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Zara Case Analysis Zara: It For Fast Term Paper

Zara Case Analysis Zara: IT for Fast Fashion is a unique case study in that it powerfully illustrates how a lack of IT integration and process efficiency can over time force an organization into complacency, lowering the standards of performance due to a lack of real-time market and operations data and analytics. The POS terminals that are running on a discontinued version of the Microsoft DOS operating system is a metaphor of the entire company's approach to using IT more effectively. Adopting a more agile IT architecture based on the Software-as-a-Service (SaaS) platform is needed. Integrating ordering fulfillment, distribution and manufacturing is needed.

Case Synopsis

Zara's management teams are being pulled in spe4rate directions as the company continues to aggressively expand, operating 11,558 stores in 45 countries as part of the Inditex group, 550 of which are branded as Zara stores. Inditex is on pace to open one store a day throughout the time period of the case study globally. The in-store inventory management, ordering, forecasting, pricing and merchandising systems are either manual or semi-automated, leading to many potential areas of errors occurring. The POS systems that are so easily installed and used based on the MS-DOS operating system are archaic and outdated by several technology product generations by the timeframe of the case in 2003. These terminals have become the metaphor for how behind current technologies and best practices in automating retailing Inditex is corporate wide, particularly impacting the performance of Zara.

There are many areas Zara's operations that reflect how the outmoded technologies they are using are impacting their performance. Beginning at the store level, the illusion of ease of setting up new stores with a POS terminal running MS-DOS hides more severe problems. The greatest is the lack of visibility and traceability of inventory levels. Taking inventory by hand is a very good way to get inaccurate counts that have a direct effect on in-store profitability. Second, there is no real-time reporting on pricing performance by product category, no visibility into which sale items are doing well and why, or even a count by total items sold daily. Zara's management reverts to an economic order quantity (EOQ) automatically if an order is not received which in many instances is no doubt just perpetuating mediocre and substandard retailing practices.

The lack of automation around forecasting and the disjointed fulfillment processes can also lead to very costly operations errors for the company as well. The complacency around archaic technologies are leading the company to be complacent about far more severe problems that are impacting their business. At the corporate level, the lack of a centralizing analytics or business intelligence function for optimizing the data collected from order management, fulfillment and distribution and manufacturing will eventually slow down their profitable global growth. The velocity and exhilaration of being able to launch stores literally overnight and not invest in training for more advanced Point of Sales (POS) systems is blinding management of severe problems that will take millions of dollars to fix and cut into months, if not years, of productivity.

Analysis of the Company's Goals and Strategies

The company's goals and strategies are all aligned to fulfill the original vision of the founder, which is to link customer demand to manufacturing and link manufacturing to distribution. This vision is the basis of the collaborative planning and forecasting (CFPR) process that has become commonplace throughout retailing in the 21st century (Sagar, 2010). Overall, this is the strategic vision of Zara which unifies the remaining objectives defined in this section of the analysis.

The first objective in support for this vision is the integration of ordering, fulfillment and design and manufacturing. The intersection of these three areas of the Zara business model force all other areas of support or sustaining activities to also align to customer-driven demand management. At the time of the case study, these three systems and the processes they are based on are disjointed, loosely coupled and defined, and lack clarity and crispness of definition. Noticeably absent from this aspect of Zara's most challenging objective are Customer Relationship Management systems. For this objective to be attained, Zara needs to bring in analytics and business intelligence based on customer data and intelligence. The integration of CRM systems and the analytics and business intelligence they provide are a galvanizing force in uniting fulfillment, forecasting, design and manufacturing and order management in retailing (Phan, Vogel, 2010). While the case doesn't mention the role of CRM systems and their critical nature of the information they can provide, if Zara is to succeed...

