Developing Enterprise System

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This document discusses the development of enterprise systems and the software solutions provided by Lawson and Birst. It explores the features and benefits of cloud solutions, artificial intelligence, and dynamic enterprise performance management. The document also covers the Hospitality Management Solution provided by Infor HMS.

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Running head: DEVELOPING ENTERPRISE SYSTEM
DEVELOPING ENTERPRISE SYSTEM
Name of the Student
Name of the Organization
Author Note

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DEVELOPING ENTERPRISE SYSTEM
The company named Lawson is mainly a software solutions company which is mainly
industry tailored and it is capable of providing a number of software solutions to all of their
respective customers.
Birst is mainly a native business intelligence or BI of the cloud as well as a platform of
business analytics which provides a lot of help to several organizations in both understanding as
well as optimizing several processes which are very much complex within a very small interval
of time as compared to some other traditional solutions of business intelligence (Howson et al.
2018). It is built with an automation which is patented and with several technologies of machine
learning. The approach of the networked business intelligence which is provided by Birst helps a
lot in connecting both teams as well as several applications across the whole enterprise through a
network of analytics which can be trusted and also through several insights for informing
decisions which will be smarter (Parenteau et al. 2016). This particular unique approach helps all
the leading companies to a great extent in improving profitability, reducing cost, increasing the
revenues as well as in transforming the way they mostly do their business. Some of the features
of this particular software solution involves networked BI, smart analytics, semantic layer which
is agile, blending of both centralized as well as de-centralized data, adaptive experience of the
user, accessibility of the information anywhere from any type of device, modern native
architecture of cloud and creation of revenue with the help of data (Sallam et al. 2014). With
about more than about 130000 total customers globally, two days or even less lead times of
delivery having about 120 suppliers, the Citrix Systems requires to aggregate data rapidly across
about a huge number of systems. This Citrix Systems has chosen Birst for digitally networking
this particular data and recently possess global as well as a visibility which is nearly real time
and this is managed by a single person of information technology.
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DEVELOPING ENTERPRISE SYSTEM
CloudSuite Distribution Enterprise is mainly a cloud solution which is both
comprehensive as well as scalable, designed for a huge and global distributers of wholesaling
who are very much focussed upon the growth, engaging the customers and also upon having
demands for several services which are extended. It is specifically a multi-sited, multi-currency
as well as a multi-language solution possessing special capabilities in encompassing each and
everything starting from the management of warehouse to all the financials, sales orders which
are multi-channelled, buying, adding values and many more (Nowak et al. 2015). This particular
solution has the capability of providing both scalability as well as flexibility for easily taking on
a number of full new markets as well as in quickly adapting for any kind of changes with an
effortless use of up to about 49 different locations and 24 languages. Some of the features of this
specific solution involves embedded analytics, altering and flow of work, search for the
enterprise, management of document and lastly the extensibility through the platform of Infor
ION. There are a number features as well as benefits which are associated with this solution.
Some of them are functionalities which are basically industry-rich, modern interface for the users
and a seamless integration (Yasin, Ben-Asher and Mendelson 2014). The functionality of the
distribution ERP meets all the requirements of several wholesale distributers for building
materials, food as well as beverage and several supplies of plumbing and HVAC. A particular
user interface which is intuitive can be personalized for fitting all the varied requirements of the
employees and helps in fostering a working environment which will be very much productive.
Coleman AI is basically an Artificial Intelligence which has the capability of maximising
the potential of human. Artificial Intelligence along with machine learning have helped a lot in
making work much smarter (Johnson et al. 2016). Infor Coleman is mainly a very powerful AI
robot which has been specially designed for several users of the business. It is particularly built
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upon a foundation of data which is mostly industry specific. At any moment which will be given,
it can help a lot with several tasks which are executing. It also helps in providing
recommendations for the next best offers of sales and also in predicting several issues reading
maintenance as well as in adjusting several schedules of production accordingly. It is known to
be named after the most inspiring mathematician as well as a physicist Katherine Coleman
Johnson, whose specific work which is trail blazing has helped NASA in landing upon the moon.
Coleman mostly represents a huge leap for AI at scale. Some of the features as well as benefits
of Coleman AI involves augmentation of work, process automation and getting advice intuitively
(Russell and Norvig 2016). As the Infor OS’s front end, several capabilities for the future will be
coming through Coleman on any device. But as the back end is concerned, a potential cognitive
system of intelligence has the capability of processing data with the help of several intelligence
tools of business which are networked, analytics as well as machine learning which helps a lot in
making better decisions. It also has the capability of instantly sourcing data, automating several
processes which are repetitive and also in optimizing the flow of works. Coleman can free up all
of the talents for focusing upon several values which are highly valued. Coleman has the ability
to learn by asking a number of questions and in narrowing several options for providing
recommendations.
Dynamic Enterprise Performance Management is mainly the measurement of the past
performance and all the activities which are forecasted with the help of an EPM software which
is dynamic. If a holistic view is taken of the performance of the business with the Infor Dynamic
Enterprise Performance Management, all the modern business tools which are intelligent are
combined with all the capabilities of financial performance management into one single solution
of EPM software (Teece 2014). D/EPM provided with the capability to consistently report with

