Today's companies are characterized by their dynamic driving structures, where the individuals that make them up must make decisions quickly and effectively based on the latest information available, in order to maintain their competitive advantage. On the other hand, companies are accumulating large volumes of data in their operating databases at a rate that, on average, doubles every year. Still, only 7% of this data is used to gain an advantage in business decisions. Only now are organizations realizing that there is a significant amount of information that can be extracted from their databases, necessary to support the decisions that must be made by their executives, thus arriving at the concept of data warehousing..
Information is essential in the business environment in which companies move. Success depends on its prompt use in a decisive way, while a lack of information leads to certain failure. While many companies consider themselves data-packed, few own more than a small fraction of the information they need. The distinction between data and information is fundamental to the problems that companies face. Data with which the computer centers create, store and provide. Information, is the data framed in your business area, and it is the interpretation and semantics of the data, which is what companies need.
ANCIENT TIMES
Analyzing the evolution of the information systems, we see that in the beginning all the processing was carried out in the area of the computer center, and the only thing that the end user received was a thick list on continuous paper with the requested data. During the first half of the 1970s, two important technological advances occurred: the appearance of the PC, and the definition and development of relational databases.
Along with the PC, the first end-user-oriented tool appeared: the spreadsheet. With these rudimentary tools, the end user began to become independent from the computer center, taking control of their own data. These data were restricted and highly focused, but the fact of feeling independent caused a great push in the users, giving them the confidence to take advantage and continue progressing with the latest advances in technology. By the mid-1980s, it was very common to find end users with the necessary skills to work with data both technically and in the business area. All this growth was also thanks to the simplification of technology, especially in the field of personal computing.
On the other hand, database implementations that applied the relational model developed by EFCodd in 1970 also began to appear. Over time, it was found that these databases were those that provided greater flexibility, so they were quickly adopted to store the data. that the end user worked with. In many ways, this stage was an era of experimentation where end-user computing is concerned. Most of the data users had was limited in scope, and users were more interested in seeing what they could do with this data than in what other, better quality data might be available.
THE END OF DATA PROCESSING
As the end user emerged, another trend became apparent: the different ways in which data processing can be justified, and where it is benefiting the business as a whole. Over the past 30 years, most aspects of an organization's data-related operations have already been automated. These developments were always justified on the basis of lower costs. The automation of manual and mainly repetitive tasks to determine that an increase in production is obtained, while quality is improved, resulting in a decrease in costs.
With the increasing power and sophistication of computers, increasingly complex tasks can be automated, eventually implementing processes that previously would have been impossible to incorporate. In this way, functions related to the organization's clients are optimized, allowing a differentiation to be made in the services offered. As a result of this, it can be seen that the justification for the investment in computer systems went from being based on the elimination of costs, to obtaining a competitive advantage as a result of an improvement in business functions. This trend is typically described as a shift from the philosophy of data processing to the information technology strategy, driven by the business.The challenge then became the identification of areas where computing could provide support beyond simple day-to-day production processes. Already towards the middle of the 1980s, process support for decision-making became key. All this has been accompanied by a growing number of end users, which brings us to a new era in management systems.
THE INTERMEDIATE TIME
As it was still an incipient concept, there were problems in the data warehousing implementations that were being carried out: the data used in different sectors of the company did not have any integration, and the focus was on the data instead of concentrating on the function.
Therefore, a key aspect to achieve a good solution was identified: the need to adopt a common method to describe the data that was obtained from the systems in the operating environment, and which would then be transferred to the information environment. This led to the emergence of data modeling, very convenient from the point of view of systems to impose order, but even more convenient for the end user, if the defined data models are implemented within the specific area of each user.
Little by little, the organizations began to understand the importance of good data modeling, as well as a good presentation of this data to the end user.
INFORMATION SYSTEMS
The first steps to support the decision-making processes were based on the automation of traditional reporting. This immediately led to the concept of a differentiated view of business data: a first part dedicated to running the business in great detail, and a second part focused on driving the business to a more condensed level. In this way, the distinction between production systems and information systems evolved.
THE REVOLUTION OF DATA
During the first years of the 90's there was a great recession at the international level, along with the deregulation of various activities, which led to cost reductions and significant changes in organizations. This led to increased competition fiercely. Business needs changed, and managers began to stand out as they were able to see the potential of using existing data, as long as it was available on the spot, to give their company the competitive advantage that could put it ahead of the pack.
Many times there was no talk of data warehousing, but the principles applied were clearly the same. Businesses needed a new vision of their operations, a vision that previously covered different aspects of the business. Thus reaching the logical conclusion that this vision would eventually encompass the entire organization.
INFORMATION-BASED MANAGEMENT
The theoretical and practical concretion of data warehousing has been developing slowly in the last 15 years, with increasing interest in the last five. The downside to such slow growth is that there are several definitions of what is meant by talking about data warehousing.
But today you can already look ahead and predict the future based on the previously described story. The key to these predictions is the recognition that the need for competitive advantage (often an elegant term to define survival) is what is driving data-driven decision-making to base it on true information. This direction can be characterized by the term information-based management. It is transforming the way decision support is being delivered to the end user. And it can be summarized in these five points:
A single source of information: The raw data comes from different sources, both internal and external, and in a wide variety of formats. Regardless of how or where they come from, in order to present this data to the end user they have to be purified and reconciled, to ensure their quality and integrity;
Availability of the distributed information: The points from which it is possible to request the information can be of the most varied, satisfying needs for mobility, performance or confidentiality.
Information framed in the business: Users better understand the data if it is presented in the context of the business they are managing. Data dictionaries and information catalogs created by experts in the respective areas become an important source for their definition.
