Decision Support System(DSS) and Executive Information System (EIS)

Key Takeaways

okay so let's go back to our discussion on the computer based information system and which is TPS Mis and in this topic we will be discussing now you upper uh or higher level of information system which is the decision support system and executive information system before we uh discuss DSS Eis let us have a recap and of what we have tackled in the past meeting as you can see from the from the image [Music] here types of information system system and also we could uh depict from the from the image it illustrates how different uh types of information systems are utilized by different levels of management in an organization so as you can see in the operational level transaction processing system okay so at the operational level day to-day transactions that are carried out and common workers or most most of the employees who are uh performing daily [Music] transactions and then we have the second type of information system which is you mis where we in Mel managers then we have the DSs which is being used by senior managers for those who have tactical uh level roles and then lastly at the top we have the executive information system Executives who are concerned with long term planning and decision making for the entire organization so Eis or ESS provide top level management with Comprehensive view of the organization's position Trend and external environments and with this various uh types of information system being used in each uh level of management level of decisions so we have here strategic decisions tactical decisions and operational decisions types of information system will support them in their decision making based on the level of decisions that this specific individuals teams or groups are going to use so we can classify your decisions in three categories based on their level of management or based on the level at which they occur so we have your strategic decisions so decisions and is ENT organization in the long run because whatever decisions consider strategic can shape the company's Direction and future durations are long-term in nature and can affect the company for several years strategic uh decision set the course of an organization and then we have here the Tactical decisions so normally tactical uh ations are [Music] being done by various managers decision makers top managementor Executives CEO board of directors so tactical decisions these are more specific than strategic decisions that are often a followup to strategic Direction so this decision supports strategic decisions although significant impact but it is generally within a particular department or unit or group duration are medium-term decisions so on tactical manager decisions are decisions about how things will get done and this is typically uh being carried out by individuals responsible planning directing overseeing the work of a certain uh work of a group of individuals or specific department and then finally we have here now the operational decisions refers to decisions that employees make each day to make the organization run decisions that are narrow in scope and affecting day-to-day operations so immediate impact but are often uh reversible or modifiable so normally duration operational decisions are shortterm because they are uh routine and often repetitive so they are typically based on established guidelines procedures or data so we have there an examples so typical decision makers employees throughout organization so every individual in the company regardless of rank makes operational decisions related to their specific role or Tas okay so again that uh different information systems are used at each level of the company structure to support the different decision types and discuss okay another uh diagram before we discuss [Music] DSS because this will serve as foundation for us to better understand uh components system higher systems such as DSS and [Music] P so from the diagram represent different levels of decision making within the organization along with the characteristic of the decisions at each level examples the types of decisions typically made so on the left side we have here the three common decision characteristics so we have here unstructured semi structured and structured let's start with structured these are decisions as you can see video examples these are decisions that are routine and repetitive where established procedures can be applied so yeah type of [Music] decisions operational management and individual employees and teams so this level is closest to the day-to-day operations of the organization the thiss here are more routine and operational so system PPS and then we have here [Music] the example also of structured decisions inside the organization task that includes determining overtime restocking inventory offering credit to customers and determining special offers and then semi structured these are decisions that are in between unstructured and structured they involve some level of routine or set procedures but also require some level of judgment or evaluation and uh I characteristic decisions mostly I result judgment evaluation M management so these managers operates cooperates below Senior Management and oversee the work of lower managers so decisions are often tactical relating to implementing the strategies set by the top management or M leaders and then we have here unstructured decisions that are non routine and required subjective judgment due to unpr unpredictability and lack of clear procedures type of decisions management so their decisions tends to be more strategic impacting the entire organization and the determining it overall direction examp such as deciding the entrance or exit from markets approving Capital budgets and setting long-term goals so from this summary in illustrate hierarchy of decision making in organizations starting from strategic decisions made by the Senior Management down to operational decisions made by the lower managers and teams and also decisions uh decision characteristics show the nature of decisions at each level okay so mostly TPS structured decisions Mis DSS at Eis for example Mis semi structured and [Music] DSs would somehow fall on unstructured okay so for more uh for a better understanding let's proceed to the next slide which [Music] is okay so types of decisions expound definitions and explanations structured semi structured and unstructured okay so uh let start with unstructured unstructured these decisions are complex and nonroutine they are they usually arise in situations where there are no predefined structures or procedures to follow because it's Noel and other is unpredict unpredictability situations so uh making these decisions often involves a high degree of intuition judgment and evaluation so maybe an example management is let's say for example crisis when you're responding to uh public relation Scandal or unexpected negative media attention example mergers and acquisition when you are deciding to whether to merge with or acquire another company especially in in a new industry considered again as unstructured type of decisions because they are complex and nonroutine another example maybe you want to enter a new market so when you're evaluating the potential of new country or demographic for your business business expansion consider unstructured type of decisions okay so semi structured man these decisions fall between structured and unstructured so parang uh there might be some established procedures or criteria to consider but there's also a need for judgment interpretation and some sort of evaluation and some aspects of the decision may be routine While others require more strategic thinking example is product pricing while there might be guidelines based on the production cost and the the final price determining the final price might take into account comparator pricing also perceived value and other market dynamics [Music] another although standard hiring process organization but selecting a candidate for a newly created position might require evaluating which skills are most important okay so those are possible examples of semi structured and then we have here the structured uh decisions this routine are repetitive in nature okay decisions established procedures so they are often clearcut and involve little to no ambiguity example payroll processing ensuring employees are paid on time based on their set salaries or early rates is already you know a routine and repetive decision established procedure in processing the P another example of structured uh the station would be inventory reordering if if a stock for a particular uh product or item Falls below certain level there is an automatic ordering replenish routine maintenance machines