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DEVELOPING ENTERPRISE SYSTEM
great confidence, past measurement and also recent performance and forecasting of all the
activities in the future. Both analytics in depth and business intelligence provides a view of the
performance based upon real time across the business for speeding up the making of decisions
and hence siloed data can be unlocked and information can be transformed into several sights
which are actionable. Several features as well as benefits of the D/EPM involves intelligent
management of financial performance, planning for the workforce and risk and compliance
which are holistic (Hong, Zhang and Ding 2018). There is an improvement in modelling which is
predictive and in planning of the operation as well. It also improves the budgeting of the
workforce, estimation of the sales and also provides with an improvement of the corporate
management with the help of the software of EPM. Several plans can be made for covering the
gaps and product line needs so that the headcount can be optimized for meeting all the
scheduling needs. Both continuous as well as automated monitoring can be leveraged for
streamlining all the audits which are external. The compliance cost can also be cut as well as a
holistic view of data and access of the users across several environments of business can also be
taken. Both risks of security breaches as well as non-compliance can be minimized to a great
extent.
Hospitality Management Solution is mainly provided with the Infor HMS which is a
software for the management of the property of the hotel. Infor Hospitality Management Solution
(HMS) is a particular system of hotel property management which is specially built for the cloud
with great security, mobile capabilities as well as flexibility for delivering a huge guest
experience. With the help of the property management software of HMS, employees are
provided with the access to all the information which are actionable about both prospects as well
as guests and this further allows all of them for quickly assessing each booking and for offering a
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DEVELOPING ENTERPRISE SYSTEM
rich experience (Legohérel, Fyall and Poutier 2013). Integration can be leveraged from the
management system of the property of the hotel to all the systems which are operational. The
suite of solutions of Infor also helps a lot in streamlining processes like the management of
revenue, accounting and orders of work. This particular solution provides with a number of
benefits as well as features. Some of them are cloud ensured security as well as flexibility,
tracking of the preferences of the guest for providing with a better service which is personalised
and building operations of mobile for hospitality (Wang et al. 2015). HMS is mainly a true multi-
tenant architecture of cloud which can be easily deployed on-premise in a public cloud on the
AWS or rather in private. It has the capability of offering reliability of the data centers which are
regional which are mostly managed by all the leaders of the field of the management of big data
(Smith et al. 2015). HMS can also track all the preferences of the guests and helps in
automatically matching as well as merging the data of the guest. This helps in providing a better
service to the guest.
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DEVELOPING ENTERPRISE SYSTEM
References
Hong, J., Zhang, Y. and Ding, M., 2018. Sustainable supply chain management practices, supply
chain dynamic capabilities, and enterprise performance. Journal of Cleaner
Production, 172, pp.3508-3519.
Howson, C., Sallam, R.L., Richardson, J.L., Tapadinhas, J., Idoine, C.J. and Woodward, A.,
2018. Magic quadrant for analytics and business intelligence platforms. Retrieved
Aug, 16, p.2018.
Johnson, M., Hofmann, K., Hutton, T. and Bignell, D., 2016, July. The Malmo Platform for
Artificial Intelligence Experimentation. In IJCAI (pp. 4246-4247).
Legohérel, P., Fyall, A. and Poutier, E. eds., 2013. Revenue management for hospitality and
tourism. Woodeaton: Goodfellow Publishers.
Nowak, A., Yasin, A., Mendelson, A. and Zwaenepoel, W., 2015. Establishing a base of trust
with performance counters for enterprise workloads. In 2015 {USENIX} Annual
Technical Conference ({USENIX}{ATC} 15) (pp. 541-548).
Parenteau, J., Sallam, R.L., Howson, C., Tapadinhas, J., Schlegel, K. and Oestreich, T.W., 2016.
Magic quadrant for business intelligence and analytics platforms. Recuperado de
https://www. gartner. com/doc/reprints.
Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson
Education Limited,.

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DEVELOPING ENTERPRISE SYSTEM
Sallam, R.L., Tapadinhas, J., Parenteau, J., Yuen, D. and Hostmann, B., 2014. Magic quadrant
for business intelligence and analytics platforms. Gartner RAS core research notes.
Gartner, Stamford, CT.
Smith, N.A., Sabat, I.E., Martinez, L.R., Weaver, K. and Xu, S., 2015. A convenient solution:
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Teece, D.J., 2014. The foundations of enterprise performance: Dynamic and ordinary capabilities
in an (economic) theory of firms. Academy of management perspectives, 28(4), pp.328-
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Wang, X.L., Yoonjoung Heo, C., Schwartz, Z., Legohérel, P. and Specklin, F., 2015. Revenue
management: Progress, challenges, and research prospects. Journal of Travel & Tourism
Marketing, 32(7), pp.797-811.
Yasin, A., Ben-Asher, Y. and Mendelson, A., 2014, October. Deep-dive analysis of the data
analytics workload in cloudsuite. In 2014 IEEE International Symposium on Workload
Characterization (IISWC) (pp. 202-211). IEEE.
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