Overview
Planning makes every effort to foresee and speculate planned developments in the organization’s process goals and compositions. Maintaining the aforementioned closed-loop managing cycle from reporting and evaluating process results to foresight and preparation for accustoming the operative processes is a fundamental role of Business Intelligence.
The Basics
As volumes and types of business data grow within the organization, it is progressively essential to provide users right through the organization with fast and stress-free access to accurate information. Self-service BI is no longer a nice-to-have, but rather a requirement in today’s highly competitive business environment. The ages of too much dependence on solely traditional BI devices that are just accessed by a diminutive set of power users are things of the past. Bringing BI to an enterprise level is a tool required for each user in the organization. Perceptions of the past guide organization to the idea that detailed business analysis using corporate data is complex and time-consuming. This is also outdated.
The basic management definition is to plot, direct and oversee an organization’s operation. Projecting and overseeing this operation depend on the evaluation of the previous results of operating processes. Mainstream organizations worldwide recognize the fact that they should empower and embolden their decision-makers to base their judgments more on specifics than on instinctive feelings and knowledge. Obtaining fresh gains and insights from data is an important competency in a digital transformation. Although the challenges and requirements have increased significantly as of late along with the needs of agility, big data, cloud computing, digitalization, and speed.
Data Support Analysis
Globally, challenges and progressions push a number of key trends related to software and technology usage for BI and data administration and to the manner by which BI is organized. At this time, there are four user topics that BI specialists find to the very important trends in their field of work, namely, data visualization and discovery, predictive analytics, self-service BI, and the integration of BI and performance management in one common platform. Subsequently, there are also several data management trends like the use of analytical databases or data quality management that are gaining prominence in providing the architectural and technical foundation for the above-mentioned BI trends.
Business intelligence consists of a number of methods and strategies designed to advance business processes, such as:
Data integration
Data integration involves data consolidation, data mining, data storage, and warehousing. This includes collecting data from a number of structured and unstructured resources and consolidating it into a single source that could be applied to produce important data by using the organization’s business intelligence tools. Presentation of data empowers users to ask for data sources and discover utilizable information that could be evaluated against business objectives while guaranteeing security and data authenticity in a collaborative workplace.
Data Presentation
This involves information discovery, analysis, collaboration, and visibility.
Reporting
This involves the use of tools and other devices used to compare data through many business processes. Tools such as scorecard reporting empower knowledgeable employees to assess information and act on it, thus making a foundation of expertise for the organization.
All of these strategies conform to an important stage of business performance. These methods, when used all together generate feedback loops of growing knowledge that could ultimately improve the organization and its business processes and associated information over time.
A holistic approach to supporting decision making
Applying holistic BI to decision-making will enable IT to get involved more intently with business users to understand and prototype business decisions. A harmonized central master data delivers one, common data basis for BI and planning on top of other supplementary performing management processes such as financial consolidation, risk management, etc. It is a reality in most companies that an integrated BI and planning are a regularly proclaimed, however rarely accomplished objective. Reasons for these are internal policies, problems with traditionally grown system environments, and maybe also with the extremely limited number of integrated software systems available on the market. Organizations using integrated software systems for BI, and planning go through fewer hitches than organizations that adopt BI and planning independently with separate tools. Therefore, attentiveness to integrated BI and planning is especially important for organizations when choosing software products.
Decisions are borne on many points – operationally, purposefully, and strategically – and consist of past data (say in reporting), about the procedures, presently running (activity monitoring) but also gradually more concerning the future, which is forecasting, planning, and predictive analytics. Decisions must also be in-line with the organization’s vision and strategic policies on top of the goals and targets of the individuals and each department.
Planning makes every effort to foresee and speculate planned developments in the organization’s process goals and compositions. Planning and controlling an organization’s operation depends on the evaluation of the past results of these processes and selected results are usually reported as soon as the processes have completed execution, normally in daily, weekly, or monthly sequences, and added up to key performance indicators for more evaluation. Maintaining the aforementioned closed-loop managing cycle from reporting and evaluating process results to foresight and preparation for accustoming the operative processes is a fundamental job for Business Intelligence.
Business intelligence platforms have been used for tactical or strategic decision-making. The increasing necessity for quicker decision-making up to real-time has additional importance in guiding an organization’s performance, adding up data on current process operation to the views on the past, in analysis and reporting, and on future planning. Facilitating a quicker reaction to the present developments by monitoring the quality, time, or cost of processes is the ultimate aim of operative decision-making.
