration of process effectiveness.

A service–oriented approach is one way of achieving this. In this approach, organizational activity is represented as a network of separate valuable internal outcomes (services). Service value can be established using the appropriate metrics, which express the business requirements and indicate whether the service meets them. The key metrics can be documented in a service level agreement (SLA) between the customer and the service provider. The service provider can be external (outsourcing service provider) or internal (shared service center or special department in in-sourcing model) business units.

Services include human resources, infrastructure resources (eg, application, hardware, telecommunications infrastructure), materials, information flow etc. Some services can consume other service (sub-services) outcomes. As such, service provider activity can be represented as a network of services, each of which can be described in the SLA. In this type of network, business level (end-user) services are some sub-services, whose outcomes end-user services utilize in the production circle. It is the study of this model that is the subject of Service Sciences (Spohrer, J. and Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Service Engineering, ed. Karwowski & Salvendy.  Wiley.   New York, NY).

Why do we need to implement such an approach? Having established interaction between the customer and the service provider in an SLA, we can establish repeatable process to check if the services provided hits the SLA limitation and, if interaction is in non-normative way, invoke special remediation procedures. By applying the SLA format to the provision of internal activity (provided by internal service provider), a company is taking the first step towards appropriate services quality management and possibility to purchase some services from external commercial service providers. This bring internal service providers in concurrent state and force to drop the maintenance fee (shift to the left on the picture 1 and 2 and bring company to the active adaptation mode.

But pro-activity, effectiveness and quality of parts do not necessarily extrapolate to the whole. There is evidence to the contrary in the game theory: instead of success, competent service providers can bring  dependency and failure to an organization. This can be the result of inefficient management. From the other side, service provider selection failure can have a technological nature. Inter-service technological connections can be strongly bound different services to each other. This forces native service provider monopoly and can bring provider selection process to failure...

In practice, dependency on the service provider can often mean inefficiency.  Customers are challenged to  deliver pro-activity, effectiveness and quality for the whole business, without the dependency. And the service model implementation and activity-to-service transformation is the way to freedom, is the way to choose that service provider for any certain activity, which is more adequate and more pro-active.

An effective service-oriented approach delivers pro-activity, effectiveness and quality in a business. These are three of the key elements for future business success and flexibility, especially in a service-oriented post-industrial world.


Practical example

When talking about pro-activity, effectiveness and quality, it is important to look at the complete picture. Here, we look at the whole view technique that was used by RAO EES in an IT Energy project.

This approach applies to all of the activities in an organization. But for this type of experiment, it is simpler to start with non-core activity eg, information technology, human resources, accounting, etc. On the one hand, these activities are not part of the main value chain and so have less influence on the business strategy performance. But on the other hand, they are generally considered to be the outsourcing candidate that will increase pro-activity and efficiency and, therefore, need to be structured.

In the last ten years, the Russian utilities giant, RAO EES, which provides more than 70% of the Russian Federation’s energy production and has a mix of utilities assets (generation, transportation and distribution) has undergone a transformation. The main objective of the transformation was the implementation of the new business-oriented organizational structure, in which generation, transportation and distribution business were separated into different legal entities groups.

As a result, a number of large generation companies, a backbone grid company, a distribution grid company, various energy distribution and maintenance companies were established by the time this process was completed in July 2008.

Within  the main restructuring  process, a smaller process was initiated in 2003: RAO EES’s IT department - the utility’s main computer center - which employed about 500 people, was transformed into a group of companies called IT Energy - a successful activity-to-services transformation.

The restructuring of IT Energy was completed in 2008, with the formation of a commercial service provider. The newly formed IT Energy had many external clients and could provide a range of  services to the market.

Through the transformation process,  service efficiency was considerably increased, the HR skills base and the assets base (hardware and software) were improved and modernized, and IT Energy was able to maintain financial stability independent of the parent company (RAO EES).

Today the IT Energy group is a successful commercial IT Service provider that competes in the IT market . Since the transformation of IT Energy, revenue and capitalization have risen steadily (from $8 to 21 million per year) to compete with the other professional players in the Russian IT Market.

We looked in depth at each part of this service-oriented approach, focusing on: pro-activity, efficiency and quality.


