Best in Class Finance Functions For Police Forces

Background

Police funding has risen by £4.8 billion and 77 per cent (39 per cent in real terms) since 1997. However the days where forces have enjoyed such levels of funding are over.

Chief Constables and senior management recognize that the annual cycle of looking for efficiencies year-on-year is not sustainable, and will not address the cash shortfall in years to come.
Facing slower funding growth and real cash deficits in their budgets, the Police Service must adopt innovative strategies which generate the productivity and efficiency gains needed to deliver high quality policing to the public.

The step-change in performance required to meet this challenge will only be achieved if the police service fully embraces effective resource management and makes efficient and productive use of its technology, partnerships and people.

The finance function has an essential role to play in addressing these challenges and supporting Forces’ objectives economically and efficiently.

Challenge

Police Forces tend to nurture a divisional and departmental culture rather than a corporate one, with individual procurement activities that do not exploit economies of scale. This is in part the result of over a decade of devolving functions from the center to the.divisions.

In order to reduce costs, improve efficiency and mitigate against the threat of “top down” mandatory, centrally-driven initiatives, Police Forces need to set up a corporate back office and induce behavioral change. This change must involve compliance with a corporate culture rather than a series of silos running through the organization.

Developing a Best in Class Finance Function

Traditionally finance functions within Police Forces have focused on transactional processing with only limited support for management information and business decision support. With a renewed focus on efficiencies, there is now a pressing need for finance departments to transform in order to add greater value to the force but with minimal costs.

1) Aligning to Force Strategy

As Police Forces need finance to function, it is imperative that finance and operations are closely aligned. This collaboration can be very powerful and help deliver significant improvements to a Force, but in order to achieve this model, there are many barriers to overcome. Finance Directors must look at whether their Force is ready for this collaboration, but more importantly, they must consider whether the Force itself can survive without it.

Finance requires a clear vision that centers around its role as a balanced business partner. However to achieve this vision a huge effort is required from the bottom up to understand the significant complexity in underlying systems and processes and to devise a way forward that can work for that particular organization.

The success of any change management program is dependent on its execution. Change is difficult and costly to execute correctly, and often, Police Forces lack the relevant experience to achieve such change. Although finance directors are required to hold appropriate professional qualifications (as opposed to being former police officers as was the case a few years ago) many have progressed within the Public Sector with limited opportunities for learning from and interaction with best in class methodologies. In addition cultural issues around self-preservation can present barriers to change.

Whilst it is relatively easy to get the message of finance transformation across, securing commitment to embark on bold change can be tough. Business cases often lack the quality required to drive through change and even where they are of exceptional quality senior police officers often lack the commercial awareness to trust them.

2) Supporting Force Decisions

Many Finance Directors are keen to develop their finance functions. The challenge they face is convincing the rest of the Force that the finance function can add value – by devoting more time and effort to financial analysis and providing senior management with the tools to understand the financial implications of major strategic decisions.

Maintaining Financial Controls and Managing Risk

Sarbanes Oxley, International Financial Reporting Standards (IFRS), Basel II and Individual Capital Assessments (ICA) have all put financial controls and reporting under the spotlight in the private sector. This in turn is increasing the spotlight on financial controls in the public sector.

A ‘Best in Class’ Police Force finance function will not just have the minimum controls to meet the regulatory requirements but will evaluate how the legislation and regulations that the finance function are required to comply with, can be leveraged to provide value to the organization. Providing strategic information that will enable the force to meet its objectives is a key task for a leading finance function.

3) Value to the Force

The drive for development over the last decade or so, has moved decision making to the Divisions and has led to an increase in costs in the finance function. Through utilizing a number of initiatives in a program of transformation, a Force can leverage up to 40% of savings on the cost of finance together with improving the responsiveness of finance teams and the quality of financial information. These initiatives include:

Centralization

By centralizing the finance function, a Police Force can create centers of excellence where industry best practice can be developed and shared. This will not only re-empower the department, creating greater independence and objectivity in assessing projects and performance, but also lead to more consistent management information and a higher degree of control. A Police Force can also develop a business partner group to act as strategic liaisons to departments and divisions. The business partners would, for example, advise on how the departmental and divisional commanders can meet the budget in future months instead of merely advising that the budget has been missed for the previous month.

With the mundane number crunching being performed in a shared service center, finance professionals will find they now have time to act as business partners to divisions and departments and focus on the strategic issues.