equipment based on set time frame processing returns if a customer Returns the product within a specified return window and meets all the return criteria the return can be processed without higher level Revenue so information systems that as decisions move from structured to unstructured they tend to become less routine more complex and require more judgment and evaluation okay let's try to uh [Music] personal life all right so for example so the concept of structured semi structured and structured decisions can also be applied to our personal life let's say for [Music] example start structur [Music] decisions okay so repetive decis establish because maybe through habits or we have certain rules or criteria and outcomes of this decisions are predictable and usually uh there is little ambiguity involved let say for example a student uh routine and repetitive decisions that you make number one could be attending regular classes going to schedule classes every day submitting your assignments adhering to the dress codes attendance policies and other follow and other school rules okay so [Music] possible structured structur because they are they OCC regularly and follow a clear established procedure the parameters for making those decisions are well defined and predictability the outcomes of those decisions are typically known and and expected the sem [Music] structured decision elements of rtin but components judgment and evaluation so let's say for example whether you're going to decide to take up a part-time job while uh also having your studies balancing or managing your study habits or study time so element evaluation judgment personal preference okay and then we have here unstructured [Music] possible structur s are let's say for example deciding to move to another city or country for a new job opportunity especially if it's a place they never live in before investing in real estate so you are buying a home or property especially if it's their if if it's your first time or if you are venturing into real estate as an investment changing PA transitioning from one field of work to entirely different one [Music] so unstructured or I mean yeah yeah unstructured decisions because number one uh lack of predent these decisions often arise in situations that are Noel unique so prior experience or establish procedure basis and uh it is also un structured because of high complexity they involve multiple variables some of which may be unknown or unpredictable and of course there is a high level of sub uh subjectivity because of its novelty of its complexities so therefore these decisions will rely heavily on personal judgment inion then of course qualitative evaluation okay so I hope you were able to uh uh somehow no understand the differences between this type of decisions so we have here various uh examples and uh criteria structured semi and unstructured so we have here examples and then we have here the criteria so the first Hallmark of structured decisions is routine and repetitive nature clear procedure or set criteria for making the [Music] decision structured type of decision so yeah payroll inventory reordering routine maintenance checks approving standard purchase orders and processing returns next semistructured Advance semi structured so you can see in there we have here the following criteria the structurs have some routine elements but also require judgment due to partial ambiguity or the blending of standardized and novel element let's say for example you product pricing so although you production cost can be calculated you know determining the final price also involves market research comparator analysis and even the pive value considerations yeah so there is this balance act another hiring decisions a candidate meet all the standard qualifications but choosing between candidates might involve evaluating cultural fit potential for growth and other subjective measures okay and then we have here unstructured decision unru ured decision so this decisions CLS uh clear patterns routine or established procedures and they often arise from unique situations and require High degree of intuition and judgment so examples in our criteria let's say for example you um yeah you crisis management every crisis is unique whether it's Scandal or a natural disaster there's no one siiz fits all solution so it requires uh you know different kind of strategies from different uh crisis that the organization might uh experience strategic alliances because if you are forming a new partnership you are charting into or you are venturing into unchartered territory for your business so decisions would revolve around trust potential for Synergy and future projections which are aren't always you know clearcut okay oh yeah entering a new market without historical data or procedence in a new market decisions will be always based on Market Research potential risk and strategic alignment all of which involve a lot of unknowns okay so remember of Precedence High complexity there is a high level of subjectivity andly automate decision because it requires human expertise and judgment all right so I hope clear differences types or characteristics decision and uh from this uh types of decisions three types two uh kinds of decisions could be program and [Music] nonpr uh yeah structured decisions so program decisions [Music] because decision support systems generally involve uh nonprogram decisions so therefore there will be no exact report content or format for these systems reports reports will be generated based on the needs demands and you know uh depending on the preferences now of the uh managers program [Music] decisions and non program they are closely you know aligned with the structured semi-structured and unstructured uh decisions so program decisions these are decisions that are routine and repetitive for which established procedures or rules can be applied so they are typically made in response to well structured situations or problems okay so program decisions align directly with structured [Music] decisions and then we have here non-program decisions these decisions are made in response to Unique Noel or ill structured situations or problems they involve a higher level or of human judgment intuition and Analysis so preestablished formulas rules or procedures to Follows and this type of decisions correlates with semi structured and unstructured [Music] decisions okay so DSS decision support system which is the topic of this discussion and executive information system they will deal mostly with nonprogram decisions okay so primary support n DSS it supports nonprogram decisions they do not have predetermined reports content or formats instead they offer flexibility and customization to adapt to the unique needs of each decision okay so you topic [Music] DSS DSS are valuable tools for aiding managers in making nonprogrammed decisions by providing them uh information and analytical tools so we have here uh you can see in the diagram we have your Senior Management to are dealing with unstructured and semistructured E SS and decision support system okay so let us Define now what is DSS DSS definition Leverage is a combination of raw data documents personal knowledge and even business models to help users make decisions so data sources of the DSs could include uh data from the TPS Mis and other information system but the the the purpose of this decision support system is to really uh produce detailed information okay reports by gathering and analyzing [Music] data managers for decision making so it serves the management the operations and planning levels of an organization and helps to make decisions which may be rapidly changing and not easily specified in advance okay so [Music] yeah information but uh functionality would includes data Gathering because a DSS pulls data from variety of sources which could include databases data warehouses external data sources or even manual input and aside from that uh a DSS is also designed to analyze data so this can involve now statistical analysis forecasting optimization techniques and scenario analysis and and from other information system especially Mis that DSS often provides in an interactive interface that allows users to manipulate variables generate scenarios and view potential outcomes so uh DSS is really designed for decision making support it's about analyzing data to provide insights forecasts and scenarios to help users make inform form [Music] decisions TPS Mis so yeah compile information it also conducts analysis and modeling and users can interact with DSS adjust parameters posting what if scenarios and exploring different decision paths okay okay so let me show you a simpler diagram for us to somehow uh understand or imagine what DSS can provide to [Music] organization