A glaring omission throughout the entire case study is the lack of any multichannel selling strategy whatsoever. Just focusing on retail in 2003, in the very competitive retailing area of women's fashions (60% of sales are from this segment) with 20% of revenue from men's and children's clothing, so an incredible lack of insight. In 2003 the most successful retailers even on a regional level had very established multichannel selling strategies. The fact that Zara is using their website as an electronic brochure, even in 2003, is inexcusable. They need a CIO, another major problem that will be discussed later. Yet the multichannel blind spot the company has during the time period of the case study is also robbing them of valuable data and information on how to accomplish more across all channels. The use of multichannel-based data using in analytics and business intelligence systems is very effective in managing primary retailing locations (Chu, Messinger, 1997). Zara needs to get their multichannel act together.
The second major objective that Zara is attempting to accomplish is to streamline the in-store operations, beginning with inventory management and progressing through ordering, replenishment, forecasting, and pricing striving to achieve consistency in those core areas of their business. These are the areas that many retailers are most challenged in accomplishing while also keeping their product mix eclectic enough to keep customers coming back to see what's new. Zara is not balanced on this objective, as they can deliver new clothing in six months or less as evidenced by their cycles of purchasing and have a reputation for having so many new, exiting styles that up to 75% of the items may change in a given month. All of this rapid product change however is supported by technologies out of the 1990s, regardless of the applications running on PDAs in the 2003 timeframe. This objective of streamlining in-store operations would be more accomplishable if analytics and business intelligence gained from tracking customer activity was present in the existing Zara IT platforms. WalMart successfully manages stores using data warehousing, analytics and business intelligence to more effectively plan store-by-store inventory positions (Foote, Krishnamurthi, 2001).

The third objective is integrating their financial systems to their order management, fulfillment, distribution and manufacturing systems to gain greater insights into operational performance. The company today is not able to accurately track the financial performance of its core business down to the store level due to the lack of this system integration, compounded by the lack of analytics and business intelligence to the store level. The lack of control over forecasting in many retail organizations is actually a signal of financial systems not being integrated well enough to demand management and forecasting functions as well (Keifer, 2010). For Zara, this objective needs to be taken on more from the standpoint of redefining and accentuating core business processes first, then gradually layering in financial IT systems later. This third objective is also going to be more difficult for the company to attain, as it processes are stuck in the 1990s and will have to be drastically changed at the store level in order to be effective.

Analysis of Problems Encountered in Business Processes and Operations

Zara has acquiesced into complacency on its IT strategies corporate-wide with the greatest evidence of this being at the store level. The lack of integration across the order, fulfillment and distribution and manufacturing systems and strategies of the company are making its in-store inventory management and pricing strategies orders of magnitude more inefficient. There is very little information sharing throughout their distributed order management process, beginning at the store level and progressing through the distribution centers (DCs) and warehouse locations (Tokar, Aloysius, Waller, Williams, 2011). Instead of addressing this lack of information technologies and systems integration however, Zara's senior management continues to perpetuate the focus on ease of store roll-outs by relying on outmoded POS terminals that run on a discontinued operating system instead of seeing information technology as a transformational force that could take Zara and all of Indetix to the next level of performance from a market share and financial standpoint.

The lack of IT coordination has over time seriously impacted the company's ability to stay competitive and created a complacent, risk averse culture that is gradually reducing the company's ability to compete. Using the Value Chain Model (Porter, 2000) to evaluate the performance of the company by comparing its primary activities…

Sources used in this document:
References

Azevedo, S., & Ferreira, J.. (2009). RFID Technology in Retailing: An Exploratory Study on Fashion Apparels. IUP Journal of Managerial Economics, 7(1), 7-22.

Carr, K.. (2010, April). It's about value, not cost. Marketing: Field Marketing Essays,15.

Wujin Chu, & Paul R. Messinger. (1997). Information and channel profits. Journal of Retailing, 73(4), 487-499.

Howard Cox, & Simon Mowatt. (2004). Consumer-driven innovation networks and e-business management systems. Qualitative Market Research, 7(1), 9-19.
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