The cultural impact on the departments and divisional commanders should not be underestimated. Commanders will be concerned that:

o Their budgets will be centralized
o Workloads would increase
o There will be limited access to finance individuals
o There will not be on site support

However, if the centralized shared service center is designed appropriately none of the above should apply. In fact from centralization under a best practice model, leaders should accrue the following benefits:

o Strategic advice provided by business partners
o Increased flexibility
o Improved management information
o Faster transactions
o Reduced number of unresolved queries
o Greater clarity on service and cost of provision
o Forum for finance to be strategically aligned to the needs of the Force

A Force that moves from a de-centralized to a centralized system should try and ensure that the finance function does not lose touch with the Chief Constable and Divisional Commanders. Forces need to have a robust business case for finance transformation combined with a governance structure that spans operational, tactical and strategic requirements. There is a risk that potential benefits of implementing such a change may not be realized if the program is not carefully managed. Investment is needed to create a successful centralized finance function. Typically the future potential benefits of greater visibility and control, consistent processes, standardized management information, economies of scale, long-term cost savings and an empowered group of proud finance professionals, should outweigh those initial costs.

To reduce the commercial, operational and capability risks, the finance functions can be completely outsourced or partially outsourced to third parties. This will provide guaranteed cost benefits and may provide the opportunity to leverage relationships with vendors that provide best practice processes.

Process Efficiencies

Typically for Police Forces the focus on development has developed a silo based culture with disparate processes. As a result significant opportunities exist for standardization and simplification of processes which provide scalability, reduce manual effort and deliver business benefit. From simply rationalizing processes, a force can typically accrue a 40% reduction in the number of processes. An example of this is the use of electronic bank statements instead of using the manual bank statement for bank reconciliation and accounts receivable processes. This would save considerable effort that is involved in analyzing the data, moving the data onto different spreadsheet and inputting the data into the financial systems.

Organizations that possess a silo operating model tend to have significant inefficiencies and duplication in their processes, for example in HR and Payroll. This is largely due to the teams involved meeting their own goals but not aligning to the corporate objectives of an organization. Police Forces have a number of independent teams that are reliant on one another for data with finance in departments, divisions and headquarters sending and receiving information from each other as well as from the rest of the Force. The silo model leads to ineffective data being received by the teams that then have to carry out additional work to obtain the information required.

Whilst the argument for development has been well made in the context of moving decision making closer to operational service delivery, the added cost in terms of resources, duplication and misaligned processes has rarely featured in the debate. In the current financial climate these costs need to be recognized.

Culture

Within transactional processes, a leading finance function will set up targets for staff members on a daily basis. This target setting is an element of the metric based culture that leading finance functions develop. If the appropriate metrics of productivity and quality are applied and when these targets are challenging but not impossible, this is proven to result in improvements to productivity and quality.

A ‘Best in Class’ finance function in Police Forces will have a service focused culture, with the primary objectives of providing a high level of satisfaction for its customers (departments, divisions, employees & suppliers). A ‘Best in Class’ finance function will measure customer satisfaction on a timely basis through a metric based approach. This will be combined with a team wide focus on process improvement, with process owners, that will not necessarily be the team leads, owning force-wide improvement to each of the finance processes.

Organizational Improvements

Organizational structures within Police Forces are typically made up of supervisors leading teams of one to four team members. Through centralizing and consolidating the finance function, an opportunity exists to increase the span of control to best practice levels of 6 to 8 team members to one team lead / supervisor. By adjusting the organizational structure and increasing the span of control, Police Forces can accrue significant cashable benefit from a reduction in the number of team leads and team leads can accrue better management experience from managing larger teams.

Technology Enabled Improvements

There are a significant number of technology improvements that a Police Force could implement to help develop a ‘Best in Class’ finance function.

These include:

A) Scanning and workflow

Through adopting a scanning and workflow solution to replace manual processes, improved visibility, transparency and efficiencies can be reaped.

B) Call logging, tracking and workflow tool

Police Forces generally have a number of individuals responding to internal and supplier queries. These queries are neither logged nor tracked. The consequence of this is dual:

o Queries consume considerable effort within a particular finance team. There is a high risk of duplicated effort from the lack of logging of queries. For example, a query could be responded to for 30 minutes by person A in the finance team. Due to this query not being logged, if the individual that raised the query called up again and spoke to a different person then just for one additional question, this could take up to 20 minutes to ensure that the background was appropriately explained.

o Queries can have numerous interfaces with the business. An unresolved query can be responded against by up to four separate teams with considerable delay in providing a clear answer for the supplier.