okay so a DSS again is a computerized tool designed to assist individuals and organizations in decision making process it aims to facilitate and enhance the quality of decisions by providing relevant information models or data analysis tools okay normally types of DSs later could be model driven data driven document driven knowledge driven later so computered tool the central component of your DSS it is the actual software or or platform that encompasses one or more of the aform mention DSS types which allows users to input data run models and retrieve also information assisting individuals and organizations in decision making so individual level a manager trying to decide say for example a business strategy or organizational level where for example a company deciding on its next big project launch so in essence DSS is versatile tool that can takes various forms based on primary function so whether you are modeling potential business outcomes analyzing vast data sets managing critical documents or providing expert advice the DSs is there to provide Clarity and enhance decision making process okay so we have here uh video an example of uh a DSS decision support [Music] system imagine a nuclear incident anywhere in the World Imagine rather than leading to Global disorder the decision support system for nuclear emergencies affecting food and agriculture better known as DSS FFA Springs to life it sets up sampling plan it navigates sampling in the field collects data from field and laboratory processes data and visualizes decision Support options and this is how it does it immediately it downloads and analyzes data on known radiation contamination rates and within minutes gives decision makers a range of precautionary options for protecting food and agriculture at the same time it computes what additional data will be needed to inform decisions that will keep the population [Music] safe it combines land use maps and crop calendars with sampling protocols for each type of crop and vegetation in potentially affected areas and by using pre-established sampling grids instantly creates detailed assignments to guide sample collection teams in the areas the geolocation of its mobile app even registers sample positions and adjusts the grid if they are taken off position and at the same time sample collectors provide additional information directly from the field via their mobile the samples are then analyzed in pre-selected Laboratories that are also linked to DSS FFA and the results of each sample are recorded directly into the system DSS for NAFA now contains all the information it needs to generate visuals easily comprehensible maps of the data superimposed over Geographic and land use Maps using Innovative computer algorithms and geovisualization platforms the information is shown without overcrowding the map even ranking according to significance decision makers can even generate interactive queries for example about the rate of contamination in space and time the continuously evolving situation is visible at a glance on tablets or screens and it scales from field level to National and international level and with all of this it requires minimal training to use it effectively and while decision makers use this information to formulate up to-the minute Guidance with regard to agricultural production or food consumption restrictions based on National regulations political specificities and actual data dss4 NAFA is already providing support on subsequent sampling assignments and continues the data acquisition process so that authorities are always presented with the latest and most upto-date decision support imagine DSF for doesn't [Music] exist imagine it [Music] does okay so uh from the decision support system for nuclear incidents affecting food and agriculture so it's a DSS for NAFA which is uh goal dssn is to provide decision makers with timely accurate and actionable information in the event of a nuclear incident that might affect food and agriculture it ensures that the potential impact on food safety agriculture production and environment is minimized and managed effectively so for managers and decision makers DSS fora offers uh following following benefits DSS which is number one rapid response informed decision making by providing a range of precautionary options based on real-time data it helps decision makers formulate strategies to protect food and agriculture data visualization syate easily comprehensible Maps superimpose over Geographic and land use maps allowing managers to quickly Gras the situation and its implication so interactive queries guidance formulation continuous uh monitoring so in Ence DSS fora it empowers managers and decision makers with the tools and information they need to respond effectively to nuclear incidents that might impact food and agre agriculture it ensures that they can make informed decisions to safeguard public health food safety and agriculture sector so components DSS okay data acquisition analysis integration with geographic information sampling GDs and assignments realtime data collection laboratory analysis integration especially data [Music] visualization so from that decision makers to provide realtime guidance on agriculture production or food consumption restrictions based on National regulations political specifities and actual data okay so uh sample DSS then we have here now the difference of uh Mis and uh DSS so purpose is designed to provide managers with routine and and structured reports based on regular periodic or predictable inputs so main goal Mis is to support and streamline the daily daily operations and management functions of an organization DSS design is specifically to assist decision maker in making complex non-routine decisions so it aids in problem solving and decision making process by providing tools for modeling analysis and what if scenarios and in terms of data processing uh Mis process data in structured and routine manner so it deals with historical data to produce uh regular reports summaries and charts the track organizational performance DSS typically handles both structured and structured data so it can analyze and process data in flexible Dynamic ways allowing for ad hoc queries simulations and forecasts and in terms of user interaction uh Mis offers limited user interaction and because uh users typically retrieve only predefined uh reports and might have some capability to customize these reports based on certain parameters but the DS as it's highly interactive allowing users to manipulate data adjust variables and explore different scenarios so it's designed to be adaptable to the unique and changing needs of individual decision makers and in terms of uh flexibility uh Mis it is generally more rigid and standardized in its functionality because it's built to handle routine Tas and produce uh consistent outputs DSS it's more flexible it's more adaptable because it is designed to accommodate a wide range of decisionmaking needs and can be tailored to specific problems or situations then lastly on the decision making level Mis primarily supports middle management it provides the information needed to Monitor and control organizational processes and ensure that they are functioning efficiently while this is on the other hand an a higher level management and decision makers to deal with more complex and strategic decisions it offers tools and models to help people with Alternatives and predict outcomes while uh both Mis and DS s are integral parts of an organization's Information Systems infrastructure Mis is more about providing routine structured information for operational efficiency whereas DSS focus on aiding complex decision making process okay so I hope it's clear so these are now the typical uh uh typical information that is being gathered by our uh DSS so our DSS gathers a wide range of information to facilitate and improve decision making process so the following are examples so various Industries and scenarios so business and Retail and we will not be discussing this individually I'm just going to show you Nang examples of information being gathered by DSS to produce uh valuable information managers to help them in their decision making is a healthare agriculture right so Finance real estate anyway you have a copy of this presentation so just go over with this uh types of information gathered by DSS all right transportation and Logistics energy Retail Finance transportation and even in the hospitality industries so optimize room rates analyze customer preferences forecast occupancy or reservation trends ensure efficient operations and improve customer satisfaction other applications could be on agriculture in medicine weather forecasting real estate and of course in in education all right environment