BUS30003 Project Management Plan Final Presentation

Introduction

Organizational success and sustainability are dependent on the business setting. This includes fashion. A prerequisite for everybody, it is a demanding industry that must accommodate varied dress codes. It spawned “Creative entrepreneurship,” combining creativity with business. This and the marketing plan may make or ruin a firm, particularly in this area. The fashion sector has evolved over decades. Each decade has offered new styles, clothes, and other things that have been simplified and enhanced till now. Nevertheless, future market strategy can ensure they can meet demand. However, the sector itself requires numerous tactics to ensure the growth of products within the market. Planning has no one-size-fits-all approach (Ahmed, 2018). Fashion businesses must use data analytics to survive in the present-day competitive retail environment. Nevertheless, StyleHub's analytics skills are insufficient to get significant insights through their vast consumer data. As StyleHub strives to develop into a data-driven multi-channel leader, a contemporary, cloud-based data analysis platform remains a strategic focus. This paper describes StyleHub's mid-range project management strategy for adopting a sophisticated analytics technology (Ciric et al., 2018). This plan details the 24-week implementation pathway based on the preliminary plan plus stakeholder input.

 Project de-risking and flawless execution are achieved via staged delivery deadlines, budget estimations, governance structures, and controls. The correct platform lets StyleHub use consumer data to personalize suggestions, optimize inventory, and make data-driven choices across platforms. Technology installation alone does not guarantee user acceptance or ROI; change in organizational management is essential (Hübner et al., 2022). Along with technical execution, this strategy focuses on soft components like executive alignment and training. StyleHub hopes to become an insights-driven store by systematically implementing this strategic endeavor. This strategy helps realize the idea within budget and time (Damij and Damij, 2021). It reassures stakeholders because the platform transfer will go successfully with little impact. The project aims to develop and implement a revolutionary analytics infrastructure that uses data insights to improve operations, consumer satisfaction, as well as competitiveness. Using advanced analytics, the application will give real-time insights, fully automated processes, targeted marketing, visualizing information, and predictive analysis (Emere, 2020).

Background

A rapidly evolving omni-channel apparel company with 150 locations and a successful online store, StyleHub operates nationwide. Yet, in a current competitive retail environment, a cross-channel footprint is not enough (Hübner et al., 2022). With consumers expecting customized, smooth shopping encounters, StyleHub must use its vast customer data to distinguish. StyleHub gathers massive quantities of information across various touchpoints, but its analytics are outdated and compartmentalized. The on-premise technology cannot handle huge data. Data is scattered, making comprehensive analysis difficult. Data errors exacerbate the issue. StyleHub strives to get strategic insights for involving consumers, improve inventory, as well as make data-driven choices. Style Hub prioritizes implementing a contemporary, enterprise-grade cloud-based analytics solution to transform into a data-driven omnichannel store. 

The newly developed system will centralize data and allow machine learning technologies. This will enable individualized product suggestions, localized assortment optimization, and demand-based planning of inventory (Chen et al., 2022). Simple self-service dashboards would disseminate analytics throughout the company. The leadership team supports this high-profile endeavor as a growth strategy for StyleHub. Quickness, cross-functional cooperation, managing changes, and feedback through iteration are balanced in the 24-week implementation plan. StyleHub can use statistics to delight consumers, reduce waste, and make fact-based decisions in merchandise sales, store operations, and supply chain, along with marketing utilizing the proper platform. Analysis and data collection will drive StyleHub's competitive edge (Daniel & Daniel, 2018).

Nevertheless, business intelligence began to fail over time. It was developed to handle tiny amounts of static data on older IT systems. It was also a time-consuming procedure that described historical findings without explaining their reasons or commercial prospects. Therefore, BI was developed to incorporate business analytics (BA), which is "the broad utilization of statistics, analytical and quantitative evaluation, descriptive and forecasting models, as well as fact-based administration to motivate judgments and activities." Thus, essential business data is evaluated to help companies comprehend their company and market. The emphasis shifted from "what exactly happened”, and “how often” and the question of "where towards “why”. Statistical evaluation, projections, modeling for prediction, and optimization are the analytical responsibilities these issues address. These tools provide insights into corporate procedures and techniques to help make appropriate business choices.