How to be pro-active

An active strategy and the motivation and access to resources are necessary for pro-activity. The main subject here is the form of “client - service provider” interaction.

The “client - service provider” interaction model evolution goes from simplicity to complexity in five stages: in-sourcing model, single-sourcing model, multi-sourcing model, multi-sourcing model with SLM (service level management) broker, multi-sourcing model with SLM broker and compliance advisor (see picture 3).

In its simplest form - in-sourcing – the service provider is located within the organization as a department, business unit or branch. Much hidden communication (finance, requests, technological, business process, etc) binds the in-sourcing service provider to the client body. As such, it cannot be easily separated and managed as a business,  nor can it have its own strategy and independent investment activity, which means there is little scope for pro-activity.  At this stage, it is hard to set full service costs as, in most cases, they are paid on a cost plus basis and had no motivation to decrease maintenance cost.

Single-sourcing has the advantage of having only one responsibility point. A service provider can be managed like a business and has a structured interface with the client. At the same time, the service provider holds a lot of power, making the service management process difficult and can result in a lack of transparency in working processes.

With each stage in the service provider’s (or group of service providers) development, the aim is to achieve pro-activity, efficiency, and quality and to overcome conflict of interest. Multi-sourcing and the stages that follow make the service provider more transparent, but a great deal of effort is required to manage the service provider’s relationship with the other actors. The disadvantage of a pure multi-sourcing model is the absence of a single point of responsibility. This forces the process to move to the next stages.

In the next stage, the service level manager Is a relationship broker. But the broker has more power and less responsibility than in the single-sourcing model. To balance this situation and achieve objectivity and technological transparency, the next sourcing generation has a separate advisor in the form of a company that monitors the process, but is not involved in the provision of services.

In each step, different roles are separated into stand-alone organizational units in order to increase transparency and overcome conflict of interest in the service providing process. Each generation has its own strengths and weaknesses, the most important are brought together in table 1.
Table 1. Evolution stages strengths and weaknesses  

Evolution Stage




Single responsibility point

Strategy fully dependent on business strategy

No pro-activity (no own strategy, no own investment activity)

No motivation to decrease maintenance and innovation costs


Single responsibility point

Pro-activity potential

Conflict of interests

Dependency risks


Decreased dependency risks

Pro-activity potential

Management complexity

No single responsibility point

Multi-sourcing with broker

Single responsibility point

Decreased dependency risks

Pro-activity potential

Unbalanced broker power vs responsibility

Broker power increasing risks

Scheme establishing and management costs

Multi-sourcing with broker and advisor

Single responsibility point

Decreased dependency risks

Pro-activity potential

Service providing transparency

Relationship complexity

Scheme establishing and management costs

Establishing a service-oriented relationship requires the transformation of the service process. This can be done in three ways, differentiated by risks and project length like in mountains’ sky: blue, red and black routes (see picture 4)

The blue route (“divide and conquer” route as shown in picture 4 represent the transformation process. This is the most comfortable way to transform business activities into services, but requires significant time and effort on the part of the management, and potentially, the help of external experts too.

Picture 5 illustrates the insourcing-to-outsourcing transformation process scenarios. In each of the proposed scenarios, the services infrastructure is transferred to a special “assets” company, which will be responsible for asset management activity. Operational activities (people and processes) are transferred to another service provider that will be responsible for the provision of services.  

Using the blue route, both the service provider and the service infrastructure company are subsidiary and controlled by main client. So, A and B (see picture 5) will (taking in account all options program) equal more than 50% shares + 1 to keep control in main business hands. In most forced scenarios  – black route – the service provider and infrastructure are not controlled by main client . A and B, in this case, will equal less than 50% - 1 share to convey control to the non-client shareholders. In the middle scenarios – red route – A will more than 50% +1 and B – less than 50%-1. The most important results of A and B managing are collected in table 2.

