Advanced Data Analytics/AI

You want to grasp the opportunity data & AI provide to create business value. You want to create a data-led and/or AI-enabled business and serve your customer better through faster, more precise, and more relevant operational processes. You need a guiding vision with a clear roadmap and the right capabilities to execute and move from promises to concrete value creation.

We are transforming companies to create a sustainable competitive advantage through data-led & AI-enabled decision making. We support our clients with questions such as:

“What are my company’s data priorities?”
“What are most valuable data use cases?”, and
“How do I make selected use cases a reality in my operation?”

Along their transformation, we help by:

Understanding the value
Building a business-led Proof of Concept to prove the value can be extracted
Setting up the organization to deliver value
Operationalizing advanced analytics and a data-led & AI-enabled way of working

Creating value with data-led decision making

Companies generate more and more data but collecting this does not create any value by itself. Data is merely an enabler to move from judgment-based decision making to data-led decision making. That is:

1More objective

Use of data reduces weight of “opinions” in favor of observations

2More granular

Use of data enables advanced personalization

3More scalable

Use of data allows for easier replication

This allows companies to build a sustainable competitive advantage by increasing business velocity, i.e., the ability to generate & apply insights increasingly faster than the competition.

Be business led (not tech-first)

All data efforts should be a commercial margin opportunity focusing on ROI and stepping away from the “data as a hobby” mindset. We support clients by translating their board level ambitions into concrete value opportunities, identifying long lists of opportunities, and prioritizing them. Typical initiatives differ per maturity level of the company:

Transform the organization in parallel

In parallel to rolling out the commercial initiatives, the organization should be transformed. Typically, the organization must change 3 building blocks:

Capabilities – hire externally and/or train people within the organization. For example, at an FMCG company we set up the data team by assessing internal capabilities and hiring data scientists to complement the team. Furthermore, we assisted the team to set up a small-scale pilot and later scale up to a country wide roll out
Way of working – structure organization to use data as the starting point for decision making. For example, we trained all sales reps to approach customers pro-actively, based on insights, instead of selling reactively. Way of working changes in four steps from 1. Reactive, to 2. Proactive, to 3. Precise, and lastly to 4. Automated decision making.

Tools & metrics –develop tooling for insights and decision making and set up cascading KPIs towards phase 4. For example, we developed a simple tablet app that allowed sales reps to see the latest information on their customers, generated via an EPOS. Additionally, we set up the data structure to support live dashboards for continuously tracking & optimizing sales performance

Prove value before scaling up

It’s essential to first prove the value of the use case, to ensure resources are used effectively and risks are reduced to the minimum. We do this by creating a simple version of the solution (Proof of Concept) on which we base a detailed business case with real data. In parallel, we create a tailored roadmap based on best practices, to ensure a smooth scale up of the solution.
For example, in case of demand forecasting, we first create a business case by proving the value of forecasting demand for one product group. Secondly, the Minimal Viable Product is created that is used by ~10 sales reps in one area / country and delivers actual value. When this works well, the success is shared with all sales reps to build excitement. Lastly, the Minimal Viable Product is scaled up to all sales reps across countries and continuously optimized to increase value.

Organize data and tech to support the business case

For actual value to be created, it is critical to develop an operationalized solution which the organization can work with. This often requires adaptations to both the data and technical infrastructure. Firstly, it is critical to assess whether the right data structure is set up that allows operationalization. Secondly, we will collaborate with a technical partner to operationalize the Minimal Viable Product, connect the necessary IT infrastructure, and develop a user interface for employees. Simultaneously, we will make sure the way of working is adapted and necessary capabilities are present within the organization to best capture the identified value.