Scope

Targeted areas include:

• Choosing a provider of a system for analytics after doing thorough research
• Connectivity to third-party services, such as e-commerce and customer relationship management
• Construction of customized data visualization tools and analytical dashboards
• Management of transitions along with user-enablement initiatives
• Older information from the system export

Figure 01: Implementation of business analytics procedure ()

Project Details

Project Name		Project Phase	POL Number
StyleHub Analytics		Implementation Phase	ABC123
Project Manager
Project Manager Name
Approver	Name		Approval Date
Chief Data Officer	Sebastian Tran		28-8-2023
Management Officer	Emma Stiles		28-8-2023

List of Reviewers

Reviewer	Role	Endorsement Date
Myself	PM	22-8-2023

Version History

Version		Date	Comments
V0.1	1	22-8-2023	Implemented
V0.2	2	18-9-2023	Updated version of V0.1

Project Planning

Project Timetable and Delivery:

According to Nicholas (2020), the project's timeframe spans from 6 to 12 months and encompasses many significant phases, including the gathering of requirements, solution development, testing, deployment, as well as post-implementation assistance.

Stage Synopsis:

The implementation process consists of many distinct stages, including initiation, solution development, testing, installation, as well as post-implementation assistance. Each of these phases entails a specific range of operations and outcomes.

Construct Cycles:

Regular ceremonies facilitate the cultivation of collaboration and mutual comprehension by establishing a platform for transparent communication and synchronization over the duration of the project.

Complete and prepared mean:

Assurance of quality is achieved by establishing explicit criteria for readiness and completion, therefore emphasizing the project's commitment to achieving high standards.

Process of deploying:

The deployment phase includes system setup, onboarding of users, and smooth integration, all of which contribute to the transformation of strategic plans into tangible outcomes.

Governance

Strong governance procedures shall be required to supervise the analytics platform rollout and guarantee that strategic goals are met. StyleHub's structure of operations and optimal procedures for digital evolution are reflected in the governance framework. The executive advisory board will be responsible for providing strategic direction and approving the annual operating budget (Walker et al., 2022). The group will get together once a month to monitor progress and identify and eliminate any obstacles. Delegates from the corporate side, the IT side, the analytics side, and the main divisions will make up the Digital Transition Committee and act as the central legislative body. They'll get together twice a month to discuss how various departments are doing and make adjustments as necessary (Ahmed, 2018). Executive sponsorship and leadership of the committee is provided by the executive vice president of Insights.

Project Tools

R and Python are useful analytical tools. When it comes to data analytics, R and Python constitute both of the most often used languages. The... Apache Spark framework. Big data analytics, also known as large-scale data visualization, is a commonly used for Apache Spark, Apache Storm, PIG, as well as HIVE, and other data processing engines.

Impacts of applying Business analytics for StyleHub

Initiation Timeframe

A product's "time-to-market" (TTM) refers to the amount of time it takes to get from development to retail. Competitiveness in product development is the primary metric. The manufacturing industry seeks to reduce innovative product time-to-market for a variety of reasons, including a shorter product life cycle and more global competition. First, a shorter TTM extends the life of a transaction and boosts profits. By dominating the market early on, StyleHub may establish new standards, acquire a technological edge, and increase profits by charging higher prices for its products.

Open innovation may shorten the time it takes to create a new product.

Supplier and customer involvement in developing novel products has a significant effect on TTM since 80–90% of TTM is utilized during the design phase. Researchers proposed the use of open innovation in R&D as a means to this end in 2003. It proposes that businesses use both internal and external sources of inspiration and market channels to advance technological innovation. Both clients and vendors may provide input.

StyleHub may benefit from knowing customer preferences and expectations via co-creation. After all, managers think (big) data analytics might be used to learn about customers and then tailor existing offerings or develop whole new ones in response to those learnings. Co-creation among consumers allows for unrestricted feedback and defect disclosure.