Table 2. Structure of equity influence

Changing direction

A (work process)

B (assets base)


Increase control from the main business

Increase necessary process expenses

Slow the transformation process and can bring stagnation

Guarantee business independence

Decrease strategy and actions pro-activity [strategy can be active or passive. Increasing A stimulate strategy activity. Actions so on

Decrease service provider investment

Freeze infrastructure optimization and centralization processes

Freeze investment from the partner (service provider) side

Prove assets safety and ownership

Decrease pro-activity

Improve independency


Force transformation process, service optimization and centralization

Force investment into infrastructure (if B on low level – into alternative assets base)

Force pro-activity (especially if B on the high level)

Force infrastructure centralization

Force partner investment into

Dependency risk

Increase partner investment flow to infrastructure modernization

Force pro-activity and efficiency

The IT Energy company’s Main Computer Center of Power Engineering (was a 100% owned subsidiary of RAO EES at the beginning of transformation process) which was transformed into a group of companies. Picture 6 shows the new structure of the IT Energy group.

Assets (infrastructure, hardware and software) were transferred to the IT Energy group’s parent company (number 1 in picture 6). All administrative activities (HR, finance, lawyers etc) were concentrated in the administrative service company (2). Service activities were spread across four service companies and five competence centers (3). In addition, new monitoring (4) and management (5) were established. The monitoring company provided service level quality and technical level monitoring. The management company provided management services (if necessary) and represented minority interest in the transformation process.


Service companies were divided between the technological services provided:

·       Data center engineering center (co-location services);

·       IT infrastructure services (dedicated server providing, infrastructure support, etc);

·       Application management company (application, data & report management and maintenance)

·       Desktop management (user support, periphery support. etc)

By the end of the transfer process anywhere from 30 to 60 people worked in each of the companies, making a total of about 300. The five competence centers provided project activity in different subject areas: SAP practice, Microsoft practice, Industry analytics, etc. On average, between 6 and 20 people worked in each competence center.

The desired structure was implemented through a number of steps. At the start of the project, the infrastructure and people were held in one company. It took about one year to identify the right service catalog and department structure, which later was reflected in group structure. In that time, the company’s equipment and software was identified and linked with a newly established service catalog, so that from one division, a new company in the group was created.

However, it is critical that employees understand exactly which services in the services catalog correspond with their roles.

The transformation process requires the complex organizational structure and internal relationships to be seamlessly embedded within the group.  The entire group needs to adhere to the intergroup rules established before the transition to a more complicated group structure. This  takes  time; in the IT Energy project, it took one and a half years for the rules of intergroup relationships to be understood. Is it possible to buy an external product if one of the group members can provide the same? What is to be done if a group member’s tariff is much higher than the market rate? How to pay commission if one member brought a client to another member? Are intergroup tariffs the same as external tariffs? How to deal with the situation where one member’s business plan failed because another member’s business plan failed? A lot of difficult questions arise when this potential is captured.

These questions demand answers that form the basis for the intergroup rules of communication. In turn, this process enabled IT Energy group to operate like one service provider.

Each company within the group had its own market-oriented strategy and business plan, loaded according to its readiness to provide commercial services. When business plans are successfully executed with high quality services and in accordance with intergroup rules, then the company’s management team retains power. If not, the management company (5) will immediately takeover the management of the company.

Each member of group role description and determination and appropriate rights delegation at the individual company level enabled passive work processes to move into the pro-active mode, when people motivated to provide services on effective and quality manner. In a pro-active mode peoples:

- looks for and close effectiveness black holes,

- stop some redundant and/or not necessary operations,

- identify and stop old devices, which takes a lot of efforts to support,

- optimize infrastructure

- start to centralize and optimize software and hardware,

- standardize services for new clients to catch mastab effect

- looking for new market niches (pro-active strategy, if it supported necessary resources stimulate trials to find a new market niches for the company)... 

As a result, revenues started to grow from 32 to 75% annually. The revenue share of external companies increased from 17% in 2003 to 60% in 2006 and 20% - 2008 as  new clients started to come.

It is worth noting that, when this key investment program to modernize the data centers and IT infrastructure was launched, IT Energy’s parent company,  RAO EES, did not invest in the process. Based on these results, it is possible to say that, in the case of the IT Energy project, pro-activity was harnessedd. In the IT-Energy project we have got pro-activity.

This example shows that harnessing pro-activity can be achieved by transforming an organizartion’s internal divisions into separate business units or shared service centers (SSC). Done this way,  the process can to be managed effectively and the latent forces that are liberated in this process are the result of long-term management efforts in business development and more common business efficiency and capitalization estimation.