The implementation of a call logging, tracking and workflow tool to document, measure and close internal and supplier queries combined with the set up of a central queries team, would significantly reduce the effort involved in responding to queries within the finance departments and divisions, as well as within the actual divisions and departments, and procurement.

C) Database solution

Throughout finance departments there are a significant number of spreadsheets utilized prior to input into the financial system. There is a tendency to transfer information manually from one spreadsheet to another to meet the needs of different teams.

Replacing the spreadsheets with a database solution would rationalize the number of inputs and lead to effort savings for the front line Police Officers as well as Police Staff.

D) Customize reports

In obtaining management information from the financial systems, police staff run a series of reports, import these into excel, use lookups to match the data and implement pivots to illustrate the data as required. There is significant manual effort that is involved in carrying out this work. Through customizing reports the outputs from the financial system can be set up to provide the data in the formats required through the click of a button. This would have the benefit of reduced effort and improved motivation for team members that previously carried out these mundane tasks.

In designing, procuring and implementing new technology enabling tools, a Police Force will face a number of challenges including investment approval; IT capacity; capability; and procurement.

These challenges can be mitigated through partnering with a third party service company with whom the investment can be shared, the skills can be provided and the procurement cycle can be minimized.

Conclusion

It is clear that cultural, process and technology change is required if police forces are to deliver both sustainable efficiencies and high quality services. In an environment where for the first time forces face real cash deficits and face having to reduce police officer and support staff numbers whilst maintaining current performance levels the current finance delivery models requires new thinking.

While there a number of barriers to be overcome in achieving a best in class finance function, it won’t be long before such a decision becomes mandatory. Those who are ahead of the curve will inevitably find themselves in a stronger position.

There is an excessive amount of traffic coming from your Region.

#EANF#

Social Structure And Network (A Mathematical Model For Social Behaviour)

