Information Systems and Big Data in Startup Companies

Introduction to Information Systems in Startups

For startup companies, the key business functions include sales and marketing, HR, finance and accounting, and manufacturing. Present-day startups require information systems for monitoring all their business operations, such as business planning, material acquisition, production, quality control, and delivery to markets. In view of these key business roles, the chief information systems required are: Marketing and Sales Information Systems, Production and Manufacturing Information Systems, Accounting and Finance Information Systems, Strategic Information Systems, Enterprise Collaboration or Office Automation Systems, and HR Information Systems (Al-Mamary, Shamsuddin & Aziati, 2014).

Functions of Information Systems

Marketing and sales departments are in charge of selling company offerings. Marketing chiefly deals with determining buyers of the company's services and products, ascertaining their demands and requirements, planning and creating products and services to satisfy those demands, and conducting advertising and promotional activities. The sales function deals chiefly with getting in touch with buyers, selling the company's services and products, order-taking, and follow-up sales. These functions are supported by marketing and sales information systems. Shim (2000) claims that marketing information systems support management in the domains of product and service development, pricing, marketing mix, promotion, sales forecasts, and distribution.

The financial function deals largely with handling corporate financial assets and investments such as cash, bonds, and stock. The accounting function deals with maintaining and managing corporate financial records, including payroll, receipts, and depreciation (Al-Mamary et al., 2014). Shim (2000) asserts that accounting software's central role is the automation of routine accounting transaction entry and posting. This data is electronically organized for developing financial statements and is easily accessible for helping company leaders manage the organization. Finance information systems provide financial data to all financial managers within a company. Financial decisions are normally made based on data produced by accounting systems.

HR information systems deal with generating, categorizing, maintaining, and distributing information about the workforce in order to help managers at different levels undertake appropriate decision-making. Currently, most successful firms employ HR information systems to facilitate everyday HR operations (Al-Mamary et al., 2014). Corporate HR departments are responsible for attracting, training, and retaining personnel. HR information systems facilitate tasks such as identifying prospective employees, maintaining comprehensive files on current workers, and developing programs to improve personnel skills and knowledge.

Production and manufacturing functions are responsible for the actual creation of services and products. Production and manufacturing systems handle tasks including: planning, developing, and maintaining production facilities; setting production objectives; acquiring and storing raw materials to ensure uninterrupted production; and scheduling material, equipment, human resources, and facilities to produce finished goods. Rivera and Hernandez (1997) note that production information systems are computer programs capable of managing a production-linked data pool. Shim (2000) maintains that the mission of manufacturing information systems is to apply computer technology to improve production effectiveness and processes, thereby improving product quality and reducing manufacturing costs. In short, manufacturing systems take in information technologies, materials, data, equipment, and management practices, and employ them through manufacturing processes to generate improved end products.

Enterprise collaboration systems, also known as office automation systems, are among the most common information system types used to help managers control organizational data flow. These systems are responsible for enhancing workgroup and team efficiency and communications. Although they operate at a broad level and are not specific to any single organizational level, they offer key support for a wide array of users. Their aim is to support office activities using information technology. Email, voice mail, video conferencing, multimedia systems, group decision-making tools, and file transfers may all be carried out using enterprise collaboration systems (Al-Mamary et al., 2014).

Strategic information systems use IT to provide firms with a competitive edge through their business processes, products, or services (Nowduri & Al-Dossary, 2012). They represent a specialized category of corporate information system whose primary purpose is securing or maintaining a competitive advantage.

Importance of Operational Data and Big Data

Efficient and effective acquisition, processing, and analysis of operational and big data will help a firm gain a more comprehensive understanding of its business, customers, offerings, competitors, and more. This can lead to efficiency improvements, reduced expenditure, improved sales, better products and services, and enhanced customer service (McGuire, Manyika & Chui, 2012).

Operational and big datasets help organizations overcome conventional limitations cost-effectively, opening avenues for ingesting, storing, and processing information from novel sources such as market data, social media, communications, and digital customer interactions. Research indicates that over eighty percent of organizational information is unstructured and therefore not suited to conventional data processing systems (McGuire et al., 2012; LaValle et al., 2011). The use of big data facilitates unstructured data processing and increases system intelligence, which can then be applied to improving sales performance, better understanding customer requirements, supporting marketing campaigns, conducting fraud monitoring, and strengthening internal organizational risk management.

Big data competence helps companies integrate two or more data sources easily and efficiently. Combined with decreased per-GB storage costs, this enables companies to develop, for instance, a federated customer view by consolidating client information from numerous isolated departments into a single structure and then running consolidated data analytics and reports (LaValle et al., 2011). Furthermore, big data technology frees firms from the historical cost-accuracy trade-off, allowing them to retain information at granular levels of detail and preserve all information history economically and with ease.

The big data concept has given rise to a new paradigm in data architecture. Earlier, data systems relied on a fixed collection of information requirements. Now, platforms for data storage are no longer limited to a rigid, predetermined data model — data systems can manage all varieties of structured and unstructured information (McGuire et al., 2012). Unstructured data integration can, in particular, improve reporting and analytics. For example, the organizational objective of maintaining an integrated customer profile view across geographies and functions is vital for: ensuring more intelligent organizational decision-making; enhancing customer profile monitoring to identify "red flags" (i.e., opportunities or threats); and enabling the firm to deliver more relevant and customized customer services.