Automated Information Inter: As data becomes information, they are going through an increasingly complex path. The automation of these mechanisms together with those of distribution is a fundamental question.
Information quality and security: Information is the main asset of every company, and like any other asset, it must be managed and protected. Its quality must be assured. And determination is a prerequisite for reinforcing the value of it.
WHAT IS A DATA WAREHOUSE?
Based on all the history developed so far, an appropriate definition for the concept of data warehousing can be outlined:
A data warehousing is a simple, complete and consistent storage of data obtained from a variety of sources, available to the end user so that they can understand and use it in the business context.
Achieving good quality of information is quite difficult in today's companies. Modeling the company in order to make sense of the data is a very delicate and long-term process. But using the appropriate tools that meet the five points mentioned above, together with the experience of consultants specialized in the subject, a comprehensive management system can be implemented for organizations that supports decision-making processes and allows them to obtain the advantage competitive that is so much needed to stay ahead in today's difficult business world.
PRODUCTIVE SYSTEMS vs. INFORMATION SYSTEMS
The characteristics of the productive systems are:
- They keep the business running second by second; the data they contain is current, and is primarily a real-time representation of the state of the business; in these systems individual events (or transactions) are generally limited in scope, simple, and usually result in an update of the data; They are optimized to offer a fast response time in predefined transactions, focusing on the performance of those transactions that produce updates; They are used by people who work with clients or products individually; Every day they are more directly used by customers.
The characteristics of information systems are quite different:
- They are used to administer and control the company; the data is historical, at a certain point in time; that is, they represent a stable vision of the business in a period or at a particular moment in time; queries are optimized rather than updates; the use of these systems cannot be anticipated in advance and can be totally unpredictable; they are used by managers and end users to understand the business, in order to form concepts and make decisions based on this knowledge.
A Data Warehouse study begins with gathering information from the system to be analyzed, including its historical databases. The information obtained is processed in the Data Warehouse system. The results of the Data Warehouse study can be applied to the processes and productivity of the system to, for example, increase profits.
EXAMPLE: One of the largest supermarket chains in the United States commissioned a Data Warehouse study with the goal of increasing sales. For this, all the supermarket systems collected information for a month and sent it to the Data Warehouse system.
The Data Warehouse System analyzed the information and determined, among other things, that male customers bought large quantities of diapers and beer on Thursdays, probably because it was the day that their wives asked for them and they took the opportunity to buy beer to watch the weekend matches.
In the gondolas in the middle of this road they placed pacifiers, baby toys, french fries and popcorn. They also decided not to lower the prices of diapers and beer the same day.
With the information from the Data Warehouse study, the supermarket chain decided to place diapers in the gondolas on one side of the supermarket and beer on the other side, a measure that allowed them to multiply their sales on Thursdays by forty.
DATA WAREHOUSE & BUSINESS: Client Hunters
Marketing gurus are very clear:it was time to seduce the client. Enough summary information, the formula that appealed to anonymous consumers as if it were a flock of sheep willing to consume any product or service compulsively was exhausted. Retailers, banks, aviation companies, telephone companies, practically all the companies that fight for their space in hypercompetitive markets know this very well. In fact, they get exhausted trying to understand their users. But not only do they try to understand them, the idea is rather to retain them, pever their consumption habits, anticipate that demand and, of course, satisfy it before the competition. Not an easy job for stressed-out system managers who have hitherto tied with a modest proprietary database. In this sense, the exceeding instance is called the data warehouse.
According to the influential Gartner Group, the data warehouse is basically a data reservoir, which includes the design and creation of physical and logical database structures specifically oriented to facilitate access by qualified users to analysis, transformation, extraction, consolidation and improvement of the quality of these data, in order to create a source of information that simple raw data could not provide.
In other words, it is about creating and managing a data architecture that allows the user access to a strategic analysis tool. The heart of the warehouse is, without a doubt, the database. Not coincidentally, the main suppliers, Oracle, Informix, Sybase among others, are working hard to impose this new technology that is no more than ten years old. To them we must add IBM, NCR, UNISYS, on the physical supports of this technology. There are many projects under study and some fairly advanced sales efforts, but the picture is still in its infancy. Financial institutions, telephone companies, and retail are, until now, the main stakeholders, along with the government market and consumer-oriented companies.
The Data Warehouse is a process and not a product. During the last five years, a mistake made by almost all companies, especially hardware companies, was selling the data warehouse as if it were a product, when in reality the data warehouse is a process that involves several areas of a company: first place to everything that is organizational. The second area is the technology that supports this process and the third is the competitive environment in which the client company operates. Without a competitive framework, there is surely no point in talking about the data warehouse or managing the business in a certain way.
Who would have thought a few years ago to mount a data warehouse on an open system? Today an open system is the exclusive system as a platform for a data warehouse. A few years ago there was no talk of anything other than a reliable system or a proprietary system. Currently there are mass consumption companies in Argentina that do not know their profitability by product.
The data warehouse, those who have started using it, are doing it in its most primitive stage. The most typical expressions of managers are: "I have so many systems in my company, so much information, that when I want to make a report I don't know what data is valid." "I have an operating system, for transaction processing for Accounting, another for Sales, another for Cashflow, another for telephone attention, but none of them fits, because in one male and female it is like "M" and "F", and in another "V" and "M".
According to the previous statement, there is a problem that is solved with a reservoir of operational data, and that reservoir is being called the data warehouse. But, the data warehouse “is even much more, it is a process that allows us to do many more things. At the local level, what is being asked is a procedure by which you can save standard data for a specified period of time and make the information reliable. That is the primary stage. The secondary stage is being able to use that standard corporate information to make decisions.
Managers have their dilemmas. In a bank, a person stops paying their credit for a few months. You have to decide if your account is canceled, but you also evaluate if you have been a good payer for the last three years, to see if it really should be canceled. This is no longer the “ABC1” or “C3” segment, it becomes all the families of a certain age that are going to have children and move, and it is then time to offer them a mortgage loan.
It is no longer going to segment more than a standard way, but in this case, for the moment of life that a client may be going through. Marketing is going to deal with people and their lifestyle and not with a defined market segmentation.
SUPPLIERS and PROJECTS IN POSITION OF DATA WAREHOUSING
Informix bet on a specific technology for the data warehouse. In the past, there were proprietary technologies, and even today, some companies, such as IBM or NCR, that have dabbled in this information management technology continue to be semi-proprietary technologies.
The idea of Informix, for example, was to develop an open technology that runs on any platform and that enables massive data management without restrictions. Today we are seeing a corporate warehousing in which numbers and letters are handled, but let's not forget that content management is slowly coming. Today, everything that is characters is handled, but the first data warehouse is already appearing with the management of photographs, audiovisual e-mails, content information that will be modified over time. What a company like Informix is doing is trying to make this technology handle content in a massive way, in a short time, with an agile platform, and with benchmarks around twice the most popular database platforms today.
Operationally, Informix is managed with technology partners that allow you to interact through information extraction tools and data mining tools to be able to prepare reports that can predict behaviors. Process partners are consultants and implementers who are dedicated to designing the data model, preparing the organization for the use of the tool, or even putting together marketing campaigns around this.
BUSINESS INTELLIGENCE: Data warehousing and data mining techniques to improve profitability
Designed for decision-makers, business intelligence solutions provide information at the right time, in an organized, summarized and presented way that is easy to understand and take advantage of, in order to achieve faster and more effective responses. These solutions analyze and find relationships in the data, transforming it into strategic information. This results in decision making on a better basis and increases the likelihood of greater success. How these solutions can help improve business in key areas of our industry is what we will try to illustrate in an application of these characteristics on three sectors of the economic and productive area: Banks, Health Companies, and Insurers.
THE BANKS: SOLUTIONS FOR THE BANKING MARKET
The banking industry is in the midst of a transition period. Financial institutions are feeling the impact of deregulation, rapid technology changes, and increasing credit risk. Globally, banks re-evaluate their business initiatives to ensure their future competitiveness. Success or failure depends on the quality of the information on which new business initiatives are based.
The speed at which changes unfold in the financial services sector is dramatic. The world of finance is witnessing a growing number of trends that are redefining and reshaping the industry, including mergers and acquisitions, the rapid development of technology, deregulation in certain jurisdictions, and the increasing sophistication of customers..
Globalization and the partial removal of industry boundaries also resent profit margins. Non-traditional competitors are gaining ground, while banks are increasingly turning to financial investments and insurance. Today's banks are incorporating a greater variety of financial and banking activities to compete with non-financial institutions. The use of traditional bank branches is decreasing in quantity due to technological innovations.
With the large amounts of money at stake, credit card companies and lenders are increasingly under pressure to reduce credit risk and fraud as much as possible. Tomorrow's leading institutions must have sound strategies based on correct information, and you will see that they can secure a significant share of the market. This means having a detailed understanding of your customers and competitors to provide a range of products and services that meet the needs of both, and this is where a good business intelligence solution can make a difference.
With the help of tools and techniques such as data warehousing and data mining, interpreting current data can provide answers to questions that will help you be more competitive, such as:
- Who are your most profitable customers, what products do they use, and why? How risk-afraid are these segments, and why? What type of promotion can entice them to tempt you to adopt a more aggressive investment strategy? What other products and services is a customer likely to buy, considering the products they currently use? Which customers are most likely to go to another competitor? Which branches should be consolidated, or eliminated, in a particular area? How to put more evidence in the hands of branch managers so they can make better decisions?
For financial institutions to thrive in this changing environment, they must have the ability to easily access their vast data stream, and extract the information that will help them make better and more effective decisions. Such solutions also make information available to those who need it, allowing access directly from their offices or laptop computers. This information can be provided in graphic or numerical form, depending on the preferences or needs of the user.
Data mining and data warehousing are among the technologies used by large companies to gain the competitive advantage they need. Returning to the questions posed above, let's see how a financial services institution can benefit from this type of technology:
By accessing the right data, decision-making tools allow you to understand how profitable your customers really are. Consolidating data from different sources into a single repository (data warehouse) will provide you with an accurate picture of your customers.
With this information already consolidated, data mining will allow you to determine the products they are buying, and why. By later comparing other customers with this profile, you can define where to target new marketing campaigns.
- Data mining allows you to segment your customers and understand their characteristics. In addition, it will help you predict what would be the most attractive products for them. With these defined profiles, you will be able to create products that target these segments and thus offer a true alternative to the competition. The ability to monitor credits, credit cards and other credit instruments is one of the priorities of financial institutions. To remain competitive, it is essential that companies have the ability to detect potential credit abuse. By analyzing the behavior of customers who have already switched to the competition, data mining will help you apply predictive profiling to determine which customers are more. likely to leave the company.These customers can then be targeted with special promotions to increase their loyalty. A data warehouse can be used to consolidate financial and performance data of branches in a given region. Then, with this comparative information, you can decide about the elimination or merger of certain branches.
The ability to make effective decisions is governed by the quality and quantity of information that is immediately available. In short, what is the end result of business intelligence solutions?It will allow you to easily access a large amount of data that is already stored in your organization and transform this material into information on which to take a certain action. With real-time access to this information and analysis, the company's decision-making skills will not only be faster, but also more effective. Business intelligence solutions allow your company to increase the market it covers, determining what your customers buy today, and why they buy it. And it will also help you predict what products your customers will want and buy tomorrow.
HEALTH: SOLUTIONS FOR THE HEALTH AREA
The demands in today's healthcare organizations have various aspects. Pressures to reduce costs by maintaining a high level of patient care have led these organizations to reformulate their management methods. And while the consolidation of hospitals and physician groups is helping to improve productivity and costs, the task of amalgamating driving processes and consolidating patient information remains pending.
On the other hand, the communities are demanding higher quality services. Capacity limits are already being reached more frequently because life expectancy is longer thanks to advances in medical technology. All of these demands are based on one problem: the need to discover more information, be it trend analysis about the patient population, cost tracking, or payment reporting. With greater access to more valuable information, health sector personnel will be better informed, allowing them to use their equipment, buildings and staff more efficiently.
But what is the most effective way to obtain the necessary management information or historical data when and where it is needed? The answer lies in data warehousing and data mining solutions, which will allow you to answer these questions:
How to define prices correctly according to trends or patterns in diseases or symptoms?
Which procedures are more cost effective and more beneficial to patients, such as preventive treatments instead of post-disease treatments?
How does geography and age groups affect the demand for certain medical procedures?
What methods achieve the best results in patient recovery? And if there is more than one option, what is the least expensive?
Can staff assignments be improved based on a better understanding of patient profiles?
Is there a case of fraud between any particular class of provider?
How can you determine which equipment is most used by patients?
Where can an investment be made in equipment to achieve better care while lowering costs?
How effective are the recommended procedures for patients?
Business intelligence solutions will help you find answers from existing volumes of information from patient records, clinical data, and bills.
The information requirements previously outlined can be satisfied as follows:
- Combining external demographic data or national health statistics with internal data on patient treatments in a data warehouse can better understand changing trends in disease patterns across geographic regions. The result may be a better rate application policy. Data mining can be used to discover patterns and relationships between treatments, results and costs. Patterns can be detected from the patient's first visit, and thereafter. An extensive data warehouse, using high-performance databases, can provide a detailed analysis of patient treatment according to age and region. With this information it is possible to predict where the greatest demand will be for a particular medical procedure.Data mining tools should be used to determine the best and cheapest procedure for recovering a patient. By performing an analysis of the result and the protocol, you can compare various diagnostic procedures and find out which one gives the best result. And if more than one treatment is possible, it will be possible to determine which is the least expensive, helping to offer better care to more people, using decision support tools to analyze overtime records, patient demographic information, and illnesses, staff requirements can be more accurately predicted based on patient profiles. These solutions also take into account fraud problems and questionable practices. For example,By applying data mining to billing information, a departmental data warehouse can track patient utilization of equipment and determine where and when bottlenecks occur. This analysis can then be used to prepare for the regular planning of equipment and the elimination of equipment that is no longer used. Doctors will want to access their patients' information so that it can be compared with the practices of other colleagues. This information is vital as part of the professional development of each of them. And this type of information may be available to each of them through the internet directly at home, or the doctor's office.A departmental data warehouse can track patient utilization of equipment and determine where and when bottlenecks occur. This analysis can then be used to prepare for the regular planning of equipment and the elimination of equipment that is no longer used. Doctors will want to access their patients' information so that it can be compared with the practices of other colleagues. This information is vital as part of the professional development of each of them. And this type of information may be available to each of them through the internet directly at home, or the doctor's office.A departmental data warehouse can track patient utilization of equipment and determine where and when bottlenecks occur. This analysis can then be used to prepare for the regular planning of equipment and the elimination of equipment that is no longer used. Doctors will want to access their patients' information so that it can be compared with the practices of other colleagues. This information is vital as part of the professional development of each of them. And this type of information may be available to each of them through the internet directly at home, or the doctor's office.To prepare for regular equipment planning and disposal of equipment that is no longer used, clinicians will want to access their patients' information so that it can be compared with the practices of other colleagues. This information is vital as part of the professional development of each of them. And this type of information may be available to each of them through the internet directly at home, or the doctor's office.To prepare for regular equipment planning and disposal of equipment that is no longer used, clinicians will want to access their patients' information so that it can be compared with the practices of other colleagues. This information is vital as part of the professional development of each of them. And this type of information may be available to each of them through the internet directly at home, or the doctor's office.And this type of information may be available to each of them through the internet directly at home, or the doctor's office.And this type of information may be available to each of them through the internet directly at home, or the doctor's office.
INSURANCE COMPANIES: SOLUTIONS FOR THE INSURANCE AREA
Market shrinkage, lower profits, and fraudulent claims are forcing insurance companies to make some really tough decisions to stay competitive, and in some cases their survival. The quality of the information on which these decisions are made can mean the difference between success or failure.
Competition in the property insurance area is lowering premiums, resulting in a lower profit margin. According to some agencies, the short-term liquid return for property loss insurance will reach 5% in the next two years.
Some forecasts provided for 1997 a moderate profit margin for life insurers. But most of these profits will come from investments, and not from new businesses. The average insurance agent still sells only one policy per week (as has happened in the last 25 years). Although annuities and other investment-oriented insurance products are flourishing, their margins are low.
There is increasing pressure on insurance companies to provide more products and service options to an aging consumer base that has more knowledge and demands much more. Equally critical is the increase in globalization, which is limiting the profits of the insurance industry. As a result of NAFTA, the EEC and other economic unions and treaties, global competition will become increasingly intense.
But using data warehousing and data mining solutions you can find the necessary marketing solutions and business strategies in the data you already have. The following questions immediately arise when considering competitiveness in an insurance organization:
- Are different pricing systems going to translate into better market penetration? When is the right time to offer a customer a new product? How does my company compare to the competition? What is the profile of a profitable customer for a set of products? What actions does a customer take before changing carriers or no longer paying a premium? Which customers constitute a serious credit risk? How can better products be designed to attract and satisfy customers? Which products are more likely to attract fraudulent billings? How many investment funds and bonuses should an agent sell per week?
Tomorrow's leading insurers will depend on the detailed knowledge of their clients and competitors to provide products and services that ensure their competitiveness. To analyze and propose solutions, let's review the questions asked, and see how datawarehousing, data mining and decision-making tools can help solve the exposed needs:
- Using a high-performance database, data mining will help uncover patterns that provide insight into market segments and customer purchasing behaviors. Predictive models will collaborate in changing pricing policies to optimize results, based on historical information, such as the time of year, area, economic indicators, competitive behavior, promotions, offers of other products, etc., data mining It will help discover purchasing patterns around new product launches. Then using decision-making tools, you can “navigate” these patterns to obtain strategies that will effectively take advantage of consumers' buying habits, and then launch new products.Data warehousing allows the internal performance data to be combined with external information from the competition to precisely determine the effectiveness in the market. This detailed market analysis is used to allocate resources more efficiently in the most profitable areas, as well as to set other areas as the destination for new campaigns. Decision-making tools allow identifying and marking clients. Then using data mining to analyze the attributes of these clients, it is possible to determine the type of client that you want to attract and retain. Profiling a client's behavior is essential to determine which clients may be preparing to change companies. Performing sequential pattern detection over time and analyzing clients that have already changed,You can begin to recognize predictive behavior. By identifying the characteristics and behavior of past and current clients that represent high credit risk, and then applying this profile on the basis of current clients, you can detect clients who are on the same path. the possibility of fraud can be minimized. For example, with data mining you can analyze claims to find the possibility of fraud in a particular segment. Using a data warehouse, sales of funds and premiums can be accumulated by agent. Using this information, you can perform a trend analysis on earnings and compare this against the agents' output. This will give a more accurate indication of sales versus trends, and will help establish achievable quotas.
In each instance, business intelligence solutions will help convert existing data into business knowledge and experience. They also allow easier and more direct access to information, from anywhere in the world. And this information can be provided in multiple formats, depending on the needs or tastes of those who use it. All this makes decision-making processes faster and more effective, resulting in greater success and a better future for companies.
TRADE AND DISTRIBUTION: SOLUTIONS FOR TRADE AND LOGISTICS
As has never happened before, the current moment is the most competitive for the commerce and distribution sector. The need to solidify and increase the market and profits is essential to ensure its survival and growth. Store staff find a greater demand for products that are particularly suited to certain needs. In this time of massive specialization, it is essential to understand and satisfy the needs of each local market, maintaining a viable distribution network. What is needed to meet this objective is information about customer behavior and tastes, sales patterns, and even the flow of circulation within the premises.
With a strong economy, and even stronger customer confidence, the retail and distribution sector are enjoying a healthy business environment. But even when sales are at their healthiest point, there is always the threat of competition taking over the top not to mention the possibility of a weak economy holding back growth. To remain competitive and maintain profit growth, merchants need to carefully locate and examine a wide variety of business information.
This information may include inventory, market analysis, merchandise planning and administration, business performance analysis, issues related to product administration, production planning, and monitoring and promotion analysis. And this is where a good data warehousing and / or data mining solution can make a difference, by interpreting current data, giving you answers to questions that will help you be more competitive. Some formulations in this regard are:
- What products will customers want tomorrow? How is competition affecting each of the market segments? How can the spectrum of customers whom I include in mailings be improved, to target those who are more likely to buy? What affinity exists between products so that they can be used in promotions? What promotions generate the highest profit margins? What physical distribution of the premises will result in more purchases by the client in each of their tours ? Where are the imbalances in the stock, and why? Which supplier's delivery cycle coincides with the current demand? How can information be delivered to the managers of each location in real time that allows them to optimize profits?
Let's see how these requirements can be evacuated through data warehousing and data mining:
- Learning what customers will want tomorrow can be determined with data mining. By analyzing historical information such as the time of year, location, economic indicators, competitor behavior, and other promotions, patterns surrounding the launch of new products can be discovered. Working on these patterns, a profile of the types of products that customers may require in the future can be developed. Data warehousing allows the internal performance information and the external information of the competition to be brought together to precisely determine the effectiveness in the Market Data mining provides the ability to characterize consumer segments. Catalog mailings can then be designed to meet the needs of certain segments. Then,Using support tools in decision making, reports will be obtained about the results of these mailings. Ultimately, all of this will increase orders and save time and resources by ensuring that catalogs will be received by customers who are most likely to make a purchase. A data warehouse can collect and store a detail of sales transactions to allow easy access. Data mining tools can then do an analysis to determine which products were purchased together. This information is essential to plan promotions, the physical distribution of the premises, and the determination of prices. Using business intelligence solutions, you can perform analysis of profits with respect to customers' loyalty,and the movement of merchandise in each of the premises. And because these solutions allow large volumes of information to be traversed in a short time, it is possible to detect sales patterns that lead to strategic marketing decisions. Maintaining an adequate stock balance is essential for cost-effective commerce. Applying support systems for decision-making on a data warehouse that is updated daily, or even hourly, allows you to track inventory and alert when indicators indicate the point of replenishment. Then data mining will give you the ability to start predicting and projecting the necessary stock according to the performance of the points of sale. With this information it is possible to optimize the supply chain, thus achievingAlways deliver on time. Business intelligence solutions also provide the tools for trend analysis to further understand productivity, equipment usage, inventory levels, and production costs.
