Change Management Analytics
By: Ronnie Moshe Rendel
Tags: Data Science, Knowledge Management, Business Automation, Change Management, Business Transformation

Data Driven Methodology for Managing Business Transformation Initiatives

In this article I will present a data driven methodology created as part of my knowledge management team’s mission supporting global business transformations for a Fortune100 company.

Our said objectives for the project were:

Measure employee effectiveness before/after implementation of change

Map corporate departments, roles, and business processes + related KPIs

Lists of CM processes & best practices for enabling for the absorbance of change

Leveraging Existing Business Communication Flows

Our approach was based on using existing business conversations and analytics to build a real time picture of work accomplished and track progress while keeping the data as anonymous as possible, focusing on work segments and business processes instead of individual employees or managers.

In order to accomplish this goal, we needed to establish key corporate and department goals and map them against our given change management timelines, initiatives, and objectives. In practice, our deliverable included the following main components:

Lists of department managers, trainers, knowledge subject matter experts,

Manager/Department Credibility

Company Perceived Credibility

Manager CM Journey

CM Transformations Timeline

Locally validated ideas enabling global transformations at scale

Identify new CM Tracks, User Personas, Talent Management Journeys

Enabling for absorbed change

Increased credibility among the workforce

Root cause analysis for negative impact on workforce effectiveness

Change Enablement Program Creation:

Internally, we worked with our company’s management consulting teams to organize into the following service-delivery consulting lines of business:

Communications & Training

Subject matter experts + smart request/inquiry tools

Business absorption risk mitigation

Service introduction & Stakeholder integration

Change Enablement Communications

Learning & Knowledge Management

Overview of project management and issues/requests workflow & tools

Stakeholder integration & Strategic Solution

Discuss business risk, delivery, and privacy concerns

Key Aspects of Knowledge Management Capabilities

As I mentioned before, this project was owned by our knowledge management team, and in support of the above objective, we ‘codified’ the following internal structure for the team:

KM Process

Each knowledge management engagement follows an account management process composed of the following general sections:

Business Understanding Data Ingestion & Analysis Model Development Client Deployment & Training Acceptance & Data Quality

KM Project Structure

Project Charter & Scope Definition Raw Data Reports, Documents, and Discovery Analytics Model Development Data Features/Dimensions & Measures Business Context Model Analysis Model Performance Internal deployment, integration, and testing Client deployment & integration with other analytics and operational initiatives

Change Management Analytics

Change Management Analytics are proprietary methods & measurements leveraging the client’s existing data capabilities to define, schedule, and manage the workforce impact of upcoming business transformation, providing our clients with a combination of organizational agility & consistency simultaneously.

All of the business entities measurements and data flows are processed through machine learning models and data lakes and presented to corporate management via a corporate knowledge portal (mockup):

Mockup Dashboard for Realtime Corporate Knowledge

Part of our CM analytics assets is a funnel of web pages allowing different members of the organization to create, score, and elaborate on new initiatives.

We also combined the company’s elaborate system of both open and structured employee/management surveys, incorporating them into our data driven change management models:

Combining employee surveys with data driven models

We guided our client stakeholders in building the metrics, tools, and context for discussing global initiative priorities — critical tools for automating CM communication and strategic discussions about upcoming transformation initiatives.

Workforce Performance Measurements

The following is a list of measures & entities sourced from existing enterprise systems and data assets used to quantitatively measure productivity and success of business transformation initiatives:

KM Information Architecture / Documents Structure

We also organized our internal documentation resources into the following sections, we greatly improved our ability to manage increasing complexity:

Project Deliverables

Data Raw Processed Production Models

Documents

Project Data Reports Model Reports Data Quality Management

Code

Queries & Transformations AI & Machine Learning Deployment & Analytics

Conclusions

The resulting organization structure and client centric processes combined into a powerful knowledge management center driving both executive level strategy and tactical business execution for both our own company as well as our clients: