Introduction to Data Science Cookies Ltd Bakery

Question: Discuss about theIntroduction to Data Sciencefor Cookies Ltd Bakery. Answer: Introduction Cookies Ltd bakery has been selling its whole range of enticing cookies since years. The sales all around have been productive and now it is time to grow digitally. The company runs its business through local transaction management system. With the advent of technology now one can present themselves and their product anywhere and anytime. The report comprise of the two prior requirements of the company that is being Consumer-centric and Data-driven. It will focus and highlight the technologies that will help the company to expand and achieve high sales and productivity maintaining the quality. This report has been divided into three parts Storage and data collection system Data in Action Business continuity plan during IT disaster The age of digitization has taken the business to great heights. Each and every company whether executing business online or not, today requires an online presence. This presence allows holding on to consumers and enlarge mass of potential customers. Being online helps one to showcase their products and thus making it easier for the company to become a brand. This also provides a gateway for the customer to be connected with their favorite product or brand by rating and reviewing the product. This kind of medium influences a large mass with varied customer of diversified demography. Along with that new and trending Information and Communication technologies should not be forgotten. Today we have many such systems to help the business flow fast and accurate. Cookies Limited likewise requires a strategic plan to keep a track of customers needs, demands and feedback in accordance with the data collected from the customer itself. Following strategies and business model can be implemented to achieve the desired outcomes. Data Collection Storage System Data can be defined as any set of information or facts gathered from different channels of sources for analysis or referencing (Stanton 2013). Data collection is a way of collecting or gathering facts on some targeted variables done in a systematic fashion. These data need to be analyzed, managed, calculated and keep a track of it (Stanton 2013). Tracking the data let the company plan and manages future models for the growth of the company (Shmueli, Patel and Bruce 2016). Data collection basically is done to secure the evidence and then analyze it later to answer those questions that have been raised. Cookies Limited requires maintaining the data related to its inventory, transactions, sales and product details. Inventory Data for all the raw products purchased needs to be stored so to keep a track on the investments and the budget. Transaction It will include all the monetary deals taking place related to buying of raw products, selling of the products made, investments on buying new and more advanced machineries, packaging and payments made to the employees. Sales Under this only the data related to pure sales of the company is maintained. The productivity and the gain incurred in the sales in a particular time. These data capture evidence and calculate the growth of the company in the recent past. Product Details This will consist of all information related to the products being served by the company along with their extent of sale. It will help in re-designing the product list in accordance to the present demand. Storage System A storage system can be mentioned as a system which stores, updates and allow user to access data to resent or calculate any issue. The storage of these data is very important for the company which would be advantageous if all is stored at one single place. This can resolve many issues of storing, accessing and managing data. This process can be accomplished with help of a proficient database system. A Database system will allow the managing authorities to conveniently store and update their data collection (Coronel and Morris 2016). To implement, this will require appointing a Database Administrator who will manage the entire task related to it. This system comes for free (Oracle database) and does not require any nominal charges. Alongside this also provides the facility of cloud computing which allows authorities to access manage and alter data anywhere, anytime through any devices (Grasselt 2016). Carrying out these implementations will lower the investment budget, increase the productivity, make computing faster and help the Cookies Limited to prosper (Bester et al. 2016). Data in Action Consumer-centric product design determines the marketing and sales of a specific label, bracket or the monetary portfolio of products. Such design provides liberty to the company to target appropriate consumer to enhance the profits. Furthermore, it assists company in determining suitable strategies for acquisition of suitable customers by understanding customer demand and service based requirements. Besides this, it helps in long-term value additions by differentiating a product from the race and decrement in the production time to maximize profit. Production and marketing of such produce must be customer oriented and is be induced by appropriate statistics on the requirement by the customer (Chang 2016). Customer centric business requires consumer pivot direction, cognizance of the target consumer, detailed analysis on the existing and future relationship, strengthening the front line, increased profits, and appropriate feedback to key stakeholders. Customer Relationship Management (CRM) Customer Relationship Management (CRM) software can prove to be a best implementation to get the business customer centric. To elaborate we can say, it is software which works on enormous amount of data where it solely uses it artificial intelligence to list down or separate the needs and requirements of different people differently. This sets appropriate policies, procedures and guidelines for synergy between the producers and consumers, and amplification in overall experience of customer (Khodkarami and Chan 2014). It gives the company and its people a 360 view of