manufacturing and [Music] also Public Safety you can see law enforcement and for emergency responses to predict crime patterns manage resource allocation during emergencies and monitor Public Safety video [Music] clip all right so other examples of D SS applications and organizations who are using that one yeah and so yeah kindly read this one okay next application DSS Human Resource Management because you are HR student so uh human resource uh professionals can use DSS in various aspects of their uh roles to enhance decision making Pro improve efficienc and support strategic planning number one Recruitment and selection okay so to analyze best amounts of resumés and applications to short least candidates based on specified criteria so speed up um recruitment process and from that you can now also predict the suitability of a candidate for a role based on historical hiring data and performance evaluations okay and uh other examples could be applied in training compensation and benefits performance appraisal and even retention strategies you can also use this for succession planning Workforce uh analytics okay so yeah let's say for example Workforce [Music] analytics mod to provide insights into your Workforce demographics skill sets and distribution so for your strategic workforce planning to make informed decisions about hiring training or word scaling and other areas in human resource management so finally read on this one okay just like what I mentioned a while back there are various types of uh decision support system so we have the communication driven model driven data driven document driven and knowledge driven DSS okay and here's a table for what it does and how it works data driven DSS it help companies save manage and analyze combination of data it's both internal to the company and and external to the company okay so heavily on large volumes of data and uses data analytics techniques to derive D Insight so primary goal is to extract patterns and transser the data to inform decisions let's say for example HR uh HR can use datadriven uh DSS to analyze employee performance metrics over time to identify top performers or to determine if there are consistent patterns in employee absences model driven DSS this systems are less data intensive and more on algorithmic because they use mathematical models and simulations to evaluate different scenarios and but to predict outcomes based on varying inputs okay example HR uh model driven DSS to forecast the impact of various compensation packages on employee retention and recruitment communication driven on the other hand uh these types of DSs emphasizes collaboration because it integrates communication tools to enable group decision making uh often in real time and across different locations SA for example in HR HR teams spread across multiple locations can use communication driven DSS to coordinate recruitment drives or standardized training sessions knowledge driven also known as expert systems so these DSS have knowledge based that they refer to when referring to Solutions and the knowledge based is continuously updated to ensure its relevance uh let's say example is customer service department AI chatbot that provides Insight answers to customer queries by referencing a vast knowledge base HR uh onboarding system that guides new employee through company procedures providing answers based on the database of a commonly asked questions from previous batches of new hires then lastly number five document driven these systems help users locate locate and retrieve uh documents they can search uh through vast amounts of of uh textual data to find specific information so h h r an example is HR staff using a document Ren system to search through the years of employee records looking for specific training certifications or past performance review so uh in summary the type of DSs uh that an organization chooses to implement is contingent upon its specific needs while uh all of this DSS aims to you know provide or Aid in decision making method and approach Based on data models communication knowledge or document [Music] Bas mod driven core types of model driven DSS okay so these are various uh software tools model driven DSS so we have Financial so focus on providing insights related to financial matters so it can offer data on cash flow internal rates of return other types of investment so decision makers evaluate finan performance and predict future Financial outcomes so software such as Excel because Excel it allows users to build Financial models conduct sensitivity analysis and forecast Financial scenarios statistical models so this model offers summary statistics Trend projections hypothesis testing and other statistical analysis so this is useful when there's a need to analyze data patterns correlations or when conducting research that requires three grow statistical evaluation so SPSS rapid minor R [Music] Studio wide range of statistical functions to analyze and interpret data effectively graphical model assist decision makers by visualizing data and information they help in designing developing and using graphical displays of data making complex information more digestible and easier to understand okay so Excel PowerPoint charts charts cutter plots Etc okay then lastly we have the project management model so this is geared toward managing large projects it helps identify and coordinate critical activities and tasks that might Poe risk to the project if not completed in a timely and cost effective manner so in planning executing monitoring and closing project [Music] so [Music] software Microsoft projects pqm for Windows and Etc so from this four models decision makers by offering data driven insights in various formats and model software will depend on the specific requirements and the nature of decisions to be made by those managers okay and then we have here now the component of DSs which is group decision support system or gdss gdss so diagam [Music] thats Focus primarily on individual decision making however uh there is so much work to be done in the organization and much of the thing accomplish are being done in groups so special category of systems called gdss group decision support system develop to support group and organizational decision [Music] making uh DSS still it's computer based [Music] system decision makers who are working together as a group so uh Target is on uh uh supporting groups in analyzing problem situations and in performing group decision uh making tasks so gdss includes tools now for brainstorming ranking ideas voting and group discussions okay so probably the difference between gdss and DSs that gdss is focused on group collaboration and decision making you DSS uh it is often oriented towards individual decision making and GDs is designed for to be used by groups teams or committees and DSs for individual managers or decision makers gdss tools and features includes uh tools for communication collaboration and consensus building while DSS emphasize data access analytical models and customizable interfaces although both of them aims to assist in decision making process but gdss focuses on collaborative decision involving multiple participants whereas DSS is more geared towards assisting individual decision makers by providing them with relevant data and analytical tools so we have here now the examples of gdss software tools electronic questionnaires electronic brainstorming the organizers and the canly read on the following softwares uh aside from the softwares there are also Alternatives organization [Music] okay to come up with organizational decision okay so we have here for you could use local area decision Network wide area decision Network decision room or teleconferencing let's start with decision uh room okay so it's a small group in a face tof face meeting face Toof face meeting support small group as you can see in the diagram okay so decision room position there is low decision on frequency but close location of group members okay so decision room is a physical specific physical space where group members convene occasionally for Focus decision making session so it must be equipped with the N technology and tools to facilitate the process an example sigur is a board of directors meeting quarterly in a conference room equipped with interactive boards and data visualization okay next is the teleconferencing yeah Act of meeting VI telephone [Music] low decision frequency low decision low decision frequency and also there is a distant distant location of group members so this is used when groups are geographically distant and don't need to make decisions frequently members communicate via video or phone calls so example is annual strategy discussions between company Executives located in different countries next is