When the markets were hit by the global economic crisis in 2008,, the Russian IT market was badly affected, with 80-90% capitalization failure in IT companies. The IT Energy group was caught  in  the middle of this situation, for example, the SAP practice competence center almost collapsed. But not all of the company was negatively affected.  The Data center, IT infrastructure and Desktop management services all continued to generate strong revenues and profits.  The organizational structure presented above helps some companies not only to survive, but also to grow.  As the result of this efforts total consolidated group revenue left on the same level, as before crisis.


How to improve efficiency

The service provider’s focus is on managing services for clients in an efficient and effective way. Managing technology effectively can be vital in this effort.

 It is estimated that there is significant hidden potential to increase  optimization and efficiency  in unstructured activities. There are a number of ways of  improving efficiency :


1.       Clearly determine the organization’s borders and resources (peoples, infrastructure, materials, etc.)

2.       Establish all of the valuable activity elements (eg, service, projects and other activity) - first generation service catalog

3.       Establish correspondence between activity elements (AE) and resources that are consumed in the provision of the service.  It is important to get full product costs (people, infrastructure, materials and underpinning contract or sub-services used) to be able to compare with the market price

4.       Compare full AE costs with market price (if exists) and determine the AE value and costs relevancy

5.       For each AE, determine the development strategy (“kill” or “sell” vs “hold” vs “improve”)

6.       Determine  the order of priority for the development of each AE

7.       Prepare and start an optimization program.

Before investing resources in describing particular activity elements, it is necessary to determine the effectiveness and importance of this action. In order to do this, it is necessary to determine the available human and infrastructure resources and allocate them to certain services.

For the step 1 to complete we need whole company activity and resources pool have to be identified. On this step human resources base, including temporary personell, have to be identified. Infrastructure, hardware and software, which used to provide services, have to be described too. Some of services consume a lot of material (for example, cartridge and other spare parts for printers, faxes etc), which have to be described too.

For the step 2 we used an idea that whole activities in the IT Energy can be divided on set of Activity Element (AE). Each of AE consumes human resources, infrastructure resources, material, other services valuable product etc. 

AE has “project” type if it’s starts from time to time on timetable basis or if some identified condition had happened. We can estimate how many time this AE needs to be complete and how many resources each type it’s consumes.  AE has a “service” type if it’s we know normative monthly average resource consumption per production unit for this AE and control divergence level for each time step (month or week. In IT Energy case - month). AE has an “other” type if we just allocate it’s resource consumption by facts. For each of AE it’s type can be defined.

In IT Energy case most of the resources (month average - 60-80%) had a “service” type. 20-30% - had “project” type. 

On the step 3 we measure AE resources consumption. Infrastructure complexity and high changing dynamics can bring a lot of problem on the step 3. Doing this, it is possible that cost migration effect can appear (see picture 7).

The cost migration effect indicates that, in a highly complex and dynamic environment, costs that are allocated to a certain activity element, will offset the elements that are less controllable or are located outside controlled space borders. To prevent unmanaged cost (resources consumption) migration, it is necessary to check resources identified and resource allocated balance:

SUM of resources available (consumed) = SUM of resources allocated (equation 1). 

To control resource allocation correctness for each AE type necessary to be establish as early as possible, the following:

·       Two control offices – for “project” and “service” type.  These offices will control resource consumption in AE of appropriate type

·       The normative limits for “other” AE type resources consumption


Project management is not a new concept.

Maintanance management techniques have been developed over the past 60 years (a long time before ITIL – IT Infrastructure Library, Service Sciences and other modern solutions) on how to manage the work process in service organizations were introduced. One such technique is the reliability centered maintenance (RCM) approach was developed in 60-th.

Most techniques assume that, for each service (or “function” in RCM terminology), there is a set of operations. For each operation there is a description, resources consumption estimation, condition, when ticket for special job will generated (on time-directed or condition-directed base…) etc. As a result it is possible to run each operation by an automatic work ticket generation.

But when we talk about transformation process at the very beginning of building service management, we need to establish a simplified operational model as quickly as possible to control work processes. Then it is possible, going from high priority AE to low priority, to develop the aim model.

A simplified technological map was developed in the IT Energy project to establish a quick and cost effective operational control for each service (see picture 8). 