These solutions help the merchant increase its market share by discovering what customers are buying, and why they are buying it. And they help predict the products that customers will want tomorrow. In this way, the budget and personnel can be assigned to areas where the return on investment is greatest.
TELECOMMUNICATIONS: SOLUTIONS IN THE TELECOMMUNICATION SECTOR
Telecommunications companies around the world are facing declining market share, deregulation, and rapid technological advances. The competitiveness and ultimate survival of companies in the sector depends on their ability to make decisions quickly and in an informed way. The quality of the information on which these decisions will be based can mean the difference between success or failure.
The telecommunications industry is entering a new and challenging era. The pace of change in the telecommunications sector is so dramatic that it is often called the "new frontier." Deregulation, globalization, new technology and increased competition are the trends that are creating an atmosphere of uncertainty. Despite this, the potential to increase market share and earnings has never been greater.
But, the inevitable competition that results from these external influences is forcing telecommunications companies to closely examine their business initiatives. In other words, companies are re-examining their approach to the market, their spending, and their structures.
Furthermore, the blurring of the line between communications and the media is directly impacting prices and profits. Encouraged by this new landscape, cable and telephone companies are invading each other's markets. And both segments of the industry are now trying to intervene in the potentially profitable Internet market. There is also open competition between companies using cables, and companies using satellites.
To establish leadership as a telecommunications company, you must have detailed knowledge (not just data) of customers and competitors. Business decisions based on this knowledge will allow creating effective strategies to provide a range of products and services that meet the needs of all customers. Given that all telecommunications needs are provided by a single provider, the successful convergence of all these services may be the key to ensuring a healthy market share.
By exploiting the existing data you can find the answers to questions that lead to being more competitive in the sector:
- How are the right services offered to the right customers? How does the company compare to the wide variety of existing competitors? What are the customers reporting the highest and lowest profits, and what products are they using? What features, plans, options and combinations generate the highest profits and highest margins? How has advertising for a particular offering impacted on profits and sales? What percentages of customers own one product in combination with another? How can it be detected quickly? Fraudulent behavior among cell phone users? How can service reps provide that personal touch that improves customer satisfaction and increases customer loyalty?
Telecommunications companies have access to a rich detail of calls for each client, which has a value beyond imagining. But despite the need for high-quality, robust information, most companies are not capitalizing on this volume of data to make effective decisions. Business intelligence can help answer the above questions:
- Data mining gives you the power to characterize consumer segments by digging into the vast amount of customer information found in databases. Promotions can be designed that target specific needs of a segment. And you can use decision-making tools to report on the results of these promotions. By creating a data repository, you can gather internal and external information, in order to accurately determine the effectiveness in the market. Consolidated product sales in one place helps to better understand the distribution of profits across products, geographic regions, and the life of the customer relationship with the company. Establishing a data warehouse that collects historical marketing data and sales,Reports that compare various campaigns can be easily generated. This information can be used to determine the effectiveness of a given advertising campaign, and the impact that this effort can have on the offering of other products. Traditional decision-making support tools offer the possibility of determining the frequency of sales. of certain products combined with others, thus providing guidelines for the commercialization of them through special offers. Business intelligence also aims to minimize fraud risks, implementing a data mining analysis, on the segmented data of the customers. Keeping fraud under control keeps costs low.Also with data mining you can know the individual preferences of certain clients, so as to be able to anticipate the reactions they may have, and thus provide more personalized attention to each of them.
ENERGY COMPANIES: SOLUTIONS FOR THIS UTILITY SECTOR
Deregulation has forced utility companies to emerge from their protected industry into an open market. These companies must map out new business strategies to ensure their ability to compete within this deregulated sector. And democratization in certain parts of the world has opened global competition for energy buyers. The success of any of these new initiatives is based on the quality of the information they have, but it has to be more than business information. It has to be business intelligence.
Today, utility companies face a total transformation of their industry, which was once protected. The notion of regulated monopolies brings thoughts of bureaucracy and waste. A series of deregulatory steps are taking most utility companies from a full monopoly to a competitive market. And as countries turn to democracy, these closed markets are experiencing totally open competition from energy providers. As a result, utility companies are evolving from being engineering-led companies to marketing-oriented organizations..
As consumers become aware of these changes, they will begin to search for companies that best meet their service needs at the best available price. This creates an interesting challenge for those companies that never thought they had clients, but had service fee payers. And with the advent of the open and competitive market, there has been a growing trend to take advantage of the opportunity to acquire those profit companies that were paralyzed by the uncertainty created by deregulation.
But with the big gains this industry is enjoying right now, do they need to worry about the prospects of deregulation? The answer is simple, those companies that take a proactive position today, to meet the needs of their customers and provide exceptional service, and who in turn can react quickly to changes in the market will be the leading companies of tomorrow. And this is where business intelligence solutions can help.
Utility companies are rich in data, but poor in information, unable to answer questions that would help them be more competitive, such as:
- How to offer promotions of new products and services to those clients more apt to buy? How to determine which of the potential clients will be those that report the highest profits? How can service representatives provide a personal touch in customer service? How can fraudulent practices be identified and predicted? What information can be delivered to useful industrial customers? How does the behavior of meteorology affect variations in energy consumption, and particularly fuel consumption, in certain areas? Which customer segments are most likely to purchase warranties for your appliances, or to request periodic checks of your electrical systems?