Analogy and metaphor are often used by social scientists to explain a social phenomenon because certain social concepts are otherwise very difficult to comprehend. For example, a physical structure like ‘building’ or a biological structure like ‘organism’ is compared to define the concept ‘social structure’. Actually, social structure is not a physical structure. An abstract concept which can’t be seen is explained in a simplified way by using an analogy which can be seen easily by everyone. Physical scientists use a model to test the predictions. If the predictions are correct when the model is tested every time then the model constructed is perfect. Otherwise, the model is suitably modified and then the predictions are tested again. This process is continued until the model becomes perfect. Do we have a grand model of social structure that can be used to test social predictions? In this article, an attempt is made to understand how far network theory is useful in explaining social structure and whether social predictions can be made using the network.Radcliffe-Brown was one of the earliest to recognise that the analysis of social structure would ultimately take a mathematical form. Radcliffe-Brown defines social structure as a ‘set of actually existing relations at a given moment of time, which link together certain human beings’. According to Oxford dictionary, ‘relations’ means the way in which two persons, groups, or countries behave towards each other or deal with each other. The phrase, ‘link together certain human beings’ can be compared with a ‘net work’ of connections.Network is defined as a closely connected group of people who exchange information. Each point (person or agent) in the network is called a ‘node’ and the link between two nodes is connected by a line called an ‘edge’. When two nodes have a direct social relation then they are connected with an edge. So when a node is connected with all possible nodes with which the node has social relations, it produces a graph. The resulting graph is a social network. The number of edges in a network is given by a formula nc2, where ‘n’ is the number of nodes. For example, if there are 3 people in a party then the number of handshakes will be 3. If there are 4 people then the number of handshakes will be 6. If there are 5 people then it will be 10. If there are 10 people then the number of handshakes will be 45. If there are 1000 people then the number of handshakes will be 499,500. When the number of people has increased 100 folds from 10 to 1000, the number of handshakes has increased 10,000 folds. So the number of relationships increases significantly as ‘n’ increases. The network theory was developed by the Hungarian mathematicians, Paul Erdos and Alfred Renyi, in the mid twentieth-century. Networks of nodes that can be in a state of 0 or 1 are called Boolean networks. It was invented by the mathematician George Boole. In Boolean networks, the 0 or 1 state of the nodes is determined by a set of rules.If two nodes are connected then the network of the two nodes assumes four states (00, 01, 10, and 11). The number of states of network grows exponentially as the number of nodes increases which is obtained by a formula 2n, where ‘n’ is the number of nodes. When n is greater than 100, it is quite difficult to explore all the possible states of the network even for the world’s fastest computer. In a Boolean network we can fix the number of states as 0 and 1. In a Boolean network, if there are three nodes A, B, and C which are connected directly by edges then the state of C can be determined by fixing the states of A and B. It means the state of C depends upon the states of A and B in some combination. Further it implies that if we know the state of C then we will know the combinational behaviour of A and B. But in a social network of persons, we do not know how a person’s behaviour is deterministic. Further, in a Boolean network, the behaviour of the nodes can be studied in controlled experiments as nodes here are objects. But in a social network, nodes which are individual persons can’t be treated as objects. In a social network how do we define the states of a person? How many states does a person have? What is the nature of a state? If the expected behaviour of a person is reduced to two states like ‘yes’ or ‘no’, then the number of states of a network will be 2n. Out of this, only one state will show up at a given moment of time. How do we predict that one particular state?Family is a micro network within the network. The family members are closely connected with each other. Most of the members are also connected to other networks external to the family. Interactions take place within the family among the members who also have interactions outside the family. So there are several edges proceed from one node of a family towards nodes within the family and nodes outside the family. The edges within a family show intimate relationship, whereas the edges connecting nodes outside the family do not necessarily show intimate relationship. This intimate relationship is a very important assumption that we have to consider so as to reduce the number of states of the social network. For example, the likelihood of a family member to conform to the family norms will be higher. Similarly, the likelihood of a person to side with a close friend will be higher. Also, the likelihood of a member of a particular group to conform to group norms will be higher. These assumptions are necessary to measure the probability of how the whole network behaves in a certain way.Interaction takes place along the nodes. The connection of one node to the other is either direct or indirect. For example, a person’s friend is connected to the person directly; the person’s friend’s friend is connected to the person indirectly, separated by one friend or technically by one degree. Research (Stanley Milgram, 1967) shows that every person in the world is separated only by six degrees to any other person. This implies that every person is connected directly or indirectly with other persons in the network except for an isolated community whose members do not have any contact with outside world. The six degrees of separation is only an approximation. For example, if you know the targeted person then the degrees of separation is zero. If your friend knows the targeted person then the degrees of separation is one and so on. Milgram’s conclusion was if you have selected a person to be targeted