 This map has an operations list and the average monthly resource consumption for one service product unit. Resource consumption was estimated at the beginning of the control process for each service. This map helped compare estimations with actual statistics.  

In order to attain most effect , the assessment needs to start with the resource that can deliver the greatest results, before moving on to other resources. In the IT Energy project, we started with human resources. The reliance on human resources is represented in picture 9. The blue line represents the forecasts for human resources calculated using technological map data. The red line shows the resources that were actually used.

Point 1 on the graph is the starting point from which the technological map’s parameters were constructed using factual data (learning stage). Point 2 shows the minimum resources required to complete the operations included in technological map. The blue line shows the forecast data, which maintains the same level as point 1 because, typically, to produce the same quantity of units, you need the human resources to be relatively consistent. Point 3 shows the maximum resources required to complete the technological map operations.  The optimization circle idea is:

1.       To define normative resource consumption level

2.       Then wait for considerable declining (point 3),

3.       If it had happened investigate operations, which consumed additional resources (which brings the resource consumption increasing)

4.       separate out this operations from AE “service” type into new AE “project” type

5.       describe normative resource consumption for this new AE, 

6.       refine normative resource consumption for technological map for old AE (“service” type), tacking in account separations of some operations (new AE)

7.       then go to step 2. (“Maximum catching circle”)

8.       If there is now considerable declining for a long time – wait for point where minimum resources required to complete the operations of technological map (point 2)

9.       If had happened refine normative resource consumption for technological map, tacking into account minimum resource consumption

10.   Then go to step 2  (“Minimum catching circle”)


Picture 9 demonstrates the situation within the IT Energy project in May 2007 when the factual data was analyzed and the technological map for a group of services was revised. Some valuable operations that formed part of the operational process were excluded from the technological maps, which were done at point 3 (step 4 “maximum catching circle”). These operations were defined as temporary operations. As a result, in point 4, an accurate forecast was made for staffing levels. The graph shows an increase in resource consumption in June and July because more service units were provided. So, in order to estimate full resource consumption for services, the resources that are used by operations from the technological map (old AE) must be added to those consumed by all scheduled operations (group of separated out AE for this services).

If no maximum met for a long time (in IT Energy case about 3 months), a “minimum catching circle” can be used (step 8). In this approach, the starting point is the minimum resource levels required (point 2). The aim of this steps is to decrease the normative average month resource consumption for the service technological map to make future declining more visible. Then the ordinary optimization circle (maximum catching) can be effectively continued.  That is why the minimum catching approach should be used to improve business processes optimization results and speed.

A continuous technological map improvement process (with separation out valuable operations) brings increasing numbers of operations (dedicated from technological map AE) under review. These operations are already managed according to the RCM approach, which suppose, that any operation mast be time directed (TD), condition directed (CD) or run-to-failure (RTF) operations. If appropriate, these operations could be scheduled and ticketed automatically (active mode). This would allow us to build a full service model in the most cost effective way, because we have identified the maximum resource consumption to identify operations that are separate from technological map operations.

We have discussed AE list (first generation service catalog) as a flat entity. However, one service usually consumes products of another service and, as a result, there can be multiple relationships between different services. This is typical of a service network.

The service structure evolution is represented in picture 10. At the first step (1) there are no services and customers can consume resources directly. In step 2, the services entity appear.  In step (2) services are recognized for smaller tasks. At this point, services (AE) not optimized and infrastructure not centralize, that’s why no scale effect received. In step 3 the flat service structure becomes optimized. Services that were disparate previously are now managed as one optimized service. As a consequence, the resources are massed in a common pool (4). At that point, it is possible to turn service management into a service chain (or network) where the sub-service consumption slot on the technological map (see picture 8) starts to work.

Once the evolution steps are completed, we can move to service chain management. This can only happen after our service catalog is established and we have attained cost effectiveness from flat services improvements. Service chain management is a complex process that requires specific expertise.

Service chain management helps to identify the next hidden problem: the resource “black hole”, uncharged services, service level disparity, cross subsidizing etc. “Black holes” are services that are actually provided, but cannot be charged (typically inherited services).Uncharged services are services that can be charged, but are not usually charged in practice. In the IT Energy project, these uncharged services related to the provision of infrastructure for data storage. In some cases, a service level disparity appears when critical services use non-critical sub-services (service level non-correspondence).  

