This is our blog about designing and implementing Intelligent organizations. Within this area of expertise we write often about the following subjects BI, analytics, the tools, decision management, data visualization, BI success, Business Intelligence concepts, data management, continuous improvement, and the organization of BI & Analytics.
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Companies and organizations that need temporary extra capacity or expertise can go to Passionned Group from the start of 2015 for quality specialists and interim managers who will optimally fit in the organization. The interim managers are among the best in their field and are ingrained in the Passionned DNA: they are enthusiastic, knowledgeable and results-oriented. The interim managers shall ensure that the changes are accepted by the organization, and that they thereby become entrenched.
Martijn Stuiver (40) has been the Director of Continuous Improvement at Passionned Group since the beginning of this year. Martijn is an expert in the field of change and behavior and will help customers of Passionned improve themselves continuously and learn how to be innovative. “Change is difficult,” says Martijn, “but if the objective of the change coincides with the goal of the team, the work becomes more fun and the team members end up producing better results.”
Passionned Group is about to enter a new phase in which interim assignments are going to occupy an increasingly important role to help and retain clients. Changing market trends play an important role in this.
He or she should be a driven professional with his/her own sales responsibility. Your primary objective will be to generate revenue by placing interim managers and specialists with customers. This means that you will know better than anyone else how to position Passionned Group well with prospects (new business). You should be a fully-fledged (substantive) discussion partner for clients and are perfectly able to comprehend issues and hiring needs, and you should be able to translate these things into concrete assignments.
Dividing the organization up into effectors can increase the speed at which the organization responds and adapts. Effectors are flexible, autonomous and market-oriented teams that act as a unit. In their purest form such effectors can be seen as small organizations within the large organization, often responsible for one or more processes. However, they frequently use the organization’s common infrastructure and its standards and values. These people are very motivated and collaborative.
The first five of the fifteen process steps of the Business Analytics cycle are usually fully executed by computers. This paragraph takes a closer look at the various processors – the most important stakeholders of Business Analytics – that play a role in the last ten process steps.
Figure: a variety of processors within an organization process information and knowledge and keep the organization on track.
The adaptive capacity of an organization depends largely upon how well the organization processes information. It is therefore important that the handling process– the second process of the large Business Intelligence cycle – is well designed and supported within the organization. We define a number of steps within this process. These are shown in following figure.
Figure: The BI cycle consists of 15 process steps where data is converted to information and knowledge.
Fast as lighting, when we consume (new) information we will run through existing structures and connections in our minds so that new knowledge and information can be connected to what we already know. We are, as it were, trying to fit this new information into our brain, which either happens comparatively easily or with some considerable amount of effort.
During the internalization process, people should ideally be aware of which fixed beliefs and assumptions they, unknowingly or in fact knowingly, use. Unfortunately, various studies show that we tend to see what we want to see and that our brain is extremely lazy and prejudiced. “We like to think that our judgements, beliefs and opinions are based on solid reasoning. But we may have to think again.”
If you want actionable management information, you need genuine KPIs. To ensure that users understand the information as quickly as possible and that they can define actions, the Intelligent Organization will have to take into account a number of generic requirements (see below) that should be imposed on management information and key performance indicators:
Keep the number of indicators manageable. Not too many, not too few. A rule of thumb here is: it’s better to have set of four meaningful KPIs than to have forty indicators showing arbitrary information. Initially, managers as well as employees seem to need a lot of information to be able to steer well. Research has shown that managers who are capable of scanning a wide range of information perform better. Question is, though: does this mean they also need a wide range of indicators?
On this website, we have examined the second basic process of the major Business Intelligence cycle: the handling process. In fifteen steps we described the process of transforming data into information and knowledge that instigate action. The fifteen steps together in fact form the minor Business Intelligence cycle. The indicators and their context, which have been identified earlier, are used as a guideline for these steps. Next, we described the most important target groups (the processors) and usage roles within the Intelligent Organization and we concluded this article with the requirements we should place on the handling process.
Driving a car is in a way quite similar to steering an organization: when you know how fast you drive (an indicator) you in fact know nothing (yet). You want to know when you will arrive at your destination; you will want to know whether you are driving in the right direction; you want to know if there is enough gas left, and so on. Steering an organization well is therefore only possible when the organization meets the conditions for effective management:
Everything in the digital economy is concerned with data. Businesses that are becoming increasingly smarter, collect and analyze data in a structured way, so they can make high quality, fact-based decisions fast. The increasing importance and use of data has led to new developments that are going to have a big impact on Business Intelligence. In practical terms, the Passionned Group predicts the following six Business Intelligence trends for 2015.
The data-driven approach either relies on the data that originate from the information systems that support business operations or goes in search for available external sources that can fulfill the information needs. This approach operates as follows:
Inventory of resources: the organization makes an inventory of applications and information systems that register and administer the organization’s data. These may include an ERP system, a tool for financial administration, the CRM system, a complaint system or a combination of those. If relevant, and not to forget affordable, the organization might also look for external data such as market information (supplied by a market research agency), demographic data, Land Registry (Cadastre), the patent register, a registry of brand names, weather forecasts, press bureaus such as AP and Reuter, data from CPB (Economic Policy Analysis) or the Chamber of commerce and finally websites of competitors.
