Business Intelligence (difficulty of implementation)
Despite obvious advantages of BI systems to the large organizations, many heads avoid their implementation. However, those who decide to optimize a company performance thus face some problems. Ignorance of these problems often comes to an end with a large number of laborious work, high costs for maintenance of a system and lack of notable advantage. In article the main difficulties which the organizations making the decision on implementation of BI systems meet are listed and explained.
Inconvenience of the solution for users
Implementation of a new information system quite often causes discontent of a number of employees shown for the following reasons:
- complexity in mastering;
- data view in new, not corresponding usual a type;
- insufficient data-refresh rate;
- lack of own criterion of classification in a new system.
In this case, the solution is cooperation of users with technology experts and also confidence of the implementing party that data are collected in the necessary and convenient type for users. Also the IT service needs to be convinced that if necessary the user can go deep into data and find the answer to any question.
The problems caused by synchronization of data
Having hostless system of data processing, many staff of the organization in the purposes makes forecasts and considers options of events, substituting in own information tables predicted, the untrue values. Certainly, these changes are not applied at delivery of reports and the analysis of real, current situations. At implementation of a BI system such changes are immediately made to the general database owing to what sotrudnikamiya can be taken for reliable by others.
Problems of quality of data
The Business Intelligence system should be based on absolutely exact, reliable, complete and up-to-date data, otherwise it becomes the next obstacle which needs to be overcome (or to ignore), to accept good business solution.
This problem cannot be solved once and for all, behind quality of postupayemy information constant control is necessary.
Revaluation of product capabilities
Management of the organization often believes that expensive acquisition of a BI system will bring the results comparable to costs for its acquisition and support. This right waiting, however some heads are inclined to consider that such investment will solve all existing problems in analytics of activity of the company and other spheres.
It is necessary to understand that even ideally implemented BI system will be capable to execute only the functions put in it. Objective comparison of functionality of the BI solution planned to acquisition to corporate needs and expectationses can be the solution of this problem.
Lack of the precise plan of implementation of a BI product
Often a BI system appears in the organization for the purpose of the solution of any specific objective. Then, with growth of production capacities, the scope of BI extends and covers more and more processes in the company. It makes sense to consider rates of organization development and to extend influence of a BI system in proportion to them, otherwise emergence of essential spaces in automation of activity of the company on which liquidation a lot of time and means will leave is possible. Untimely approach will not allow the implemented BI solution to pay off and become the full-fledged tool in hands of staff of the company.
It is also necessary to provide uniformity of BI products in all company in order to avoid excess efforts for the solution of the same tasks on different platforms.
Involvement of the outsourcing companies
The decision on return of a part of functional cares on outsourcing — in general right strategy to which many heads adhere. At such approach it is necessary to remember that the third-party companies cannot trust profile and tactical aspects of organization activity. A BI system belongs to tactical tools therefore to give its implementation and development of the third-party company — means to give the strategy on outsourcing.
Gartner: Why many projects of a business intelligence fail
In March, 2020 the Gartner analytical company published some results of a research in which it told about the reasons of a failure of many projects in the field of a business intelligence (BI) and also gave several advice to heads, responsible for these implementations.
According to the CRN edition in number of March 5, 2020, technology of a business intelligence and management of Big Data remain the sphere of growth for the partner channel as clients need software solutions, services and experience for implementation and use of smart technologies for business better to understand the customers and to improve the operational indicators. But BI projects often fail, and that is why, according to Gartner:
- Producers aim to sell highly specialized solutions in the field of analytics that leads to the fragmented, niche implementation projects using only tactical opportunities instead of development of optimal strategy with a wide scope.
- Internet of Things requires other knowledge and skills, than traditional projects of a business intelligence. Without having plans of set of specialists in Internet of Things, the organizations will not be able successfully to use IoT-data and to create intelligent devices of the next generation.
- Some companies try to change technology for training, providing "simple in use" and "intuitive" tools of the business analysis to the business users that they could analyze data, will not bring desirable business results.
- The increasing value purchases management of analytics, but it cannot be performed in a separation from data management.
Gartner makes several recommendations to the IT heads and managers responsible for implementation of BI projects. First, analysts to direct to training in implementation of tools of analytics and analytical processes to understanding of when and why they will be used, but not on how to use specific tools.
Also experts consider it necessary to estimate already available applications of data processing, analytics and business processes — it is possible, they turn on enough means of machine learning for the scenarios of use planned by you.
One more council — to think over probable scenarios of use Internet of Things in the companies and relevant requirements to analytics in interaction with business strategists and architects of corporate applications. Most often a problem will be to understand how to provide processing of stream data from sensors, but also more difficult scenarios are possible that will demand embedding of analytical technology directly in devices on IoT border.
Besides, in Gartner recommend to expand data management, having included in it management of analytics. It is not necessary to build management of analytics as independent process. Make a priority the approved business result for a specific business case or the business purpose.
According to forecasts of Gartner, by 2022 technologies of expanded analytics will be widespread everywhere, however only 10% of analysts will involve all their potential. By this time 40% of projects of development and assessment of models of machine learning will be performed in products in which a main objective is not machine learning.
Also analysts expect that by 2023 90% among 500 world's largest companies will integrate management of analytics in wider initiatives of data management and analytics, and to the 2025th about 80% of the consumer and industrial goods containing electronics will execute analytical processes directly on the device.[1]
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Notes
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