at random, then the maximum degrees of separation would have been six. However, the number of degrees of separation depends upon the number of critical nodes in the network in question. We will discuss about critical nodes later. So, connectivity is more or less a social reality. The question is whether this connectivity can be used as a tool to study social phenomena? If the answer is affirmative, then where can we apply this tool?If we analyse social structure in terms of a network system, then it may be useful to understand the nature of ‘dynamism’. The state of a system at the current moment is a function of the state of the system at the previous moment and some change between the two moments. Therefore, ‘a set of actually existing relations at a given moment’ depends upon the actually existed relations at the previous moment. It implies the importance of time interval, whatever the interval may be. That means if we want to know why a particular type of social structure prevails over a society at a given point in time, then we should necessarily bring ‘historical perspective’ to the study. Change is an important ingredient of dynamic system. A change at the micro level sometimes doesn’t affect the system. But, in other occasions the system becomes chaotic. It depends upon the nature of change in time and space. What is to be noted here is, a person’s behaviour is shaped by the person’s past experiences and the present situation.Moreover, a person in a social network is connected to different smaller networks which are dispersed widely. After all, a social network is networks within networks. But we should note that the system behaves differently with respect to a particular behaviour of different persons; it depends upon who the person is and how the person is placed in the hierarchy of the network. The network landscape is not even; it contains persons with different status and position. A person moves vertically and horizontally as well as deletes and adds connections. This brings change frequently at the micro level of the network. A person who is in power can easily influence others to follow an idea which need not be correct and a person who is not in power may not be able to influence others though the idea may be correct and good for the society. An idea doesn’t arise in a vacuum; it comes from the mind of a person. Even if an idea is correct, sometimes our society takes a lot of time to accept it. For example, it took a lot of time for our people to accept the fact that the earth is revolving around the sun and not the other way.In a social network, (1) each node is unique as two individuals can’t be treated as two similar objects; (2) a node may have a large number of edges connected to it directly or indirectly though it may not influence the behaviour of other nodes; (3) a node may not have a large number of edges connected to it directly or indirectly, yet it may influence the behaviour of other nodes in its network; (4) a node may have both larger connectivity and the power of influence over other nodes. So it is necessary that each node is to be studied and graded according to its connectivity and power of influence. Once this is done, we will be able to predict, to some extent, how a particular network would behave. A critical node is a node that has a larger connectivity as well as the power of influence. Why people took a lot of time to accept that the earth is revolving around the sun and not the other way: It was because the critical nodes might not have been immediately ready to accept the fact for certain reasons; secondly, each node is required to be connected with at least one critical node in order to get influenced quickly; finally, a node was in confusion because it might have been connected to two critical nodes which had opposite views.Though network is a good analogy to explain the concept of social structure, it has certain limitations: (1) The states of a network increases exponentially as the number of nodes increases; (2) The number of states of each node and its dependency on other nodes can’t be fixed as it can be done in Boolean network; (3) The number of edges (social relationships) increases as the number of nodes increases by a formula nc2; (4) Edges do not have uniform relationship; (5) Each node is unique and continues to change; (6) Information of opposing values continues to flow in the edges on both directions.Though the number of relationships increases significantly as the number of nodes increases in a social network, it does not increase the complexity of the network. Society has certain norms. People are expected to follow these norms. These norms regulate the behaviour of people. Social regulations tend to reduce the noise in the network.Though the behaviour of a node in the social network is difficult to determine, we can measure it by applying the theory of probability. For example, a family may hold a particular value. As the family is a closely knit group, all the members are expected to hold the same value. If we attribute a colour to this particular value, then the nodes of the family network will have the same colour and will look distinct. When the information pertaining to this value flows out from the family network to other networks through the edges, the information will have this colour. Therefore, the other nodes which receive and value this information will be influenced by this colour. Similarly, the nodes of a family will also be influenced by other colours as different information flow into the family network. The colour of a node depends upon how strong the node holds a particular value. Suppose, a certain node is surrounded by several nodes of a distinct colour, then the probability that this particular node will have a strong influence of that particular colour is higher. This is what happens when a person joins a group; the person will be strongly influenced by the values of that group. And when this person interacts with other nodes, those group values are transmitted. Therefore, if we know (a) the network of a particular node, (b) the colour of other nodes in the network, and (c) the colours of the critical nodes in the network, then we will be able to determine the probable behaviour of the particular node by giving weighted measure to each node of the network according to its location, distance, and colour. Though the nodes in a social network are not objects, the nodes can be studied objectively in this manner with a