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Data Science Proof Of Concept
Although the concept of Data Science has been trending for many years, many organizations today still struggle in understanding its meaning, envisioning the opportunities and embracing a successful implementation. element61 considers Advanced Analytics as the logical next step and strengthened by our 10-year experience in Business Intelligence, Data Warehousing and Performance Management, we envision the use of advanced analytics as a valuable addition in a best-practice Business Analytics architecture.
We are convinced Analytics can be accessible for companies of all size, doesnt require a big investment and will bring added-value.
As such, our belief is that its important to go step-by-step and to start with a tangible, measurable and simple use-case (i.e., a proof of concept). This allows the organization to learn and to grasp the value that Advanced Analytics can bring. As the organization gains confidence, the organization can proceed in making a choice in technology, mature in smartness, running more use-cases. Along this full learning and implementation cycle, element61 can help.
Context & Scope
A Proof Of Concept is an opportunity as an organisation to test and learn. The objective of the Advanced Analytics Proof Of Concept to provide the customer with a working application as well as to create a common internal understanding of key concepts & technologies. The application (or use-case) is chosen together with the customer and should be in line with strategic pain-points and opportunities (e.g., stock inventory forecast to tackle the increasing cost of depreciations, cross-sell tool to support marketing team with in a rising churn rate, demand forecasting to support finance to improve budget planning, etc.); the Proof Of Concept (POC) project starts when the use-case is set.
As a first step, we need to have a clear view on the objective of the use-case and the business-processes in which its embedded: after all, an Analytical use-case stands (or falls) with a solid business process: a churn prediction tool needs a solid marketing-reactivation process to bring value, a predictive maintenance tool is tight by the delivery lead-times of spare-parts, etc. Through interviews with the key business users, we will gain a clear idea of your business requirements.
In parallel, we will assess data availability and data quality surrounding the use-case. Together with the business requirements, this exercise will permit us to translate the use-case into a detailed POC solution description; this document serves as the bible towards building the actual solution and is approved by the customer prior to progressing in the next phase.
Next, the POC solution is analytically build within a software environment chosen together with the customer. element61 has expertise in each of the leading software technologies including IBM, SAP and Microsoft as well as the mainstream statistical languages and tools such as R, Python, SAS, Microsoft Cloud Machine learning, SAP Predictive Analytics Modeler, etcetera.
element61 differentiates itself by working within the software environments known and used by the customer thus not building a black-box or alien tool. Our experience shows this speeds up acquaintance, simplifies deploys, maximizes success-ratio and minimizes your investments. The final deliverable of this phase is a working prototype including the results of the unit and integration testing (i.e., testing predictive power, testing on unseen data, etc.)
Finally, we will test the model and solution in the day-to-day environment and work with the business teams to assess relevance, user-friendliness and performance. Even a prototype needs to make sense for end-users and be intuitive to use. The impact-assessment of the Proof Of Concept aims to be tangible and measurable and we will present the outcomes and impact to management. In this phase, we will also write some modelling documentation, train the internal team and outline the envisioned next steps.
An Advanced Analytics Proof Of Concept does not require you to invest into new infrastructure nor expensive software. Only when a Proof Of Concept matures and is asked to be put into production, the choice of technology arise. At that stage, our cross-vendor expertise at element61 can help you make a balanced choice ensuring integration with the existing performance management and business intelligence architecture.
We will always start from the business problems or opportunities and match them through our expertise with the solutions advanced analytics can bring. This means well intensively work with business stakeholder to get a solution which makes sense, is useful and performant.
A Proof Of Concept does not have the ambition to build a full solution immediately: i.e., via a Proof Of Concept we will deliver a working prototype through which we can measure the impact of recommendations and get familiar with the technology and concepts. This enables the customer to make a qualified decision on the future potential of advanced analytics and the meaning it can have across the organization.
The technology set-up of a Proof Of Concept will be chosen together with the customer and aims to be as simple as possible. Similarly, the Proof Of Concept will prefer simple statistical models to allow for full understanding from business analysts and management. After the POC, their performance could be further improved through "test, learn and improve cycles.
Typically, the result is (1) a working prototype delivered through a set of login-credentials and/or secured files; (2) a word document with modelling and tool documentation and (3) a PowerPoint presentation with a summary view on the project, the impact achieved and next step recommendations.
Duration & Rates