Business process design and modeling is primarily transactional and static, and has traditionally been very effective for enablement and support processes. However, process modeling in customer-facing activities brings a unique set of challenges to the forefront. In these cases, the process is more dynamic and less predictable than back office, transactional processes, as there are activities which occur outside of the process owner’s span of control (for example, wait times between the customer seeing a product, and purchasing it).
A dynamic and flexible business process modeling approach is required to adapt to these environments, and add structured decision frameworks to otherwise subjective and inconsistent decision-making processes. In today’s competitive landscape it is imperative that the entire business process follows a standard structure which is robust enough to achieve buy-in from all the stakeholders and build a strategy that can maximize the chances of success.
A retail industry case study is illustrative. A merchandising group of a major retail client required the creation of an integrated process solution to support objective and consistent decision-making regarding selection of products to include in the retailer’s promotional programs. It included the design and documentation of process models for selecting promotion items and the preparation for supply chain execution and ongoing replenishment of these items. This included reaching consensus on current state process, identifying the desired future state process, and creating a roadmap to address gaps between current and future state.
The solution also included a mapping of stakeholder roles and responsibilities, both within the merchandising group and various support teams and stakeholders that would need to be executed for successful implementation and sustainability of the solution. Identification of appropriate interfaces between business organizations was necessary to assess the effectiveness of the decision-making chain and the role of support teams in the planning, executing and monitoring of a promotional event.
The assessment uncovered the non-utilization of tools that assist in building an intelligent and predictive strategy of planning and executing events. Predictive analytics is a significant source of competitive advantage and provides an opportunity to achieve a higher ROI on projects when compared to those without the use of predictive analytics.
Some of the other significant drivers of creating a predictive analytics culture are cost reduction in serving existing markets, cross-selling, quicker response to economic swings, new product launches and trial, and testing of new governmental regulations and customer demand.
Further, predictive analytics combined with business intelligence will help the group in exploiting the capabilities of support teams and data sources so that strategy is built on historical data, voice of the customer, corporate strategy and pre-defined performance metrics. A robust and dynamic business process relies on association of metrics to each part of the process to allow effectiveness measurement at every transaction point of the process.
A successful business process solution for this group thus consisted of roles, activities and tasks that align with performance metrics and fully utilize the capabilities enabled by an intelligent analytics system that will help the group gain credibility and eventually help the company be a leader in the industry.