probabilistic determination.Suppose a node is a drug addict and living in the neighbourhood of other nodes who are drug users and sellers, then we have reasons to believe that the node’s addiction is due to its location and easy availability. But we can’t attribute the same reason to a node’s addiction to drugs if the node doesn’t live in the neighbourhood of drug users and sellers. The circumstances under which the two nodes have got addicted to drugs would be different. There may be many causes for a node to become a drug addict. However, network analysis with probabilistic determination will be useful to find out the significant cause. In the former case, the node should be treated leniently because the probability to become a drug addict is higher due to its location and easy availability. The node is prone to be a victim of circumstances. The circumstances could be due to retreatism, a concept developed by the sociologist Robert Merton (1968).According to Merton, retreatism is a response to inability to succeed; it is the rejection of both cultural goals and means, so that, in effect, one drops out. The sale of illegal drugs itself is another kind of deviant behaviour which Merton defined as innovation. Innovation involves accepting the cultural goals but rejecting conventional means. This excessive deviance results from particular social arrangements. Whereas in the latter case, the node’s probability to get addicted to drugs is lower and the circumstances are not obvious. It could be a personal choice or the drug sellers’ spread to new locations. If it was a personal choice, then in addition to social arrangements, biological and psychological factors would also be considered to find the causes. In this case, the node’s deviant behaviour needs a different treatment.The above example illustrates how a social phenomenon can be studied using a network analysis with probabilistic determination. The probability of a node’s behaviour will guide us to make social predictions such as how a particular neighbourhood will behave in a certain situation at a given moment of time. One problem which would arise in this model is how the nodes are coloured. Suitable research method is to be employed to arrive at the probable nature of a node. The probable nature of a node depends upon the probable nature of other nodes in the network. The researcher should proceed from the established and known nature of certain nodes. For example if a group’s values are overtly known to everyone then the group will be coloured accordingly. However, the researcher should note that if the nodes are wrongly coloured, the measures will be wrong and so our predictions.Another problem is the dynamic nature of the system. The behaviour of a node is constantly changing. However, the change in a particular node does not bring about a change in the system immediately in most of the cases. The change in the system is felt only after reaching a tipping point. Social change does not take place every second. After all, a period of 1,000 years is just a blink of an eye in the biological evolutionary time scale. Hence, social predictions can be made at a given moment of time. A third problem is, there can be individual differences within a family or group. This fact is to be considered in the research method before colouring a node.To sum up, we are living in this information society with lots of complex problems. This is not surprising because it is natural and an outcome of evolutionary process. Many problems do not have a single cause. Taking a decision looking at one cause of a complex problem will lead us to face another problem in different form. We will have to look at all causes simultaneously to see how the riddle unfolds itself. It implies there are many solutions for a complex problem. Probabilistic determination might give us the best possible solution.
jackpotslotsweb.infospinslotwins.infoslotbidwins.infofantasyslots.infobestslotmachine.infocasinoslotonline.infojackpotslotwins.infojasabacklinkpro.infojasabacklinks.infoseosites.infolinkseo.infoslotmachinetips.infoslotmachinestrategies.infoslotmachineodds.infoprogressiveslotwins.infojyufnehnd.inforqqbgnd.infohhxyygznd.infolrhvand.infoylcalnd.infouqlnhnd.inforesrhnd.infopsdrvnd.infopabrsnd.infomtayand.infolirensmnd.infokekepnd.infohgnffnd.infokratombz.infomenody.infoauryadbe.infosongmide.infolandecz.infoeventvde.infoitrolde.infoorgivde.infofestbg.infoyzkstcom.infogdzbzcom.infoneuqncom.infoozmuzcom.infofudggcom.infoqzykwcom.infolyympcom.infodnenycom.infohqaaecom.infogpzslcom.infoaaehlcom.infobxtjzcom.infontpocom.infoeppomcom.infoemaeocom.infofbsvncom.infoezamzcom.infofghoacom.infodzypjcom.infodsfdbcom.infoebifmcom.infoisurinet.infonusuonet.infobceluk.infosnjabcom.infoOlgato.infomsmmycom.infoomdircom.infoVilato.infoegoltcom.inforrdeocom.infoAllyto.infomcsdpcom.infoweigbcom.infobwmovcom.infoqyhlnet.inforedcanet.infoimwapnet.infowbtgwcom.infosoyhocom.infomxjxlcom.infogmlatcom.infoldstxcom.infoxjwxxcom.infogpabocom.inforeofkcom.infozayhdcom.infosxbbdcom.infoszyeqcom.infoycjyccom.infocccfhcom.infoSweeto.infonzeamcom.infomycsdnet.infoTraxto.infovvhento.infopnfzwcom.infoyygjbcom.infosrywjcom.infonxtypcom.infoshrjdnet.infozaylccom.infoxjnspcom.infohznjqcom.infoqpcswnet.infotwtmtcom.infomdouwcom.infoielpzcom.infofjpancom.infoabdezcom.infoMoonug.infozgnavcom.infoplknycom.infoasbtlcom.infokumchnet.infonioomcom.infoigutrcom.infomepncom.infostixto.infobbponcom.infodrupccom.infozujarnet.infootocscom.infohrpubnet.infosabpccom.infontfckcom.infoMinito.infoagpclcom.infoapkpzcom.infoLunarto.infolielnet.infoblunxcom.infouekkocom.infovwgemcom.infosvelto.infosbicbcom.infobdysmcom.infoealelcom.infoqdonynet.infofcsadnet.infochnrxcom.infojomopcom.infozbmhwcom.infoaqdficom.infohfzeucom.inforjjilcom.infoocszzcom.infotauhpcom.infoehbnecom.infoememenet.infootrocom.infongoiccom.infosekuycom.infoceolucom.infocdklkcom.infoehwelcom.infobassjcom.infourlrlcom.infopppwccom.infoydavscom.infouandunet.infoqhtcmcom.inforghdccom.infoptcsdcom.infozgggbnet.infobmkfycom.infoldickcom.infocwkshcom.infoyxjkdcom.infozmgmbcom.infomqegocom.infoszytgnet.infomkoorcom.infoiutahnet.infoditflcom.infocolqrcom.infosjboxnet.infogxcxwcom.infohyhajcom.infoiharzcom.infojcacscom.infomilicnet.infomsmmocom.infoiktvscom.infodixlecom.infoymfabcom.infolfpetnet.infomedphnet.infonabxnet.infocxfzcom.infoazttscom.infosjielcom.infofkxlbcom.infomuzoknet.infogjainnet.infosorkinet.infopugrccom.infoSacAdnet.infoylnzhcom.infolggokcom.infoticeonet.infovvhatto.info