By reviewing the approaches, some of the tools of data warehousing, data mining, and decision-making can be proposed that can help solve the exposed needs:
- The decision-making tools allow us to identify the clients that generate profits, then using data mining on this data, we can determine the type of client that is convenient to attract and retain. Being able to offer a client a differentiated service requires the Knowledge of their behavior, energy needs, and hiring patterns. Also in this area, fraud can be minimized. For example, with data mining, all invoices issued can be analyzed to detect something out of the ordinary. It can also be used to detect bad debt cancellations. Millions and millions of dollars are lost annually due to past due accounts or missed payments. Using historical data, a data warehouse can provide a consolidated view of industrial customers.Then the information that can be obtained with analysis tools can be distributed to these clients so that they adopt more efficient practices. Data mining and decision-making support, along with high-performance databases that contain detailed data on the Meteorology and energy consumption can help to develop predictive models that indicate the need to increase energy and fuels in a particular area. This information helps to regulate the production or saving of energy. Based on demographic information loaded in a data warehouse, combined with the data that the company has of its clients, it is possible to study perfectly the characteristics and behavior in their customs and purchases.With this information available, it is possible to target exactly those customers who are most likely to acquire, for example, warranties for their appliances, or verification services for their energy systems. Many energy companies have already realized that the data necessary to optimize their operations and progress in the market, they are already available in their current databases. They only need to be empowered through intelligence and business tools. The potential of the information that can be discovered using data warehousing, data mining, and decision support tools is great.All that remains is for companies from all sectors of industry and commerce to define an action plan and start using the tools that best suit their needs, together with the advice of consultants who are experts in these techniques, in order to increase your competitiveness and survive in today's business world.
JUST in TIME: "If time is money then real time is real money"
INTRODUCTION and GENERAL
The speed of business today requires that the information your company manages is independent of time and space. This is valid for both operational and strategic information: the sales force cannot wait until tomorrow to enter the orders collected today, and the decision makers cannot wait to return from their business trips to know the numbers - updated to the minute - to show them what state the company is in. As if this were not enough, the culture of telework is added, something that is giving good results in overcrowded cities around the world. The key is real-time information. The way to do this is through mobile computing technology.
Fashion and ways of carrying information have come a long way from the earliest laptops the size of a briefcase to today's palmtops, more powerful than those and the size of an electronic calendar. But evolution has not happened in one direction. On the one hand, laptops became today's notebooks: great processing power, large screens and minimal weight. This is how many desktops, with everything and their heavy monitors, had to give way to these machines capable of taking the office wherever you go. On that scale, new technology products emerged to take on the new challenges of registration and immediate information, such as PDAs or pocket computers with a pen interface, which today have reasonable amounts of memory,decent handwriting recognition, a few personal productivity apps plus communications devices and software. All this at a really low cost that makes them as accessible as an electronic agenda.
At the upper end of this segment of PDAs, it is confused with a new one, that of palmtops and handhelds, which have a small keyboard, a standard operating system (Windows CE, the most common), various applications and the possibility of exchanging Data transparently with popular PC Office packages. The evolution paid off: today, PDAs, palmtops and handhelds are part of vertical solutions, such as cases of automation of sales forces, which is why all these devices have found the desired niche.
Speaking of fast and borderless business, it is impossible not to mention business via the Internet, although many people despise it for lack of a critical mass of users locally. John Donovan, a renowned technologist and CEO of the Cambridge Techonology Group, and creator of one of the evils of our time, the mainframe, expresses that the common people wrong the way. From the beginning they despise Internet businesses for lack of a potential market. According to his theory, the first benefits of mounting the technological structure on the Internet / Intranet should not be sought in the increase in sales made through the Internet, but through the reduction of costs and the development and implementation of systems, and the competitive advantage to be able to access them from anywhere. Following this advice,It is possible to have the company's IT infrastructure (be it small, medium or large) ready for the moment when the set of local Internet users is finally large enough to start profitable businesses. At that time, the winners will be those who have tested the technology internally for a reasonable time. Once again, the key is real-time information.
In the same way that Japanese, European and North American manufacturers managed to streamline their processes and better satisfy their customers by eliminating stocks and producing just-in-time, systems can truly provide competitive advantages, avoiding tight data compartments and bringing closer and closer to the producers and consumers of the information.
The mechanisms for obtaining business information in real time are based on mobile computing technology, a product of the high degree of computational dependence that companies and professionals have reached, and the need to do at least part of the work outside from a fixed physical place. This leads to the need to have all the necessary information, adequate processing power and the possibility to connect to the company from anywhere to consult information in real time and exchange the results of tasks.
But mobile computing does not simply mean giving a notebook to each user; companies need to adapt their entire computer systems for the effective operation of the information flow in real time. There are two main areas where mobile computing is developing: automation of sales forces, and telecommuting.
"NOW AND ANYWHERE: Technology at the service of productivity"
The concept of mobile computing is to allow the user (private, professional or corporate) to maintain their degree of operation and organization when they are away from their workplace. By applying this concept in the work of professionals and companies, improvements are generated not only in productivity but also in cost reduction. Professionals in general were the first to incorporate mobile computing technology when they acquired, a few years ago, their first electronic agenda. These basic information management needs today are covered with the smallest devices such as handhelds, palmtops and PDAs.