you local area decision Network characteristic is there is high decis frequency and there is close location of group members because this involves decision making system that function within a local area like a specific building or campus and uh these systems are designed for groups that make decisions frequently and those who are located relatively close to one another example is a team within the same building collaborating on a daily project using shared network and then lastly we have here the white area decision Network so there is high decision frequency and also there is a distant location of group members so system caters to groups that are geographically dispersed but needs to make decision frequently it utilizes the internet or other wide area networks to connect participants so let's say for example a multinational company with teams across collabo uh across continents will collaborate on a project using cloud-based tools through the use of video conferencing internet and whatever uh wide area decision Network work that they they they're going to employ so those are the examples or Alternatives of [Music] gdss okay so in this video we will be uh discussing executive information system executive information system call the pyramid level or type of information system so uh e or sometimes executive support system help managers with unstructured and semi structured Problems by focusing on the information needs of Senior Management so it combines data from internal and external sources so generally ESS creates a generalized Computing and Communications environment that can be focused and applied to changing array of problems so it helps senior Executives monitor organizational performance Tru activities of competitors spot problems identify opportunities and forecast Trends so by definition ESS or Eis okay it's a computer based information system designed to provide senior managers with easy access to information they consider relevant their job so uh an Eis can support uh both operational and strategic activities such as viewing Market movements analyzing sales forecasts setting policies planning and preparing bu and the main objective of this system is to gather analyze and integrate both internal and external data into a dynamic uh profiles of key performance indicators that are critical to organizational success okay and also definition [Music] all right and of course examples of intelligent information executive information system okay so uh just like what I've saidina an Eis is somehow specialized decision support system primarily used by Senior Management to a strategic decision making so oftenly intelligent information and sometimes business intelligence system or bi system because uh data from various sources and data and information for from various sources such as Number One external database so these databases provide the vast array of data from various Industries Trends and economic indicators they are a primary source of external intelligence that can influence the Strategic decision making number two your the Eis also get intelligent information from technology reports like patent records so keeping tabs on emerging Technologies as well as patent uh filings can give an organization insight into future technological Trends and potential competitor strategies okay another is you technical reports from Consultants these reports are typically specialized insights provided by industry experts or Consultants that offer detailed analysis and recommendations number four market reports this is an integral uh component for an executive because these reports shed light on market trends Market segmentations forecast and customer behaviors the Eis can also gather data from confidential information about competitors this could include insights into competitors strategies operations and potential moves so crucial too for strategic positioning and comparative advantage number six speculative information like market conditions so this might involve predictions or forecasts about potential future market conditions based on current data and Trends okay the e also uh gather information some government policies regulations and legal Landscapes can significantly affect business operations staying updated with this changes is essential for businesses to align their strategies accordingly okay then of course uh Financial reports and information uh critical to for an executive because this reports offer insights into Financial uh health profitability and operational efficiency of a company or its competitors okay so let's proceed Nam s features of uh executive information uh system number one user friendly interface so the E Systems typically have a graphical user interface that is easy to use allowing Executives to navigate and retrieve information without needing extensive technical knowledge okay and of course there must be data cons uh consolidation Eis can pull data from various sources within an organization such as Sales Inventory human resources and other uh units and present it in a summarized and Consolidated manner number three there must be a real-time access also so many Eis tools offers realtime data access ensuring that Executives have the most upto-date information when making decisions number four Trend analysis so the an Eis often includes to TOS for spotting Trends in data over time which can be crucial for strategic planning number five there must be a drill down capability also no while Eis provides summarized data it also allows users to drill down to more detailed data when needed number six customization Executives can often customize the Eis dashboards to display the specific metrics and data that are relevant to their role or current objectives then number seven uh there must also be external data integration so apart from this internal data the Eis can also integrate external data such as market trends economic indicators or competitor data to provide uh holistic view of business environments okay those are the key features of uh Eis now to give you better understanding of of of Eis I have here here an example of uh of an uh executive information system hello there all leaders make their decisions based on the information provided by their team When leaders receive the reports created by their team with great effort and time they often encounter unexpected information that was not foreseen and it becomes harder to compensate for losses and missed opportunities you can prevent the adverse effects of potential losses of decisions taken based on lack of information and missed opportunities with IPS 360 ESS the flexible business intelligence software for strategic management M IPS 360 ESS which provides flexibility as much as imagination for Strategic Management with business intelligence collects raw data from all business processes converts data into meaningful information and distributes them to strategic layers in real time thus all employees monitor the performance of their work centers in real time and the management layers Remain the only support they need for their teams this increases performance and reduces costs with effective and quick decisions with allocation of time and effort on remedial activities rather than data analysis all objectives are achieved thereby process Focus ownership productivity and profitability are increased throughout the organization while the IPS 360 ESS provides agility and decis decision making based on real-time meaningful information it also provides saving on time and cost Improvement in financial performance with increased efficiency Improvement in organizational communication encouragement towards learning and performance development and eventually competitive advantages with strong process focus and efficiency as a result success is shared within an organization where everyone is focused on improving processes thus efficiency and internal communication are improved profitability and competitiveness are increased agile decisions for Strategic Management IPS 360 ESS the flexible business intelligence software for Strategic Management www.vin.com viny plus Innovation and process access Technologies okay so that video IPS okay is an example of Eis so the IPS 360 SS is labeled as a business intelligence software for Strategic Management which is uh can be considered as primary function of an Eis okay support strategic decision making number two realtime data access one of the Hallmark of Eis is providing Executives with realtime data so the IPS 360 ESS collects and distributes data to strategic layers in real time allowing for immediate insights and decision making number three data conversion so Eis systems are known for taking raw data and converting it to meaningful actionable information and looking at the video it mentions that the