BI Trends
A good number of organizations worldwide have accepted the fact that they have to enable and embolden their decision-makers to base their judgments further on facts than on instincts and experience. Possessing the appropriate comprehension, processes, and technology primed to support this would not merely enable them to improve in managing performance but then also generate opportunities to create fully fresh insights and benefits from data, a strategic competency in digital transformation. In trying to achieve this, however, the challenges have not diminished in recent years, these are;
1. Agility
Organizations should need to acclimate quicker to the ever-changing customer and market deportment increasingly pushed by rapid-transforming digital, information-driven processes. The exigency for flexibility and speed in adapting to new developments and requirements led to a rapidly increasing need for data discovery and self-service business intelligence in the hands of users and the ushering in of year-in-year-out rolling of plans and forecasting cycles.
2. Big data inundations
The use of continuously rising volumes of data that is coming in varied configurations from increasingly internal and external resources led to the introduction of fresh technology similar to Hadoop, producing more heterogeneous IT architectures although it also creates skills gaps in the organizations, both technically and the side of the business.
3. Digital transformation
As organizations were confronted with the need to transmute to digital business models centered on data and software, organizations have to understand the challenges of innovation from data in improving their operating advantage or changes to their business models. The primary objective of digital transformation for most of the organization is to turn into a data-driven business through the value chain, generally from assets digitalization such as IoT (Internet of Things) combined with service-oriented business models and the business networks digitalization (suppliers) with automated decision prototypes centered on appliance erudition, through to completely digitalized sales, distribution, and billing or money collection practices for data products.
Cloud computing
Cloud computing technology has long been a controversial talk about a topic, principally with respect to data confidentiality and protection, which used to be the principal concerns preventing the shift from developing into the mainstream. Given that most organization is contingent on technology in some or all respects, the exigence curve for tech experience is continuously a vertical, endless climb. In spite of increased training opportunities for everyone pursuing a career as a system professional or software programmer, there is still a shortage of applicants to fill up the thousands of job openings.
In spite of it, we now see cloud computing being adopted and reconnoitered by many organizations. The benefits that it can do are just now too hard to ignore such as the immediate availability of BI and planning services (time-to-value), abridged local IT participation in BI (for example, no installation/hardware required) in addition to scalability, and the obvious flexibility. Moreover, security is regularly now appreciated as somewhat that a qualified provider can better provide than the normally limited in-house IT resources. These worldwide advancements and challenges propel a number of significant developments associated with the management of software and technologies in favor of BI and data administration and the method BI is being structured.
To gain a better understanding of the professed importance of today’s BI technology, BARC conducted a worldwide survey of almost 2,800 BI specialists asking them how important the present BI trends are for the organization they work for. The 2016 BI Trend Monitor also gives an all-inclusive representation of regional, company, and industry-specific dissimilarities, providing an informed view of the BI market. The significance of this trend evaluation is reinforced by the actuality that the trends are hierarchical and centered on the judgment of a considerable number of specialists worldwide as an alternative to the opinion of a single analyst company or software seller. A discovery/visualization, predictive analytics, self-service BI, and the integration of BI and performance administration in a single shared platform are presently significant BI user issues that BI specialists recognize as the top pertinent trends in their field of work. Also, participants have specified the number of key data management trends such as data quality management or the usage of analytical databases that deliver the architectural and technical foundation for the above-mentioned BI trends.
Functionality integration for BI and performance management
These aforementioned trends have a key influence on integrated BI and planning, hence also driving the demand for easy-to-use, visual, innovative software products encompassing BI and performance administration.
Self-service BI and planning
This has been the organization’s long-standing wish list and still remains to be a high primacy in relation to satisfying the demand from business users for agility and flexibility. Many organizations are assessing software products through a specialized focus on the simplicity of use and quick results for business users while IT strives to fulfill the demand. Demand such as from departmental users for the provisioning of self-service competencies and for data to be accessible anytime, anywhere, and on every device is putting too much pressure on BI and IT organizations. As a result, there is a rising demand among enterprises to empower users into building or design their own custom reports, data/planning prototypes, planning forms, interfaces, logic, or inquiries. Hitting a clear-cut balance between agility and data governance is an extremely important factor in the realization of self-service BI undertakings. It is (data governance) essential for data-driven companies that are extending self-service BI and planning.
Functionality for business users who want to use a self-service approach typically affects two specialty areas, namely, data discovery and visualization and predictive analytics. The evolution of visualizations and visual navigation in data to support a data discovery process is one of the most important trends in the market, especially for business users. Many organizations have recognized that data-driven decision-making, as opposed to relying on instinct, has to turn out to be more important since decisions should progressively be deemed all-important impelling factors in a logical, inclusive, and proactive means. Interactive methods and new visualization types that could be used up and expended in a self-service approach are necessary to enable decision makers to view instantaneously, the most important trends, along with spotting outliers.