The advantage of giving users this first approach to mobile computing is the efficient management of their agenda, telephone index and basic information for daily work, with the possibility of making queries and modifications much faster than on paper. In addition, the most advanced devices allow you to perform work in a way that would be done on a desktop computer, as well as communicate with other computers.
On the other hand, the use of notebooks by professionals has reached very high levels, to the point that many do not have a desktop computer or almost do not use it. The advantage of being able to transport all the computing power of a desktop computer and all the information that is used to work, has as a direct consequence an increase in productivity. Unlike a business desktop computer, what it takes to work is available all the time and the way one usually works.
The impact generated in the companies by the adoption of mobile computing technology by professionals generated new specific applications for corporate environments. Today, especially in our country, there are two applications of mobile computing that have had the most development: the automation of sales forces and the rationalization of workplaces. The automation of companies 'sales forces is the area of mobile computing that has developed the most in recent years due to the need to streamline this part of companies' work and the cost reduction that comes with it, which makes the payback time for such a project really short.Company sales forces are one of the areas that handle more papers and spend more money on telephone communications, with the consequent need for personnel to handle papers in general and answer the phones. The chain of forms and procedures, such as phone calls, begins precisely with sales agents who visit customers, taking note of orders and requests on forms, and transferring them to the company by telephone, voice or fax, or taking them in person or by mail.. These orders are registered again in the stock and billing system, and there begins a process that, at its own operating time, must be added the possibility that the stock of a product has been exhausted,and the customer or the seller must be called by telephone to redo that part of the operation.
A sales force equipped with a mobile computing device (handheld, palmtop, PDA or notebook) can take an order, communicate in real time with the company's stock and billing system, analyze if there is available stock to satisfy the request, and directly enter the order in seconds. In addition, this has collateral consequences such as that the customer saves the waiting time for order processing and can receive the products in less time, and the company must dedicate fewer people to the task of processing orders.
A much newer area than sales force automation is workplace rationalization. The most concrete background comes from the United States, more precisely from the state of California. There is a law in force that requires companies to have 20% of their staff work at least one day a week at home. The benefits it generated in the companies were mainly reflected in the reduction of some fixed costs. By being able to organize time, in such a way that it is known in advance that certain people will not be on certain days of the week, the number of physical jobs can be reduced with the consequent savings in electricity, telephone, supplies and general maintenance. Another additional benefit is that the employees,As managers of their time in a more personal way, they work according to objectives to be met in a certain time and not only according to time of work accomplished; This allows them to organize themselves to fulfill important tasks and not just urgent ones.
But, as always, the incorporation of a technology must be carried out by adapting the environment where it will operate, establishing clear rules and procedures for its use and training who will use it. The professional or user who is not really productive with pencil and paper will obviously not be more productive due to having a portable device. This type of technology has the mission of streamlining and enhancing people's work capacities, but not of creating them. For example, whoever does not take the trouble to put all the necessary information in their paper agenda to have a well organized day, will not do it with the best of mobile computing devices.
Something more complex happens with the automation of a sales force. It is also not enough to buy the devices, but it is necessary to have the appropriate modifications in the computer and communication systems of the company so that the sellers can consult and transfer the information efficiently. And it is also true that this will only benefit the most active sellers who are the most limited by the slowness of the system. When it comes to streamlining the workplace, it's also not about buying a notebook for each employee and sending them to work at home. The company must also adapt the company's computer and communications system so that those who work from home can submit their tasks and consult the necessary information. On the other hand,In addition to selecting the person who will become a teleworker in a part of the week for the role they perform, it should be borne in mind that those who cannot concentrate and produce at work can hardly do so at home. This implies that the person who will work as a teleworker must have a clear work discipline and probably require some specific training.
LAST CONCLUSIONS
- Undoubtedly, technological advancement and its use have collaborated enormously with the development of logistics, such as managing the flow of products and raw materials along the Supplier chain to the Customer, even going through the manufacturing stage. The performance improvements achieved so far, and planned for future years, have been helped by other fundamental factors. The effort has been interfunctional, with a joint approach to the problem and its solution as something proper by the people involved in the chain of production. The quality of the company's culture, with its emphasis on benchmarking, problem solving, and quality improvement processes, along with encouragement from the cross-functional team, provided a favorable environment for the change process.It enables people from different parts of the company to use a common language to describe, analyze and improve processes. And perhaps the most important element was the commitment to deliver benefits sooner in the implementation of the strategy through short-term change processes or optimization of the operating units. This has allowed top management not to be impatient with the pace of change. Execution is not yet complete. There are still some significant improvements to be made in the production chain processes. However, important steps have been taken in this area and with examples of companies that are leading the way in achieving these goals, but we still realize that as with most strategic objectives,we are in a race where improvements will never be final. A key point in this development path is found in transportation and distribution, where although there have been signs of improvement, there is still a long way to go in this regard.
We could fit one last reflection taken from the book "The new ignorance" by Santiago Kovadloff
«Creating is nuancing the predictable with the unpredictable. But the foreseeable is always an essential component where you really want to innovate. "
REFERENCED BIBLIOGRAPHY
- LAN & WAN - Tech Exec Section - Administration - Editorial Monthly Publication Canaima.COMPUMAGAZINE - Technology and Business - Monthly Publication Editorial MP Ediciones SABIG NETWORK COMPUTACIÓN - Computing and Business: Computing for Companies and Professionals - Monthly Publication Prince Cooke and Asoc. - Audit - Costs - Taxes - Systems - Estudio Miguel Angel Monti y Asoc. - Contadores Públicos.MARTÍN CHRISTOPHER - Logistics and Procurement - Editorial Folio SA- 1994.