software collects row data from all business processes converts data into a meaningful information which mirrors Eis functionality another video is performance monitoring the software allows all employees to monitor the performance of their work centers in real time so the Eis typically provides top Executives with Comprehensive view of organizational performance often in real time and then number [Music] five for or to enhance decision making so e IPS 360 video aim to enhance decision making by providing managers with relevant and timely information so you software in emphasize agile agile decisions for Strategic Management which is a core benefit of e another user friendly interface Al explicitly but the emphasis on realtime data access strategic ins insights and dimension of flexible business intelligence software suggest user friendly interface which is a characteristic of Eis okay and uh of course organizational benefits such as improve financial performance enhanced organizational communication and competitive Advantage so this benefits align with the typical advantages provided by uh by by an so therefore IPS 360 closely mirror Eis because it is designed to provide Executives and Strategic Management with the tools and information they need to make inform timely decisions which is the primary purpose of Eis okay right okay proed next okay let's proceed now to business uh intelligence so business intelligence is subset of Eis okay business intelligence it's set of tools Technologies and processes that helps businesses collect data analyze this data and turn it into meaningful information that can be used to make better uh decisions definition business intelligence okay it's uh sophisticated data collection technology and Analysis to bring every last drop of value from all your business processes so the purpose of this business intelligence is really to uh convert raw data into meaningful insights thereby enabling better decision making and enhancing business processes so by gathering processing analyzing data from your various sources business intelligence tools provide comprehensive view of an organization's operations market conditions and other relevant data so is to make informed decision making [Music] okay provide decision makers with accurate up to-date information ensuring that decisions are data driven and well informed okay okay so main purpose business intelligence know it's it is uh really revolving around harnessing the power of data to drive business success by how by providing a clear picture of the past and the present and offering insights into potential future scenarios so uh business intelligence empowers businesses to operate to operate uh more effectively responding to uh challenges proactively and seize opportunities decisively okay we have here the [Music] video from Hitachi Solutions okay so uh from the video explain business intelligence so it's about delivering relevant and reliable information to the right people at the right time to achieve better decision faster so on purpose is to uh collect unstructured data converts it into information and present it to improve business decision so it takes a vast amount of data generated by businesses and present it in a meaningful actionable way so complexity bi [Music] okay Performance Management analytics predictive modeling data and tex mining andot analogy to restore bi organizes business data making it accessible and easy to navigate without relying on others so from the video we can uh conclude that business intelligence refers to tools techniques that collects organize and present data in a useful and understandable manner so if an organization takes efficient access to accurate and action information on demand bi is a very valuable tool okay so we have here now specific reasons [Music] why why inv organizations in uh business intelligence number one markets okay so we because of strong competition strong business [Music] intelligence other brands who are operating in the same industry and yeah expanding Global Market with days of Global Communication shipping businesses can now cater to customers from any part of the world blooming electronic markets on the internet opportunities for outsourcing with it support and the Need For Real Time On Demand transaction because consumers today expect uh immediate responses and services pushing businesses to offer real time solution so business intelligence you would be able to cope up with this Market factors okay the same is true with consumer demands since uh modern customers wants uh products tailored to their preferences rather than generic one siiz fits all solutions by using bi you can uh customize the services okay the product that you offing to your uh uh stakeholders or customers and desire for Quality customers getting more uh powerful and less loyal so therefore you need to constantly determine preferences okay so investing in business intelligence will will help companies understand and adapt to these various market dynamics and consumer demands and bi tools can provide insights into customer Behavior market trends and operational efficiencies allowing businesses to make inform strategic decisions okay technological factors and also societal factors business intelligence to adapt with this various technological and societal [Music] factors and societal factors and and incorporating them in your business uh strategies companies can leverage you business intelligence tools to make inform decisions so these decisions are not only catered to the current market dynamics but also to ensure that the company's resilience and growth in the in the ever evolving business landscape okay and uh what's next is business analytics business analytics so it is often considered as subset of business intelligence although uh sometimes these two terms are sometimes used interchangeably they have distinct focuses and functionalities okay definition analytics refers to the skills Technologies practices and continuous iterative exploration and investigation of the past businesses performance to gain insight and drive business planning so it makes extensive use of data statistical and quantitative analysis explanatory and predictive modeling and fact-based management to drive decision making so uh business analytics emphasizes statistical analysis data mining predictive modeling and multivariate testing it's more about understanding why things happened and predicting future out comes and recommending actions compared the business intelligence focus is collection integration analysis and presentation of business information main goal is to facilitate better decision making based on past and current [Music] data business Analytics tools is St Advanced statistical methods Predictive Analytics and machine learning algorithm business intelligence focus on is data warehousing data visualization dashboarding and reporting business intelligence uh it helps organization understand what has happened and what is currently happening in their business through descriptive analytics so it provides historical View and realtime Insight but for uh business analytics it more on forward looking it helps organizations predict uh predict future events and prescribe actions to achieve desired outcomes so in summary while you business intelligence will help businesses make informed Decisions by by looking at the Historical and current data business analytics delves deeper into Data to provide insights into why certain events occurred and what might happen in the future or in the future so but uh despite these differences be business analytics and business intelligence often work hand in hand in hand with uh business analytics building a on the foundation laid by the business intelligence to offer more in-depth insights and actionable recommendations mhm where's this difference between analysis and analytics [Music] so um um analysis refers to the process of examining something in detail to understand its nature and to determine its essential features and uh it is a method of or process of uh breaking a complex topic or substance into smaller parts to gain a better understanding of it while analytics refers to the systematic computational analysis of data or statistics it involves the application of statistical mathematical and computational techniques to data in order to derive insights or predict future Trends [Music] so Bas basically F analysis on is on understanding the present state of the object system or data being examined analytics although you are going to understand the present state it places strong emphasis on predicting future outcomes or Trends Based on data although both of them involve dissecting and understanding data or [Music] information analysis is more about understanding the what and why