Cross-subsidizing is one of the most common problems that service companies face, but it remains difficult to identify. It happens when the revenue for one chain of services is disproportionate in relation to costs and resource requirements. 

Table 3. Cross subsidizing effect

IT Infrastructure management


Service desk (1th line)


Desktop management (Ordinary)


Desktop management (VIP)




Conference room support


E-mail support


Application management




Table 3 shows the impact of cross subsidizing for a group of IT Energy services. The data shows that among various services, the deviation from calculated prices can reach up to 100%. The average deviation is nearly 20%. By optimizing the chain management resources, on average, a cost reduction of about 20% can be achieved. Optimizing resources for infrastructure can deliver greater benefits, but needs more investment to be able to achieve this. Table 4 compares flat service catalog (flat service mode) and services network management (service network mode) mechanisms.

Table 4. Flat and network service management mechanisms distinctions

Flat service mode

Service network mode

The service catalog is flat

Service bound in network

Services have equality of value

Service value depends on position in network (The heads of hierarchy are the products which are sold to the client. Others – internal product)

Relationship between services not taken into account

Relationship determines service importance

Autonomous effectiveness management of each service

Service chain effectiveness management

Autonomous quality management of each service

Service chain quality management

Autonomous investment management of each service

Service chain investment management

Picture 11 demonstrates practical results achieved in the IT Energy project: 

·       Primary cleaning actions – a primary flat service catalog was provided and timesheet collection processes were iplemented periodically. Cumulative HR resources use was aligned to activity elements. Infrastructure was optimized.

·       Project management - stronger controls on “project” type AE were established.

·       Service management for HR – stronger controls for HR resources consumption were established on “service” type AE and HR normative consumption was calculated.  At this step a technological map assisted in the comparison of HR resource usage forecasts with actual consumption data.

·       Service management for infrastructure resources – stronger controls for infrastructure resources consumption were established on “service” type AE and infrastructure normative consumption was calculated. At this step a technological map enabled an understanding of HR and infrastructure resource consumption and, as a result, infrastructure optimization. This took into account depreciated infrastructure being removed from the production process.

·       Service management for chained services – at this step service chain were defined. It allows to turn to service network mode and implement service network management. For the clients it brings improvement and more adequate prices for the business level services, which is based on the appropriate service chain (application management plus infrastructure management plus telecommunication support and other important technological services). For service provider it breengs possibility to manage service chain on more systemic manner and to get effect from removal “black holes”, cross subsidizing and other inefficiency reasons.  Service production centralization – through the modernization of infrastructure creating centralized processes, greater synergies could be achieved.


Service management is an evolving tool that can bring considerable economic benefits. This can be divided between clients and service provider (see picture 12).  The service provider can improve processes to lead benefit delivery. By simply transferring operations from the unstructured service providing mode to the structured sourcing mode, both organizations and their clients can see visible benefits. When infrastructure depreciates, investments are necessary to improve service quality and demonstrate added value.

In the IT Energy project, we transformed the set of resources that was consumed in the production process.

By demonstrating efficiency throughout the production process, the organization was able to create a new pricing structure that had clear margins and was more competitive in the market place.


How to catch quality?

Any transformation program needs to ensure that quality of products and services are maintained during periods of change. As a result, the quality management process has to be reviewed and rolled out simultaneously with new/adapted operational processes.

The set of technological monitoring and service desk system gives a lot of information about how infrastructure and personnel working. The problem is how to analyze this information to manage the services quality.

To systemic increase the service quality on a long-term perspective, a 3D quality model (3DQM) approach was used.     

3DQM assumes that there are three independent ways to measure quality of services:

·       Customer (or external) sources (CS) – based on incident statistics from the service desk. For a commercial service provider, this is the most expensive data because it can have a negative influence on the service provider’s image as a quality service (passive SP)

·       Customer requirements model (CRM) – quality measuring model based on SLA metrics and other metrics that measure customer needs, regulations requirements and effectiveness etc. Getting information from the CRM, based on monitoring system data, SP can analyze information about incident beginning and escalation before the client becomes aware of a problem. In this case SP can  limit its potential negative impact on the customer work process

Infrastructure performance model (IPM) – quality measuring model based on the concept that good infrastructure should help to achieve customer satisfaction. With this approach, we can get information about how an incident started to develop at the infrastructure level. This should enable us to take preventive action in future to rule out any occurrence of the incident in the first place. 