Balanced supply and demand

For demand and supply to be perfectly matched, it is necessary to have accurate information about what customers want and how much of it they are willing to pay for various products and services. Researchers state that product pricing should balance manufacturing costs with what customers are ready to pay. This means taking into account consumer input while developing successful products, calculating appropriate quantities and prices based on predicted demand, and so forth. From focus groups to consumer co-creation on social media in conventional market research, a cross-section of the intended audience participates in activities like completing questionnaires, holding focus groups, or interacting with and discussing prototypes.

Inventories

Manufacturers lose a lot of money and time because of their inventory. The cost of safety stocktaking increases with the addition of space, personnel, and management overhead. ABC inventory classification6 may be determined with the use of inventory analytics, which can then be updated in real-time to ensure optimal item allocation. Using inventory data, BA can assist find obsolete or potentially dangerous items, avoid having too much stock on hand, and make sure you have just what you need to match fluctuations in demand. Using BA to find the optimal stock levels presents a number of challenges. Since there is no universally applicable method for optimizing inventory, StyleHub will need to tailor their safety inventory analytics to their own needs in order to determine what their optimal inventory levels should be. Models should also guard against being too cautious with safety stock or having it become dangerously low, both of which might impact service to clients.

Production

Using BA also aids in productivity. Using pervasive detectors, the Internet of Things, and cyber-physical networks (CPN), true "smart factories" may be developed. By keeping tabs on production in real-time, StyleHub may increase output, decrease waste, lower O&M expenses, improve scheduling, and bolster lean manufacturing initiatives. Information from the past may be utilized to establish a "digital factory" that optimizes manufacturing processes, plant layouts, product stage sequencing, tool development, building, assembling time, cost, and distribution dependability. Consider the following: power, water, procedures, tool optimization, asset utilization, quality, stock, and manpower.

Every day operations and deliveries will be supervised by the project director. Stakeholders will get weekly progress reports. We will pinpoint any potential hazards or problems so they may be addressed immediately. According to Turner (2018), the manager's responsibility for the endeavor will include coordinating the efforts of part-time IT, company division, and analytics team members. After every milestone, the team's technical managers will review the quality of the design and code. User acceptance testing will offer feedback for the subsequent sprint before release. There will be change champions in each department to encourage workers to adapt to the new system. They will train staff, update them, and advocate for the analytics system. User feedback will be gathered via surveys and focus groups. Through the efforts of the steering committee, clearly established operations and technical oversight, and aggressive change management, StyleHub shall be able to realize its expansion objectives (Ciric et al., 2018).

Schedule and Delivery

Design Strategy

Timeline and Completion of the Project:

The 6-12-month project time frame is broken down into manageable phases including gathering requirements, solutions development, testing, deployment, and follow-up assistance (Nicholas, 2020).

Summarizing the Acts:

Each stage of implementation includes a distinct set of tasks and outputs, including planning, solution development, testing, installation, and post-implementation assistance.

Build Iterations:

By encouraging constant, open conversation and synchronization across the project, ritualized gatherings foster collaboration and shared comprehension.

Complete and prepared mean:

The project's commitment to excellence is reflected in the strict preparation and completion standards.

Deployment:

The stage of deployment is when the plan is put into action and the outcomes can be seen. This includes integrating systems, enrolling users, and ensuring a smooth transition.

The project will be completed in two-week "sprinted" phases a rapid delivery method. Here is the big-picture schedule:

Project’s Phase	Weeks	Tasks
Planning	1 to 4 weeks	Verification of Needs Deciding on a Supplier
Building	5 to 12 weeks	3 Releases of the Base Platform Analytics and reporting basics
Expanding	13 to 20 weeks	Improved analytic capabilities and bespoke layouts Systems that can be integrated with others Transfer of archived information
Optimizing	21 to 24 weeks	Bug fixing and performance assessment Evaluations of Safety Acceptance testing by the end user

On-schedule completion is expected by week 24's completion. Each stage will have its own unique set of sprint strategies (Turner, 2018).