of the situation while analytics is about using that understanding to pred what might happen in the future or to inform strategic decisions and then we have here uh scope of business analytics we have here five types uh four types rather four types of business analytics as you can see in the image it only it uh illustrates you know the different types of analytics okay so we have there descriptive analytics we have their diagnostic analytics we have their Predictive Analytics and we have also their prescriptive analytics value [Music] difficulty increase and it also increase the levels of value and the complexity okay okay it moves towards hindsight to inside to foresight and movement information to optimization okay so let's uh start with the descriptive Analytics so this type of analytics answers the question what happened it's about understanding past events and analyzing historical data to identify patterns and Trends so on the other hand we have here Nam you diagnostic analytics Dives in uh deeper into Data to understand the cost of the past events it answer the questions why did it happen then we have here Predictive Analytics anticipates uh future Trends and outcomes by analyzing current and historical data it answers the question what will happen then lastly we have here the prescriptive analytics that suggests various fors of actions to handle potential future scenarios it answers the question how can we make it happen so as you can see in the diagram as we move from descriptive to prescriptive analytics the level of complexity increases and also the potential value it can bring to an organization so the objective of business analytics is not just to understand and predict but optimize operations and make inform datadriven decisions okay so individually right we have here now descriptive uh analytics this is the initial uh phase of analytics that examines past data to understand what has happened in a business or organization it focuses on summarizing historical data to provide insights into past events and performance so characteristics it uses historical data descriptive analytics relies on historical data often collected over specified or specific Peri period to analyze and understand past events and Trends it all also offers a snapshot or overview of what has occurred in the past this involves summarizing data to identify patterns Trends and key metrics from your historical data sets and to make the information more accessible and interpretable descriptive analytics often employe data visualization techniques such as charts graphs and tables to to present the data in a visually appealing and understandable format and the main purpose of descriptive analytics is to provide a clear understanding of the past business performance and it aims to answer questions like what happened and what were the key trends and metrics in the past okay so that descriptive analytics primary goal is to accurately represent historical data in a way that can easily that can be easily understood and interpreted by stakeholders including decision makers analysts and Business Leaders okay soong descriptive analytics serves really as the foundation for more advanced forms of analytics okay so again it helps organization gain insights into their historical performance Iden ify areas for improvement and make datadriven decisions based on understanding of past events and Trends so descriptive analytics is a fundamental component of data analysis and Reporting in various Industries and sectors so basically descrip descriptive analytics can be what were our total sales last quarter how many website visitors we have last month how many units of our new product were sold in the first week after launch which department had the highest employee thir over rate last year how many customer complaints were received in the past 6 months so human resource department questions could include how many employees were hired last year what was the average employee satisfaction score in the last employee survey how many training hours were conducted for employees in the past quarter what percentage of employees utilized their full annual leave which department had the highest recruitment last month okay so basically you're answering the question what happened in the past so under the descriptive analytic analytics there are very [Music] tools could be data queries data query data query is request to retrieve specific data from a database it's a method used to filter and extract specific information based on criteria set by the user then we have descriptive statistics summary of the main aspects of your data such as mean median mode standard deviation range because they offer snapshot of the data's main characteristics example J is you you teacher might calculate the average grade of a class to determine overall performance or the highest and lowest range scores to understand the variability of student performance and data [Music] visualization represent ation such as charts scps plats to visualize data patterns tends and distributions and uh visualization helps in making the data more understandable and accessible so possible marketing team analyzing we uh your marketing team analyzing website traffic might use line chart to visualize the number of daily visitors over a month helping them spot days with unusual high or low traffic and of course dashboards so dashboards are visual tools that Aggregate and display information from various data sour okay providing uh at a glance a view of the metrics and key performance indicators so they are interactive allowing users to drill down into specific details so in essence descriptive analytics is about understanding the path and presenting data in a manner that is comprehensible and actionable so by using the tools and techniques stated here in descriptive analytics businesses can gain insights into their past performance and make informed decisions for the future okay next is the Diagnostics analytics diagnostic analytics so why did it happen why did it happen Okay so diagnostic analytic seeks to determine why something happened by examining cause effect relationship so it looks into historical data to understand the reasons and underlying factors that lead to specific outcomes or events so diagnostic analytics primarily looks at historical data and past performance to establish cause and effect relationships it aims to uncover the factors that contributed to a certain outcomes and unlike uh descriptive analytics which provides high level overview of historical data diagnostic analytic involves a deeper and a more detailed analysis of specific data sets so this is an in-depth examination which is necessary to identify the root causes of observed outcomes therefore main purpose diagnostic analytics is to understand the road causes and reasons behind past business outcomes okay so you it seeks to answer the questions like why did this happen or what factors influence this result okay so by answering that question it provides Clarity on past business behaviors and helps organizations gain insights into the relationship between various variables and events so diagnostic analytics is vulnerable for businesses and organizations seeking to improve their decision making process and learn from the past experiences so by uncovering the reasons behind historical outcomes organizations can make inform adjustments mitig risk and make strategic decisions aim at achieving better future uh results and uh it also plays a crucial uh role in root cost analysis and problem solving within various Industries so possible questions that [Music] uh you might include here is y next slide word now why okay why did our sales drops last December what factors contributed why is one product why did more employees what causes the sudden increase etc etc s HR why did we see a spike in res Nations after the last companywide meeting what factors contributed to particular team's high performance rating why did the new training program receive lower feedback scores compared to the previous one so on and so forth okay thentic analis tools root cost analysis tools you technique such as the P wise or you fishbone diagram correlation analysis okay to uh identify if there are any statistical significant relationship between variables okay sools aim to dig deeper into the data Beyond just describing it but to understand the reasons behind certain Trends or patterns okay next is the Predictive Analytics [Music] okay it employs uh statistical models and forecasting techniques to identify future Trends and events based on historical data it involves using datadriven methods to make inm predictions about what is likely to happen in the future okay so Ang Predictive Analytics relies on a variety of statistical algorithms and machine