So, the idea is, that incident born in infrastructure level and can be first identify in the IPM. Then if the service quality metrics enough sensitive, it is possible to identify the incident in CRM level. Then the incident will affect on a customer workprocess and we will now about incident from the customer through service desk (from (CS level). If so, we can find that integrated quality metrics (Pipm, Pcrm and Pcs), which will indicate incident appearance in correspondent level – IPM, CRM or CS. Each of this integrated parameters consist of a lot of different metrics, which can be analyzed to identify the incident reason.

For the service provider it is very important to identify incident as early as possible. So, if the Pipm and Pcrm and Pcs enough sensitive to reflect incident appearance, the ideal situation will be, if we have got bad value for Pipm and immediately fixed the incident. In that case it is possible, that Pcrm didn’t recognize incident appearance yet and, of cause, customer didn’t call service desk yet. So, Pipm<Pcrm and Pipm<Pcs.

If incident escalation reach CRM level and Pcrm value reflect, that incident had happened, it is important to fix it before customer can fill it and will call to service desk. So, Pcrm mast be Pcs.

So, in ideal situation mast be, that Pipm<Pcrm<Pcs.   

This simple idea was lay into basement of IT Energy quality monitoring and measurement system.      


3DQM allows long-term monitoring group (or company) motivation to be built based on this principle. There are critical services that exercise significant influence on the working process, environment, safety, etc. For these critical services, the quality management system cannot have trial-and-error learning mechanism and must pre-empt problems and plan for potential scenarios. For such services, a more complex approach like RCM should be used.

In the IT Energy project the 3DQM approach helps to quickly build Customer Requirements  (CRM) and infrastructure performance (IPM) models on past actual incidents data. Picture 14 demonstrates incidents over the course of a 12-month period that was used to shape their approach. On the Y-axis the quantity of high priority incidents is represented.

Although a more in-depth discussion of quality and reliability management is needed, here we present 3DQM as an inexpensive and simple top-down model that can be used to quickly establish quality management in the transformation process. This is important because the transformation process causes distortion in the work process. Picture 14 (June - October dynamics) shows that, before 3DQM had taken affect, the old control system and services were out of control.

The Top Down 3DQM approach allows us to develop customer-oriented priorities based technological monitoring. It also allows us to focus on those infrastructure areas that are more important from the customer’s point of view.



The IT Energy project was estimated based on the following key performance indicators:

·       Revenue and profitability

·       Service provider operational activity capitalization

·       Personnel quantity - staffing

·       Revenue share of external companies etc

IT Energy operational capitalization (minus the cost of real estate) was measured on an annual basis by professional valuers. In picture 6, you can see that most of the operational activity was delivered by companies 2, 3 and 4, most of the infrastructure assets were in company 1..

From almost zero in 2003 and 2004, the cumulative capitalization of the operational companies started to grow in 2005. During that time, revenue grew too, but not at the same rate. These parameters dynamics are represented in picture 15.

When assessing the business value, the valuer in IT Energy project was influenced by the following factors:

·       Pro-active market strategy

·       Product line forming and extension with service products that comply with customer needs

·       Data center modernization project

·       Business structure, service management implementation, ISO 9001:2001 certification, etc.


The IT Energy process took more than four years to complete and proved that, when a business structure is transformed in such a (service-oriented) manner, it can:

·       Open and dynamically manage internal non-core services market of huge company

·       Provide access to the company’s internal markets for professional service providers

·       Provide alignment by way of service support, distributing the providing process among the set of professional providers (internal or external)

·       Increase capitalization and attractiveness potential Shared Service Centers and company itself.

·       Help to quickly identify inefficient divisions and exclude them from the value chain.


After the IT Energy project was finished, our group of professionals established the ISSP-Energy Gmbh professional community ( in order to maintain their expertise. Now ISSP-Energy provides a similar approach to service management model implementation in one of the biggest telecoms companies and bank in Central Asia.