Integrated Planning

Volatility and constant change is not an exception anymore. This is the routine of a high performance planning process supported by analytics that determines optimized scenarios for balancing demand, production and fulfillment at the highest accuracy level.

Data Driven IBP – the new normal

Integrated Business Planning (IBP) links every planning process in a company: from multi-year plan to yearly budgets and budget review (year-to-go), to FS&OP and to, at the operational level, the S&OE (sales & operation execution). IBP cascades down necessary actions for each decision that is made at all levels and provides visibility and governance over these actions.

All functions are considered in the planning cycles and financial impacts and results begin to heavily weight in the processes. By converting every decision into a measurable P&L impact, a higher level of confidence is brought to the process and companies can allocate the financial benefit to a specific budget line and/or individual objectives.

We, at DHAUZ, believe that an IBP should be data driven by design. Having a massive amount of data from the operation being pulled, stored and sorted, in addition to the amount of available market information, enables an IBP process to be 100% analytical.

Demand Planning

Sales & Operation Planning

Procurement Planning

Inbound & Outbound Inventory Optimization

Profit & Financial S&OP

The right combination of predictive and prescriptive analytics enables the definition of Profit S&OP scenarios at the highest levels of accuracy and clarity.

The latest techniques can even unlock a Cognitive Planning, where intelligent agents perform the tasks of the execution level of the demand, production and distribution plans.

Combining intelligent agents to analytical modeling creates unbiased scenarios and gives 100% control of the strategic decisions in the hands of Sales and Operations leaders.

Planning

Analytics and Business Expertise applied to Planning

We make our vision a reality by approaching integrated planning with IBP concepts, fine-tuning and connecting planning processes, and by leveraging technology and analytics, so that our clients can have a more accurate plan at the same time that they become able to have faster and more efficient reactions to changes they face while executing the plan.

Demand Planning

At DHAUZ, we have many pre-implemented predictive models that allow us to speed up and get to faster results. Besides that, we have a team of expert data scientists who are ready to customize and develop new models that reflect your specific issues or challenges. LEARN MORE

P&L Modeling

we model our client’s P&L to allow them to comprehend the impact of planning and operational decisions on the company’s projected financial results and base the integrated plan on whichever goal they might need to achieve: incremented market share, cost reduction, margin improvement, sales volume or revenue growth, etc.

Inventory Optimization

we leverage ML modeling, optimization and simulation to optimize inventory levels and get highly accurate results. We add simulation to inventory management for an ideal replenishment parameters definition to assure the most balanced levels of raw materials, components, work in progress and finished products.

Ferramentas Analíticas para Cenários Otimizados

Ferramentas customizadas ou de mercado para planejamento preditivo e prescritivo, com algoritmos build-to-suit considerando os custos logísticos e impostos para dar clareza do impacto das decisões tanto na operação, quando nas finanças da companhia

S&OP and S&OE Integration

Tactical planning and execution alignment that is achieved by having a control tower to orchestrate and govern processes, to engage all necessary functions, aims for overall optimization (rather than a specific function or market) and follows-up on actions defined for each planning cycle.

Client vs. Product Segmentation

We use predictive analytics and AI to create client and product segmentation in order to differentiate processes and apply the best analytical conduct for each cluster.