Through carefully examining the business processes, the horizontal business-driven approach offers insight into the added value of an organization and on how we can measure the performance of activities. The business processes are an important point of action for defining the information needs and for improving the organization’s performance. Practical experience also shows this: business processes form a significant point of engagement for the mapping of information needs. In this way, we obtain the ‘certainty’ that the information we need is actually relevant for the people that are part of these processes or who are responsible for them. “Every company on earth consists of processes. Processes are what companies do.”(Hammer, 1995).
When following the vertical business driven approach, the mission, strategies and goals of an organization are leading (top-down). This approach is based on the fact that the most elementary information needs and KPIs come to surface – and can actually be defined – when we take a few steps down and ‘descend’ to the operational level of the business processes:
the mission of an organization translates into one or more strategies that in turn can be translated into short term and long-term goals (see figure below). A mission statement normally does not change over the years because it describes the primary function and added value of the organization in general terms. The mission does not specify ‘how’ but it answers the question “Why do we exist and for whom?” The strategy specifies how an organization wants to achieve its mission and the goal indicates more specifically, what an organization wishes to achieve. When a certain goal is achieved, an organization can employ other strategies to keep on pursuing its mission. It is thus a cycle of strategy and pursuing goals that maintain the mission: every goal reached becomes a means to setting new goals and achieving a higher level of ambition.
Traditional organizations make decisions occasionally, intelligent organizations make decisions constantly and at all levels, even beyond the boundaries of the organization. It is therefore quite conceivable that professional Business Intelligence – using innovative IT – could halve the response time of organizations, thereby enhancing the adaptability by a factor of two.
The adaptability of an organization is, among others things, a direct result of how quickly the organization responds to changing market conditions (Liautaud and Hammond, 2001), for example aggressive competitors entering the market or the industry regulator tightening or loosening certain rules. We examine the boundaries of the Intelligent Organization from three different perspectives that harmonize with the three stages of the Intelligent Organization:
What we see in practice is that successful organizations do not normally develop the sensors, processors and effectors simultaneously but often progress in a logical sequence. In most cases, attention is given first to developing and improving sensitivity, for example by defining relevant KPIs. The actual development and usage of processors and effectors follows later. These organizations realize that wanting everything at once, is the same as wanting and ending up with nothing. The three stages and the four ambition levels of Business Intelligence are closely related. This is depicted in the following figure.
A higher level of maturity requires a well thought out and integral form of Business Intelligence. After all, maturity level 2 already requires data integration from various sources – different tasks and processes now need to be aligned. To be able to perform tasks better, we frequently need data from parallel processes. The next two levels of maturity, ‘improving’ and ‘innovating’, demand that internal and external data, such as information about the market or about technological developments, merge.
Consequently, the market expands, offering organizations opportunities to widen their sales territory and market share without losing sight of specific customer needs. The ultimate marketing goal is thorough customer segmentation, preferably in such a way that each customer represents one segment and that they are approachable as an individual, as a person (Peppers and Rogers, 1996). That is not an easy task in this era of increasing individualization and the ever-expanding population.
In recent years, Business Intelligence and Analytics has become more relevant and as a result gained a much larger audience. In the past managers formed the main audience but nowadays we see that many Business Intelligence applications are also being created for knowledge workers. There are two reasons for this change: firstly, the booming information democracy and secondly, the fact that knowledge workers, to an ever greater extent, are urged to make independent decisions and solve problems quickly. In this article, we examine the benefits of Business Intelligence for managers and knowledge workers from various angles.
Business Intelligence offers organizations numerous opportunities but not until we begin to measure the critical factors for achieving greater performance. The act of measuring at all already improves the situation, assuming that the correct aspects are being measured. In response managers tend to work harder and that has little to do with the actual information.
For that reason measuring alone is not sufficient in the long term. The measurement and control system should integrate thoroughly with the organization and employees will need to understand the philosophy – enhancing performance through actively using and applying information – behind it.
Major accounting scandals around the turn of the last century have led governments and shareholders to want to be able to appraise organizations better. The recently increased focus on corporate governance and on information exchange between shareholders and organization executives illustrates this. Shareholders – and governments – presently demand that organizations be transparent.
Stakeholders simply do not settle for financial numbers alone. Decision-making based on such figures alone provides a distorted picture of what is actually happening within an organization (De Waal, 2002). To quote Burton G. Malkiel: “A firm’s income statement may be likened to a bikini – what it reveals is interesting, but what it conceals is vital”.
Nowadays, consumers want to consume and experience instantly. The fact that mobile phones, which combine numerous functions, have really taken off is illustrative. Another example is the ready-made meal. Modern people want convenience. “We see that everything, from textile to weapons, from houses to meals, becomes more complex: more difficult to make but easier to use” (Csikszentmihalyi, 2003). The Experience Economy emerges alongside.
