Challenge

Over the last few years, several consumer goods markets (e.g., sugary drinks, alcoholic beverages, tobacco) witnessed laws that have changed both regarding products’ usage and tax, with significant impacts on brand and consumer behaviour. Further changes with the launch of new product categories will increase the need for price and distribution strategy planning activities.

The current case study was part of a project together with a worldwide consumer goods company to develop a market model for an Asian market, capable of generating strategic insights, including brand and region-specific market share and volumes, and several P&L metrics including brand gross margin and EBIDTA projections.

Solution

Several opportunities were identified to enhance the quality and efficiency of the planning process:

Process - Development of a single-tool centralizing information, parameterization and validation processes, thus streamlining scenario exploration to massively reduce lead-time and increase market review frequency.

Intelligence - Development of a predictive engine to estimate total market size according to prices, consumption trends and the natural growth of the population. Regional brand market shares were also forecasted, considering local preferences of product attributes and switching patterns within the available portfolio.

Analysis - Development of dashboards to support the visualization and analysis of strategic scenarios, providing visual aids to explain causality between strategic levers and market outcomes to senior stakeholders.

Results

The project provided the organization with analytical models, which were vested by higher reliability and assisted the strategic decision-making process towards more accurate decisions. In addition, the integrated market model tool radically reduced the time of generating scenarios, which released the team for higher-value tasks such as result validation and analysis of market insights.

Related Case Studies

ESTIMATING WORLDWIDE ADOPTION POTENTIAL FOR INNOVATIVE TOBACCO PRODUCTS
USING GAME THEORY TO OPTIMIZE STRATEGIC PRICING DECISIONS AT A CONSUMER GOODS COMPANY
OPTIMIZING PRODUCTION PLANNING AT A CONSUMER GOODS COMPANY

Insights

The corporate world has been embracing analytics and artificial intelligence systems within an increasing number of business functions that have traditionally been oblivious to its potential. Additionally, the digitalization of the customer journey is increasing the amount and detail of data that can be accessed, which provides tremendous value towards decision-making and personalization efforts when properly addressed. These new possibilities pose several challenges throughout the marketing mix that require an ever-increasing pool of analytical solutions. Therefore, companies that do not adopt these techniques within their processes will soon become outdated and lose market competitiveness. In addition, the deployment of analytical tools to the different marketing functions will increase marketers’ decision-making quality by empowering them to deliver the right product at the right price and at the right place to the right people. Now, which marketing activities have the largest upside regarding the deployment of analytical methodologies? We will explore this question by enumerating several applications that companies should be looking to improve soon and by examining a recent client analytical transformation. Still, figuring out areas of improvement is not enough for marketing departments to embrace the future, as they must first adapt their own skills and capabilities to embrace a new age of Marketing. Leveraging the P's of analytics Recently, marketing departments have started to deploy analytical processes and artificial intelligence into the marketing mix of their brands’ portfolio, but the full potential is still left uncovered. Product optimization decisions will increasingly make use of detailed consumer market data and forecasting models, whether deciding a retailer’s assortment or a Consumer Packaged Goods (CPG) company’s portfolio. Additionally, marketers planning distribution channels will find tremendous opportunities when challenged with sales location planning or customer contact optimization. Promotional planning, recommendation systems, product pricing and media planning are all activities that will further require personalization efforts to maximize their efficiency. And finally, the customer of the future will be increasingly demanding towards brands, turning personalized and efficient communication from a competitive advantage into a must-have for any corporation. While there is extensive potential for analytical processes, companies should realize that the combination of analytics with manager experience and creativity is still paramount for the success of improvement initiatives. Moreover, resource investment should always be as effective as possible, so expected returns on investment (ROI) should always be evaluated before jumping into any transformational endeavor. Artificial intelligence supporting marketing decisions Take the work we have recently done with a large retailer, in which there was a concrete opportunity to leverage both the teams’ business knowledge and the overwhelming richness of big internal and external data to improve product assortment decisions. The teams clearly knew that analytic processes would be extremely helpful not only to identify and forecast overall market trends, but also to support the customization of product selection to store-specific customer characteristics. In the past, mass customization across all the stores was too complex to be included in the decision-making process, but specially designed analytical models and a careful parametrization of category strategy enable the fine-tuning of managers’ assortment decisions to maximize profitability and to improve supplier negotiation efforts. The new age of the marketing function The megatrend of digitalization has had a corporate-wide reach across all business functions. Marketing departments have typically had a hard time embracing all the opportunities that come along, mainly due to a misalignment between the required capabilities and the typical marketer skills. Typically, companies have either outsourced or leveraged expert internal teams from other departments to obtain the required capabilities to embrace artificial intelligence in their marketing processes. However, with analytics becoming a reality in marketing departments all the way from strategy to operations, this procedure is neither sustainable nor capable of promoting process adjustments and continuous improvement. As such, not only should CMOs promote the integration of analytic-savvy teams within their departments, but marketing business schools should also include these skills within their curriculum. The marketer of the future will combine creative and business skills with analytic and digital capabilities to embrace the incoming challenges, and the first-moving organizations into this field will gain a competitive advantage for the new age of marketing. Written by Pedro Campelo (Senior Consultant at LTPlabs and Professor at IPAM) & Liliana Silva (Junior Business Analyst at LTPlabs).

SEE MORE

'In God we trust, everyone else bring data’, the famous Edward Deming's quote reminds us how important is to get actions and sustain your action on facts and information. With industry 3.0, digitalization and information systems start to be an imperative to be in the market. Right now, industry 4.0 is progressively revolutionizing industries with access to real-time data, connectivity and computational power. However, thinking that is necessary to gather an enormous volume of data before performing analytics is merely a myth.   Analytics helps improve resource utilization From services to manufacturing, every company deals with resources and how to capture the best out of each one. Data analytics provides a set of tools that helps to build a tangible understanding of business processes and better utilization of each resource. Reports and dashboards are the simplest and the most used tool to keep track of each process. Despite being a basic principle of management, by leveraging simple information into a set of KPIs enables companies to detect and keep on track their business. From an operational perspective, monitorization is powerful to track historical decisions but it is not as powerful to foresee better resource allocations or act before more complicated issues arise generating inconvenient situations. Simulation and optimization models are perfect examples of how to overcome this difficulty. By having the possibility to test different set-ups, simulations models specifically tailored to the business problem allow companies to forecast the performance of each KPI without an impact on operations or costly investments. With the possibility to anticipate and analyze each problem, archive better results and improve cost efficiency is much easier. Additionally, optimization models step-up the game by proposing optimal solutions for complex problems like production planning or delivery routes. Simultaneously, from a marketing and sales perspective, data analytics is core to help companies target customer needs and focus their effort to connect the best products with the best communication. Although, the other marketing principles like price or promotion will also benefit from better data analytics, being able to have clear control of what are the causes and actions of each resource is core to exploit the best out of each one.   An analytical powered cultural shift More than numbers, advanced analytics must be ingrained within the company culture and should be fostered from the top. Currently, the challenge with this era is not how to gather the data or select the best tool to analyze it (there are a plethora on the market), but how is data backing up decisions within a company. In a competitive environment not leveraging data is fatal, as is not having everyone on the same page regarding company metrics.                       Data analytics is one more tool to get everyone in the company within the same page and following the same goal, whereas that goal is empowering growth, or improving overall company efficiency without misalignment or gut-feeling decisions. Leveraging tailor-made data analytics such as statistical models or machine learning algorithms to increase client knowledge, optimize pricing strategy or improve resource utilization when doing production planning or inventory management is a sure way to increase a company bottom-line profitability.

SEE MORE