learning techniques to analyze historical data also to discover patterns and generate forecasts so this technique uh helps in identifying relationships and Trends within the data primary focus Predictive Analytics is to determine probable future outcomes or events so it doesn't provide certainties but rather probabilities based on historical data and patterns and lastly it relies heavily on the quality and relevance of historical data so if we wanted our Predictive Analytics to be accurate it depends on the quality quantity and relevance of our historical data so high quality data enhances the reliability of predictions relevant it can lead to less accurate forecast okay so purpose Predictive Analytics okay is to predict what is likely to happen in the future based on known data and ultimately uh go Predictive Analytics is to provide businesses and organizations with forecast that can help them prepare for potential future scenarios so forec will enable decision makers to anticipate and plan upcoming events allocate resources efficiently and make informed decisions okay so common questions Predictive Analytics are the following my example what will our sales look like in the next quarter based on current trends how many users are we projected to have by by the end of the year okay Human Resource Management questions US based on current patterns how many employees are we likely to hire next year what will our employee turnover rate be in the next quarter which departments are most likely to need additional stopping in the upcoming project phase given the current feedback Trends how is employee satisfaction likely to shift in the next 6 months okay so questions along Predictive Analytics and uh there are also various tools that linear regression time series analysis Data Mining and um simulation okay so we have to note that while Predictive Analytics answer the questions of what's next the question what we what should we do about it often calls under the realm of prescriptive analytics so uh or last types of or scope of business analytics you prescriptive from predictive to prescriptive analytics so it provides specific recommendations for how to handle potential future scenarios it goes beyond descriptive analytics which focuses on what has happened and Predictive Analytics which focuses on what is likely to happen by suggesting the best course of action to achieve desired outcomes descriptive and Predictive Analytics to uh [Music] understand so therefore it combines now these two forms of analysis to make inform recommendations okay and also prescriptive analytics relies on complex mathematical models optimization algorithms and simulations to evaluate multiple possible actions and their potential outcomes so it seeks the most favorable solution among various options so actionable recommendations [Music] okay predictive it offers insights and forecast predictive descriptive prescriptive provides now actionable recommendations and this recommendations guide decision makers on specific steps to take in response to different scenarios okay so in essence prescriptive analytics uh empowers decision makers with data driven recommendations to optimize their actions and make choices that align with their goals and objectives so Advanced mathematical techniques and algorithms to explore numerous decision Pathways helping organizations make decisions that can lead to favorable results and better overall [Music] performance okay so sample uh questions [Music] okay all right so always remember prescriptive analytics recommend actions based on analysis of data descriptive tells us what happened diagnostic tell us why it happened Predictive Analytics forecast what might happen prescriptive it suggest ways to handle future scenarios different tools we have optimization models simulation optimization decision uh analysis and even the use of utility jury so basically in the realm of prescriptive analytics the goal is to provide actionable recommendations [Music] okay to evaluate various uh strategies or action then select the the ones that's most likely to achieve desired outcome okay and example prescriptive analytics in HRM so are considered prescriptive analytics because they involve the use of data analytics uh techniques and modeling to offer actionable recommendations that guide organizations in making informed decisions to achieve desired HR outcomes HR prescriptive analytics to optimize HR strategies and practices for better results and outcomes okay so question are considered prescriptive analytics because they involve using data in advanced analytics uh techniques to recommend specific actions or strategies that organization should take to achieve desired HR outcomes okay recommendation of strategies optimizing HR decisions utilizing Advanced uh analytics uh technique addressing specific are challenges and of course you data driven decision making okay so [Music] right di so in summary while descriptive and diagnostic analytics focus on past data and understanding historical events you predictive and prescriptive analytics are forward looking aiming to forecast and influence future outcomes okay transition from basic reporting to a more complex decision making tools prescriptive analytics and there's a progression from information to optimization which represents a journey from understanding basic facts to making inform the for the Future Okay information it's all about collecting and storing data without uh drawing any conclusions from it optimization so it's about uh uh recommending specific actions to achieve the best possible outcomes hindsight insight and forite hindsight refers to Looking Backward and understanding the the past realm descriptive analytics Insight this uh looks into the reasons behind past events it's primarily the domain of diagnostic analytics foresight this is about uh predicting the future that calls uh Predictive Analytics and of course prescribe proper uh actions managers to improve business operations okay and also of complexity descri [Music] analyticity value it provides the foundational understanding of historical data okay so limitation descriptive analytics is backward looking and doesn't offer insights into why things happen or how to influence future outcomes and diagnostic analytics complexity is moderate value it goes beyond mere observation to provide reasons for past performance so understanding can help businesses avoid past mistakes or replicate success liation is uh focuses on past data and doesn't provide future predictions so Predictive Analytics complexity forecast future events allowing businesses to prepare and strategize accordingly okay limitation is it's still based on historical data and inherent assumptions so the accuracy of predictions can vary and unforeseen external factors can influence outcomes and then prescriptive analytics very high [Music] complexity organization because it provides questionable recommendations to achieve desired outcomes okay so this is a proactive approach that can lead to optimize decision making process maximizing benefits and minimizing RIS issue prescriptive analytics is it requires sophisticated models and algorithms and effectiveness of recommendations can still be influenced by external Factor so uh in uh in summary As you move up the the the pyramid data complexity increases requiring more sophisticated tools and uh expertise and potential value also increases as insights become more forward looking and actionable and you decision making it evolves from reactive based on the past to proactive influencing future outcomes but you have to note that each level of analytics builds upon the previous one so a solid foundation in descriptive analytics is essential before moving to diagnostic analytics to Predictive Analytics to prescriptive analytics so each level has its own value and the most effective analytic strategies often incorporate insights from all levels so what is the connection now of this business analytics to Executive information system so Eis are specialized Information Systems designed to support senior executive and decision maker in strategic decision making process connection scope business analytics [Music] so thoroughly all right but uh uh in [Music] descriptive at diagnostic analytics provides Executives with a clear understanding the past events and their causes yeah allowing for reflection and learning from historical data and you predictive prescriptive analytics Empower Executives to look forward anticipate challenges and seize opportunities guiding the organization's strategic Direction okay so executives are now equipped with a comprehensive 360 degree view of their organization enabling them to lead with confidence foresight and Agility so that's our discussion on Executive information system