Advanced Analytical Tools
These tools have a multitude of uses ranging from the provision of business intelligence that helps managers understand how and why the organization is performing through to predictive analysis that assists users in understand what happened, why and what is likely to occur next. While this type of descriptive, diagnostic and predictive analytics is vital, it is not sufficient in guiding senior management in their efforts to build strategies around inevitable future challenges and scenarios. While no one can actually see into the future, prescriptive analytics can be added to the advanced analytics suite to help build sophisticated business models that asses different scenarios and their impact on cross-function business objectives. As an indication of how businesses are recognizing the benefits of advanced analytics, Gartner's recent study on prescriptive analytics worldwide reported the number of organizations using prescriptive analytics was expected to grow from 10 percent in 2014 to 35 percent in 2020.
What Executives Gain from Advanced Analytics
Corporate decisions are made by the executive team by focusing on what is known, what has happened, and what challenges / opportunities may face the business down the line. Advanced analytics provide the tools to extract relevant data and evaluate the impact of different scenarios. Although CIO and CTO input is essential, full appreciation of the data needs the combined expertise of the executive team. Key C-suite executives who should be involved include:
- CSCO: Many organizations have Chief Supply Chain Officers who coordinate the entire supply chain from procurement to delivery. Their role is to continually predict demand and match procurement to meet that demand. It goes without saying this is a complex task that involves the integration of inputs from marketing, sales, logistics, production and procurement functions. In a large, dynamic corporation, proactive management of the supply chain requires constant input to evaluate and balance conflicting requirements so as to achieve optimal results. As an example of what can be achieved, a leading consumer goods company significantly increased ROI and improved decision making using business models created using advanced analytical software.
- CFO: Although effective supply chain management is essential, management of cash resources is just as important, and the Chief Financial Officer must ensure the corporation always has adequate funds in hand. Key inputs include knowledge of sales revenue, actual operating margins, funding for work in progress and the phasing of capital expenditure. This crucial task requires immediate access to relevant, trustworthy data provided through advanced analytics.
- COO: The Chief Operating Officer is responsible for overall day-to-day management of the organization and is a key role player in determining direction. While other C-level executives are responsible for short-term coordination of their own activities, the COO needs to keep a finger on the organization's pulse. The COO is also responsible for determining short-term strategy of the business unit and intervening when there's a crisis. As such, the COO needs to be able to visualize the entire operation and use an integrated business planning approach to measure performance, evaluate scenarios and identify opportunities across the organization.
- CEO: The Chief Executive Officer is usually less involved in day-to-day activities, but rather focuses on the longer-term direction of the business. The CEO will obtain input and direction from the company's board, trading partners, suppliers and other organizations. The CEO is ultimately responsible for the business and is held accountable for its results. While advanced analytics are great for strategic decision-making, the CEO may be aware of certain high-level goals and objectives that other members of the business are not.
Moving Beyond Traditional BI
There's a key difference between traditional business intelligence and prescriptive analytics. The benefit of business intelligence lies in its ability to analyze raw data to present senior management with a concise representation of the current state of the business. Advanced analytics then take over by providing tools that effectively and accurately model the business. In doing so, advanced analytics gives senior management the ability to assess the impact of different decisions. Additionally, prescriptive analytics goes further with an ability to analyze data in such a way as to be able to present the best solution for a given set of criteria.
Benefiting from Advanced Analytics
The real benefit of advanced analytics lies in its ability to analyze large volumes of data and to identify patterns / trends that can be used to guide business strategy. But this information is of limited use unless it's in the hands of the business decision makers. Not only that, it's also imperative that all C-suite decision makers are involved in the preparation and analysis of the data because they are best equipped to recognize what the data is saying.