every customer and then allows to use these data to heighten the experience of the customer. This can push the business to a different level. It can help Cookies limited in the following ways: Providing a Complete View CRM software works as a perfect tool which functions smartly to identify the customers need and the history of the positive customer. It is like a survey made internally for a better understanding of the customer interaction. Here one can reference to the last customer interactions. This works much faster and in a smooth manner. Marketing Automation This is another highlighting feature which makes the CRM efficient in providing customer centric business. It provides all from email designing to automation. It sends registered user or customers electronically generated mails with new and upcoming products feedback forms and other such details to make customer relationship better. In this way business can be empowered in more lot sense. Sales Pipeline It is one of the general advantages of the CRM software to track and identify the sales pipeline. Visibility of the sales pipeline is very essential as it allow to insight in forecasting in an enhanced way. Once the precept about insights are clear on can have a far more beneficial conversation or rather interaction with the prospects. Intelligent Recommendation System Recommendation system is an extension of information filtering system which works more deeply with the allied properties of an artificial intelligence. It determines the proclivity and ranking the customer must provide as a feedback to the service or product provided (Robillard et al. 2014). In general it provides a company with likes or dislikes of customers and works as a filtering system. It automatically learns from the customers previous behaviors and action, thus forming a list of recommendation for their next interactions. Based on filtering type recommendation system are of two kinds: Content Based: Such technique compares content to consumer attributes. Comparison is done on the basis of detailed prognosis on the existing information on consumer demand and sales (Adomavicius and Tuzhilin 2015). Furthermore, it does not undertake consumer perspective for the decision making. Collaborative Filtering: It is a primary technique which advocates products after the detailed analysis on the need and requirement of the consumer. Furthermore, it uses consumer perspective for the decision making (Hedge and Shetty 2015). On the basis of the ratings and reviews provided the collaborative filtering generates recommendation any of the three below given ways: Item-based: recommendations that are categorized in consonance with similar items. User-based: Users having familiar characteristics and interests are used to derive the recommendations. Slope-one: This is a fast method which uses previous rating of the items to create a recommendation lists. Business Continuity Plan Business Continuity undertakes procedural designing and composition that allows an organization to continue operations in power outage and other disasters. The three core dimensions of business continuity are resilience, recovery and contingency (Cook 2015). Disasters must never affect functioning and framework of the business (Snedaker 2013). Further, a business must immediately recover from the critical situation and must be willingly available to front an unfavorable condition. Continual survival of online business can be implemented with the help of Information Technology Disaster Recovery Plan. This provides an organized approach to unwanted and unfavorable threats to hardware, web, software and system (Whitman, Mattord and Green 2013). Undertaking business impact analysis (BIA): This provides insights on information technology systems and constituents in order to locate and prioritize critical areas. The system which the company installs will keep them ahead with planning as the data analysis will be provided to them and they can plan their impact and solutions beforehand. Genesis of preventive measures: This determines different measures to be taken to decrease or overcome the detrimental effects. Data backup creation can be a major step to fail the effect of power outage or disaster (Whitman, Mattord and Green 2013). Here vendor supported recovery strategy will efficiently help the company to be ready for any disaster as the data has been backed up on someplace else thus saving the data from any kind of mishap. Evaluation and modification of restoring methods: This step provides analysis on strategies required for recovery after the disaster. Formation of Information technology emergency plan: Although if company lands up also in any trouble these steps provide policies, procedures and strategies for restoration after a power outage or other disaster (Cook 2015). Hence Cookies Limited requires framing on certain reconstruction plans and policies which will help it in disaster recovery. Experimentation, tutelage and implementation of procedures: This step determines the loopholes in the existing plan and also provides further training required for the efficacious activation. Continuance of new plan: This step provides an updated plan with fewer loopholes to enhance the efficiency of the business (Cook 2015). Conclusion Conclusively, Cookies limited will flourish greatly in future with digitization. The company can go with present technologies and advancement familiar today. This will allow the company to be present in front of mass without any extra advertising. It is also true the brand or a company gain more popularity among masses if it is user centric that is a user or a customer can freely share a feedback and send responses in likings of their flavor, taste and services. The company on choosing the above mentioned appropriate methods and techniques like recommendation system, database system or customer relationship management system will brinng the company in race with todays growing companies. References Adomavicius, G. and Tuzhilin, A., 2015. Context-aware recommender systems. InRecommender systems handbook(pp. 191-226). Springer US. 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