6 Steps of Solution Decomposition Process for Successful Artificial Intelligence Solutions

Solution Decomposition Process designed to ensure that artificial intelligence (AI) is deriving and driving new sources of business value. The power of this process is its simplicity. By staying focused on the business or operational objectives and tasks, businesses can successfully transform how they use data and analytics to produce optimal outcomes. There are six key steps to the Solution Decomposition Process to undertake before deploying AI solutions to derive and drive business value.

Artificial Intelligence Solution Decomposition Process with deep learning and machine learning
Artificial Intelligence Solution Decomposition Process with deep learning and machine learning

Step 1: Identify and understand your targeted business initiative
A business initiative is a senior executive mandate that seeks measurable and material financial impact on the value of the business. Key characteristics include:

  • Sense of urgency mandating results be delivered in 12-18 months
  • Important to success and survival of the business
  • Compelling and material financial impact (ROI)
  • Clear business executive ownership – someone on the executive team is not sleeping at night due to their concerns on this initiative
  • Analytically friendly in that customer, product, and operational insights have material impact on initiative success
  • Bounty of potential data sources to be mined for actionable insights in support of the business initiative
  • Strong CIO leadership and IT business collaboration

Step 2: Identify Your Stakeholders and Constituents
Identify the internal stakeholders internal stakeholders (e.g., sales, finance, marketing, logistics, manufacturing) and external constituents (partners, suppliers and customers) who impact or are impacted by the targeted business initiative. Create a single-slide persona for each stakeholder and key constituent that captures roles, responsibilities, pain points and key operational decisions for each use case.

Step 3: Identify Key Decisions
Identify the decisions that the stakeholders and constituents need to make to support the targeted business initiative. Be sure to invest the time upfront to identify, validate, vet, and prioritize the decisions because:

  1. Not all decisions are of equal value.
  2. There may be some decisions that need to be made prior to other decisions.

Step 4: Identify Predictive Analytics
Identify the most important questions that the stakeholders are asking today in support of their key decisions. Questions can then be converted into predictive analytics. For example, instead of asking: “What was customer attrition last month?” we want to predict: “What will customer attrition likely be next month?”

Step 5: Brainstorm Data That Might Be Better Predictors of Performance
Collaborate with the business stakeholders and constituents to brainstorm what data they might need to make those predictions.

Step 6: Implement Technology
Identify the architecture, systems, and technology necessary to support the business initiative. Understanding in detail the business, data, and analytic requirements helps determine what technologies are needed – and what technologies are not yet needed – as IT builds out their big data architecture and infrastructure.

Source: Artificial Intelligence: 6 Step Solution Decomposition Process by Bill Schmarzo