In our present society and economy, change has become a constant factor. Everything changes and few things are predictable. The only certainty we have is the knowledge that uncertainty is an increasingly important phenomenon. Company executives need to realize that in these uncertain times and environments, managing an organization necessitates different ways of thinking, doing business, organizing, informing and reporting.
Some essential social and economic developments accentuate the necessity to stimulate intelligent behavior within organizations and more specifically, within enterprises (Schnabel, 2000):
informalization (hierarchies and boundaries are fading);
information technology and computerization;
internationalization, globalization and liberalization;
intensification of the increasing influence and market dynamics.
Decisions need to be informed and accurate in order to run an organization well. The main advantage of Analytics – besides many other benefits which we will discuss here – is that the people within an organization are able to make better decisions faster, both at the level of the knowledge worker and at the level of the Board of Directors. Using effective BI / Analytics the organization is not only guided by the management, but also – and increasingly so – by knowledge workers and operators and in many cases, directly by customers and suppliers.
Business Intelligence has much in common with a number of other sciences and knowledge areas that, in order for BI / Analytics to reach its full growth, must work together very well (see figure below):
This ensures that an organization carries out its (strategic) activities according to a certain plan. Business Intelligence shows organizations whether that plan also works (out) in practice. The feedback that Business Intelligence provides with regard to the business operations may encourage the strategic managers, as you will see in the first chapter of our book ‘The Intelligent organization’.
Business Intelligence is not a project or a series of processes that we execute just once. Instead, Business Intelligence is a repetitive cycle of processes. The figure below shows that this cycle consists of three basic processes: the major BI cycle. In turn, the processing process of the major BI cycle is subdivided into a sub cycle of collecting, analyzing and distributing (C-A-D). This is the so-called minor BI cycle.
Organizations, from small business to multinationals, as well as foundations, governments and NPOs need reliable and relevant management information in order to perform well. Without this information, organizations lose track of both the internal course of events and external developments. They lose direction (or become unbalanced) and waste time and money either because they do the wrong things or because they fail to do what is right.
De Woonplaats, a real estate company, created from a merger of 7 housing associations in the East of the Netherlands, can be characterized as an innovative real estate company with strong ambitions, which operates in a dynamic market. The transition from a more task-oriented to a fully process-oriented organization has been put in motion.
The objectives here are to achieve a ‘smarter organization’ with ‘lean’ processes and more direction in business operations. It also necessary to anticipate and take into account the expectation that government, at a national and European level, will be taking (more) measures in the coming years that may have financial consequences.
It sometime seems that Business Analytics is the only game left in town. The familiar term ‘business intelligence’ or BI seems to have been changed everywhere with ‘search and replace’ into ‘business analytics’. The Silver Bullet that puts an end to all problems. If only life were that simple.
From thorough and extensive Passionned Group research, it seems that successfully applied Business Intelligence has a number of interconnected critical success factors. These can be placed in the higher organizational concepts; All-round vision, Agility, Alignment and – indeed – Analytics.
The difference between what ETL suppliers think on the one hand and users want on the other hand, seems to get bigger every year. It starts with the name. Users still talk about ETL (Extract, Transform and Load); while suppliers think it is passé. They talk about data integration and master data management, something that is wider than the original ETL, but describes the same problem.
If we assume that Google statistics give an indication of what people are interested in, we see that globally 240,000 people per month (in the Netherlands: 2400) search for “ETL”. The search term “data integration” is “only” entered by 74,000 people (in the Netherlands: 720). On the first Google page of “data integration”, we find almost exclusively supplier information. The first “ETL” page contains a lot of (neutral) information on the subject itself and is almost free of suppliers. Good positioning of the products remains a problem, as is clear from the above example.
The question that we are being increasingly asked lately is, ‘Could the credit crisis and its consequences have been avoided with an intelligent organization?’ In this article, we explore where and how the credit crisis began, its effects and the characteristics of an intelligent organization that should have been able to play a role in that. Finally, we give a number of options on how you can reduce the current consequences with concepts from the intelligent organization and can even exploit opportunities. Even if you have no business intelligence (BI) system.
The title may cause you to raise your eyebrows. organizations that are intelligent? Do they exist? Moreover, what is the point of an organization being very smart?
The answer is simple: intelligent organizations perform better across the board. They make more profit, have more satisfied customers, manage their workload better and innovate more successfully. This is apparent from a large-scale Passionned Group study of nearly three hundred and sixty-six companies with more than two hundred and fifty employees.
Data warehouses typically contain quite a lot of content. Let us assume, for convenience sake, that much of this content is relevant and reliable. This is often not (yet) the case, but fine, we want to address another issue here, namely that the user cannot find information even though it is available in the right quality.
I myself have once examined what the reason for this could be and have compiled a preliminary list:
Recently I was invited to a management team (MT) meeting of a financial services company. They asked me to lay down a clear vision about a specific Business Intelligence issue. In addition to the CEO and several managers, the CFO of the company was also present. He bemoaned the fact that the figures from the data warehouse never corresponded to those in his accounting system. He wanted one version of the truth, which is a praiseworthy thing in itself.