Optimizing Your Business Performance with AI & Analytics
KEY PLAYERS INSIGHTS
Optimizing an organization's performance requires collaboration between various areas including accounting, sales, human resources, marketing, etc. There are a series of emerging, and perhaps overlooked, practices that can help optimize all these different functions at once, which can free-up resources and increase the overall performance of an organization.
Finally accessible and mature advanced analytics
Advanced analytics solutions are no longer the exclusive domain of large corporations and multinationals. Solutions such as data mining to find knowledge hidden in repositories, predictive models to reduce uncertainty or optimize operations; data science and advanced analytics are more mature than ever. In addition, these practices have been optimized during the past decade through trial and error and learning from practitioners. These advances make these solutions a now affordable option for small and medium sized businesses to help them quickly set-up customer segmentations, prediction of employees’ departures or sale forecasts. Finally, analytics is no longer only led by data science and corporate teams, but are rather diffused and sometimes led in business units themselves, putting business people at the center of design and delivery of such projects.
Automation, often neglected but can have a major impact
Often considered as a distant practice of business success and optimization of an organization, automation is actually a major player, a real linchpin of digitalization and champion of returns-on-investment. Automation can be applied to various fields including human resources, information technology, customer service, and more. These solutions can augment workers’ productivity, streamline and optimize operations in order to improve customer service and boost employee engagement and productivity. A simple example of the benefits of implementing automation in an organization is robotic process automation (RPA). This practice uses software robots or “bots” to automate repetitive, rule-based tasks within a business processes at scale. Software bots, or bots, can act automatically and perform simple to complex tasks automatically and with minimal errors, which can help an organization on the road to digital transformation. These projects can help reduce the burden on your employees and help them focus on value-add tasks.
Artificial intelligence, where to start and how to evolve
Obviously, the most relevant and fastest-paced topic in terms of emerging technologies is undoubtedly artificial intelligence. AI is a large domain that includes automation, natural language processing, virtual assistants, document understanding and other technology. For many organizations, AI remains an enigma and leads to misunderstanding and fear. However, many AI technologies such as virtual assistants, image recognition, intelligent document search and classification are mature and can help organizations achieve major productivity gains. In some industries, the implementation of the right AI solutions can be a question of survival. The right solution can accelerate research and development efforts, leading to the discovery of new products, it can assist in talent acquisition by automating resume screening, or it can optimize inventory management or demand forecasting.
Successful AI projects focus on people, not on technology
The key in implementing these 3 emerging practices within your organization lies in the choice of projects to start with and the participation of the right internal business partners (e.g., domain experts, data scientists, IT professionals, etc.). This means selecting value-add projects, ensuring you have access to high-quality data (i.e., clean, well-organized and accessible), selecting the right technology that addresses the specific use case. But it also means the imperial need to put the end-users and internal business SMEs at the center of the design phase. Successful analytics and AI organizations are the ones where the business brings data and SMEs in a coordinated effort with data science and analytics experts. It also means starting with small, controlled pilot projects to test the solutions and provide learning opportunities for your team and business partners. AI does not have to be big or complex. Successful organizations in AI are actually good at infusing it with a lot of small and medium projects, that helps the business and make it AI driven as a whole.
Bringing performance without jeopardizing ethics
Finally, obviously the need to bring performance and automate as much as possible operations and decisions with AI should never be done without carefully putting ethics as an organizational standard. Transparency, explainability, robustness and fairness should be the pillars of your AI practice. From design, to development and deployment, these 4 key dimensions along with security of information, would not only minimize the risks of getting negative brand impact or being caught by regulators, but also bring more performance to AI projects by creating positive enforcement end to end. AI has a tremendous potential and as any powerful tool, it just needs powerful mechanism to ensure safe and ethical use of it.