Additionally,
there is now a thrust for better simplification and visually enticing
interaction and navigation in data, which is highly graphical, yet fairly straightforward
user interfaces to burrow deep into data, drag-and-drop functionality,
responsive charts, and visuals. As an ensuing trend, there is a growing need
for ‘visual design standards’, a run-through presentation of pertinent
information in a manner that it could be understood in an effectual and in a most efficient way (this is via the deployment of a common ‘visual language’,
usually called notation guideline, with formatting rules and design standards).
Hence, as an important precondition in many organizations, visual design
standards must be supported by the latest BI and planning software products,
meaning supporting the IBCS (International Business Communication Standards)
for the conceptual, perceptual, and semantic design of intelligible BI and
planning results.
Forward-looking data analysis and predictive planning hold huge potential to tap more benefits from investments in data and software systems. Predicting the future as precisely as possible is an aspiration for all organizations to align processes and resources proactively. Many organizations make every effort to use modern-day software technology to make predictions centered on historical data and analyze complicated business relationships. Forward-looking data analysis and predictive planning use mathematical and statistical formulas and algorithms in order to create fresh information, and pinpoint patterns, and dependencies, besides calculating forecasts.
Integrating BI and planning in one shared software platform
The integration of Business Intelligence and Planning in one shared platform as an essential element to optimally support the management cycle is acknowledged by users across all industries, organizations, sizes, or geographies. It (the integration) has remained stable and for years still relevant in many organizations, particularly best-in-class companies in BI and planning. The sustained success when integrating BI and planning is the unwavering support of professional software solutions.
Integrated databases for actuals and plan data exemplified in a consistent data model form the rock-hard basis for integrated software solutions avoiding the time-consuming and data error-prone data transfer processes between software systems. The harmonized central master data gives a single, shared data basis for BI and planning, in addition to other additional performance management processes particularly financial consolidation, risk management, and many more. Based on this scenario, a consistent data model has to be established that openly supports enterprise modeling - in addition to departmental - data views complemented by flexible time horizons for the short-operational term, mid-tactical term, and long strategic term considerations.
In achieving a fully integrated user experience, both BI functionality and high-level planning and forecasting functionality must be available in an integrated BI and planning program. Key deliverance capabilities to web-based and cloud-ready should involve the following;
● BI core functionality – for example, cyclic standardized reporting, IT-defined dashboards, or a traditional OLAP analysis.
● Advanced Business Intelligence functionality mainly matching to the trends mentioned in the previous section (for example, predictive analysis, and support for big data).
● Support functionality for top-down and bottom-up, centralization and decentralization, including financial and operational planning processes.
● A mixture of easy-to-use and self-service functionality for business users with as many possibilities to govern data and functionality.
The best-in-class benefits of Business Intelligence and planning.
Business intelligence and planning support on an integrated data program and with an integrated tool or application is a goal too appealing to invest in. A lack of coherent data and functionality resulting from the utilization of multiple tools for BI and planning and utilizing Excel instead of specialized software tools for BI and planning, are often cited as reasons for user discontent, discrepancies, or error vulnerability with BI and planning in organizations today.
Integrating BI and planning in a single, shared software program is a way of circumventing difficulties and user discontent in BI and planning processes. Best-in-class organizations, in particular, acknowledged this fundamental relationship and as a result, frequently opt for professionally integrated software platforms for BI and planning. Organizations utilizing integrated BI and planning experience three times fewer problems than organizations that do not.
Attentiveness to the integration of BI and planning is particularly important for organizations in the selection of software products. If products are not thoroughly evaluated in this regard, key problems might occur all the way down the line when using the solution. Resulting to;
● Speed and latency deficiency due to latency between the formation of data and data analytics along with the need to integrate actuals and plan data before being able to carry out planning, reporting, and data analysis tasks.
● Different user interfaces and experiences for BI and planning led to a dropped in productivity, user contentment, and more effort in training and supporting users.
● Problems in data quality, leading to inconsistencies, in trying to connect data and data structures for actuals and plan data kept in different applications and databases.
● Increased work in data transfer processes management between BI and planning environments.
● Add-on IT costs in the operation of several software systems, dealing with user problems, maintaining security, server environments, updating methods, and many more.
● Other additional licensing costs for different BI and planning environments.
Conclusion
Integrating
BI and planning in a common software program and approach shows important
benefits and is a method of bypassing problems and user discontent. The utilization of software solutions professionally is a pivotal element for continued success
when incorporating BI and planning. Hence, the integration of BI and planning
is an indispensable requirement for modern management support. Therefore, when
a decision comes to selecting software products for the organization, paying
solid attention to the features pointed out in this article takes note of
support for the full management cycle.
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References:
IBM | What is business
intelligence?
BARC | The benefits of an integrated
approach to business intelligence & planning
Optimus SBR | Business Intelligence Road Map to Smarter Decisions