Budget

Expense’s Category	Budget Amount
Software’s licenses	$250,000
Implementation services	$120,000
Internal staff timings	$100,000
Training as well as change management	$30,000
Contingency reserves	$50,000
Total Budget allocated	$550,000

The table provides a detailed breakdown of the expected $550,000 cost to deploy a platform for analytics over 24 weeks. At $250,000, licenses for software were the most expensive component (Sirisomboonsuk et al., 2018). It is planned to spend $120,000 towards execution services such as consultation and integration of systems assistance. The total budget for internal technology, company division, and analytics collaboration is $100,000. The projected cost of training and managing organizational transformation is $30,000. Ultimately, a reserve fund of $50,000 has been established in case any unanticipated costs develop during the implementation phase (Damij and Damij, 2021). This spending plan shows that careful preparation went into ensuring the project's timely completion.

Control

Frequency	Control
Monthly	The project is going to employ essential controls, such as:
Bi-weekly	Executive sponsorship and open lines of contact with key stakeholders
Before each build sprint	Consistent meetings of the steering committee for policymaking
End of each sprint	Sprint planning begins with a technical design assessment
As needed	Agile methodology incorporates end-user feedback as well as testing
Ongoing, proactive assessment	Managing and controlling scope changes
Periodic spot checks	Planning for Risk Management and Monitoring
Throughout and post-deployment	Monitoring of quality and achievement criteria in projects

Scheduled execution times for the different control methods discussed throughout the Controls section are shown in the table below. The success of the project depends on prompt governance supervision, stakeholder participation, and direction corrections, all of which may be ensured by setting the appropriate frequency early in the project's lifespan (Dasovi et al., 2020). Leaders and the board of directors get monthly reports to aid in strategic direction and problem-solving (Ahmed, 2018). To maintain a project on course in the face of risks, modifications, and feedback, cross-functional meetings of committees should be held every other week. Technical evaluations act as gate clearances before every construction sprint, guaranteeing that quality is always up to par. Sprint-ending user testing allows for frequent and rapid iteration by closing the feedback cycle (Moradi et al., 2020). Evaluating scope creep when it occurs is essential for keeping projects on track. Control must be embedded into the normal course of project execution via continuing activities including risk organizing, quality inspections, and monitoring success measures. The best rhythm incorporates responsive user feedback with careful administration (Daniel and Daniel, 2018). The controls ensure that the undertaking is managed effectively and that all stakeholders are involved.

Roles and Responsibilities

Chief data executive Sebastian Tran leads the effort, whereas CEO Emma Stiles ensures it aligns with the corporation's long-term objectives (Derakhshan, 2019). Information Technology advertising, and retail must all work together as one cohesive unit if this initiative is to succeed.

They identify the following people and activities as Business Analytics actors:

• Managers should back the initiative to implement BA and keep an eye on the results.
• Tasks for the IT project team include setting up and maintaining infrastructure.
• Consultant and system integration companies should design IT infrastructure and procedures that can easily adapt to new circumstances.
• Managers of competency centers should make sure that the necessary expertise is readily available to utilize the tools and can adapt quickly to changes in the market and in regulations.
• Keep an eye on the competition, the market, and the products they're selling so you can respond accordingly.
• Managers, please utilize the insights and KPIs to make data-driven decisions in your day-to-day operations.
• To all interested third-party technology providers: make your (big) data analytics tools as intuitive as possible.
• Shoppers: investigate available options before making a purchase.

