Small and midsize companies are constantly under pressure to differentiate themselves in a highly disruptive environment. Every rival – from one-man startups to large conglomerates – can rewrite the competition playbook forever with one new business model, one breakthrough offering, or one creative process. It doesn’t matter if the industry is mature; the company must create and exploit value immediately to squeeze out every last drop of value from operational efficiency, data-driven insights, and revenue growth.

Small and midsize companies are well-known for pivoting and changing direction with a speed and tenacity that’s difficult for even a multi-million-dollar enterprise with unlimited resources to duplicate. However, this quality leads to significant advantages only when coupled with outcome-oriented, real-time insights made possible by the latest analytics technology.

According to the IDC Analyst Connection whitepaper “Analytics for SMBs: Sharpen Operations, Capitalize on Business Opportunities,” sponsored by SAP, Ray Boggs, vice president of small and medium business research at IDC, acknowledged that “business analytics and business intelligence can inform almost every aspect of a growing company’s operations.”

Prime future success with data and advanced analytics

Whether it's classic performance measurement and financial scrutiny; regular sales, costs, and profit reporting; or HR and workforce measurement, analytics can help identify areas for greater efficiency, untapped revenue generation, process improvement, and employee training. Essentially, businesses have no choice but to add advanced analytics to their digital repertoire. If we take a moment to think about the big brands that have disappeared in recent years, it is clear that their demise was the result of limited or delayed insight on the evolution of customer behavior and market dynamics.

Everything that a small and midsize company does is centered on the customer. For this reason, advanced analytics is a great fit when it comes to dissecting and truly understanding customer needs and shopping patterns with a swift, in-the-moment experience. More important, as most successful companies have shown, the business model must also leverage that information to add value to the customer experience through, for instance, micro-personalized recommendations, content, and campaigns.

A prime example is Snow Peak, an outdoor gear retailer that has grown from a single store in the mountains of Japan to a multinational enterprise with over 100 stores. The company attributes its growth to its commitment to understanding customers and offering products that closely meet their needs. However, Snow Peak realized that its use of Microsoft Excel, an outdated enterprise resource planning (ERP) system, and handwritten notes were not effective ways to share customer tastes, preferences, and buying histories with other salespeople and event planners. For example, staff may identify the right product for a customer – only to later find that the item is out of stock and miss an opportunity to achieve a sale and make a customer happy.

By adopting predictive analytics in the cloud, Snow Peak centralized, unified, and controlled fragmented information about customers, inventories, and all other aspects of the business and made this data available to executives, salespeople, and other business users in real-time. Furthermore, it optimized inventories by coupling supply and demand data and keeping it up to date.

Snow Peak’s decision to scale its customer experience with advanced analytics in the cloud is one of a variety of use cases that can greatly improve the performance of a small and midsize business.

Additional applications that are just as impactful – if not, more – include:

• Real-time collaboration: Employees, suppliers, partners, and customers can collaborate together with access to in-the-moment, accurate data, which is a critical component of keeping everyone in the value chain engaged and informed
• Operational optimization: Companies can balance profitability, quality, and cost control with on-the-fly what-if analysis and insight acceleration through machine learning
• Extended supply chain: Predictive analytics and the Internet of Things provide supply chain operations with the information needed to respond to ever-evolving market expectations while maintaining profitable sales and operations, demand fulfillment, response and supply planning, and inventory optimization
• Core business processes: Emerging analytics technology – including machine learning, artificial intelligence, and blockchain – can help create a well-skilled, productive workforce; free employees from repetitive, low-value tasks; optimize supplier negotiations; and speed accurate decision making and planning

Even though small and midsize companies have fewer employees, less cash flow, smaller inventory, and less diverse product lines than their larger counterparts, the ability to know everything about themselves and their customers brings an opportunity to stay one step ahead of the competition. But the data is only as good as the business’s ability to capture, process, analyze, communicate, and act on it in a timely, efficient way. By using advanced analytics, small and midsize companies can acquire the skills and mindset needed to turn decision-making processes and strategies into transformational, leading-edge innovation.

by: Nic Smitch
source: news.sap.com