Conclusion

Data analytics have gone from being an added benefit into a competitive requirement in today's fast-paced fashion retail environment. StyleHub has an excellent chance to develop itself into an insights-driven multichannel leader capable of providing outstanding customer service and achieving unprecedented levels of productivity. This long-term project plan was developed to realize this dream and roll out a cutting-edge analytics platform in only 24 weeks. The strategy emphasizes both the technological and organizational aspects necessary for success, which is consistent with recommended procedures for enterprise transformations. The flexibility to adjust to changing needs while maintaining attention to the final objective is provided by the phased, adaptive delivery strategy. Using a model developed by Snyder, planners have been able to create timetables, budgets, and activity plans that are both realistic and thorough (Damij and Damij, 2021). The soft aspects necessary to propel transformation are also accounted for in the strategy. Executive supervision, as well as cross-departmental collaboration and input, are provided via governance systems. Brought about by user-centered design and training, increased uptake is guaranteed. StyleHub's innovative analytics features will help transform its staff from data collectors into deliberators. Risks are inevitable in any large-scale corporate deployment, but they have been anticipated and countermeasures put in place. The plan's thoroughness, realism, and concern for detail pave the way for a smooth transition to the analytics solution. It assures everyone involved that the launch will go off without a hitch and within the allotted budget. The true test will begin once the new platform is up and running and improved consumer and business analytics are being realized by StyleHub. Nevertheless, by anticipatorily addressing possible problems and getting buy-in throughout the business, this strategy maximizes the likelihood of a victory. The first step towards becoming a data-driven shop will have been taken, setting the stage for future development and innovation. StyleHub is undergoing a fascinating data-powered change with dedicated teams and strong project management.

References 

Ahmed, S. (2018). A Review on Using Opportunities of Augmented Reality and Virtual Reality in Construction Project Management. Organization, Technology and Management in Construction: an International Journal, 10(1), pp.1839–1852. doi: https://doi.org/10.2478/otmcj-2018-0012. 

Anantatmula, V.S. and Rad, P.F. (2018). Role of Organizational Project Management Maturity Factors on Project Success. Engineering Management Journal, 30(3), pp.165–178. doi https://doi.org/10.1080/10429247.2018.1458208.

Bredillet, C., Tywoniak, S. and Tootoonchy, M. (2018). Exploring the dynamics of project management office and portfolio management co-evolution: A routine lens. International Journal of Project Management, 36(1), pp.27–42. doi https://doi.org/10.1016/j.ijproman.2017.04.017.

Ciric, D., Lalic, B., Gracanin, D., Palcic, I. and Zivlak, N. (2018). Agile Project Management in New Product Development and Innovation Processes: Challenges and Benefits Beyond Software Domain. 2018 IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE). doi: https://doi.org/10.1109/tems-isie.2018.8478461.

Damij, N. and Damij, T. (2021). An Approach to Optimizing Kanban Board Workflow and Shortening the Project Management Plan. IEEE Transactions on Engineering Management, pp.1–8. doi: https://doi.org/10.1109/tem.2021.3120984.

Daniel, P.A. and Daniel, C. (2018). Complexity, uncertainty, and mental models: From a paradigm of regulation to a paradigm of emergence in project management. International Journal of Project Management, 36(1), pp.184–197. doi https://doi.org/10.1016/j.ijproman.2017.07.004.

Dasovi?, B., Gali?, M. and Klanšek, U. (2020). A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling. Sustainability, [online] 12(8), p.3405. doi https://doi.org/10.3390/su12083405.

Emere, C., Musonda, I. and Okoro, C. (2020). A review of critical project management techniques to enhance construction SME project performance. In The Construction Industry in the Fourth Industrial Revolution: Proceedings of 11th Construction Industry Development Board (CIDB) Postgraduate Research Conference 11 (pp. 521-528). Springer International Publishing.

Moradi, S., Kähkönen, K. and Aaltonen, K. (2020). Project Managers’ Competencies in Collaborative Construction Projects. Buildings, [online] 10(3), p.50. doi: https://doi.org/10.3390/buildings10030050.

Sirisomboonsuk, P., Gu, V.C., Cao, R.Q. and Burns, J.R. (2018). Relationships between project governance and information technology governance and their impact on project performance. International Journal of Project Management, 36(2), pp.287–300.

Turner, J.R. (2018). The management of the project-based organization: A personal reflection. International Journal of Project Management, 36(1), pp.231–240. doi https://doi.org/10.1016/j.ijproman.2017.08.002.

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