People Analytics IO HR Transformation Service
We provide specialized expertise necessary to identify the root of business problems and translate these into clear technical requirements and support you in implementing them. We design full stack people operations and people analytics work environments including integrated data collection, data management, data analysis, and data delivery system functions. We address the hard problems of data, including: unintegrated HR systems, non-existent or mis-aligned methods & definitions, data quality problems and complex security and privacy needs (including need for third party confidential survey data handling). We design and implement a technical architecture to systematically improve organization and process feedback in the following ways: 1) total range of organization related topics that can be analyzed by the organization, 2) speed of analysis, 3) certainty of analysis, 4) efficiency of analysis, and 5) uptake of analysis, designing client people analytics operating environment and support model to provide systematic, credible, timely, business-outcome-directed insights. More details on the how below:
We help you put in place high-powered systems that can continue to produce systematic dynamic insights over time without us, as opposed to spend off time to produce “one offs” and “just one more time” reports (but if you want us to, we can).
The design also considers the unique needs of people data in ways that traditional data environments designed for other purposes do not.
We use and we facilitate a modular design premise that provides a suite of interconnected analysis services on relatively inexpensive, nimble software as a service applications that can added to or changed over time. We are advocates of a new class of analytics products, which for lack of a widely recognized descriptor we call: problem specific analytic tooling or micro analytics or modular analytics - tools tightly embed with the places and times decisions are made. The connectivity of the environment increases the overall value of any single application, while at the same time reducing dependency on any single application. This is better for you. The elements we design anticipate new data and means to express that data in the future as we work to put each element in place.
1 facilitate people analytics learning, change management & Alignment
People Analytics is the new people management operational model/strategy, which requires investment in new learning, change management and re-alignment of goals, processes, roles and responsibilities.
Conduct training (or other appropriate learning methodology) to introduce people analytics to all impacted stakeholders ranging from entry-level transactional HR operators all the way up to executives.
Conduct stakeholder interviews to develop perspective and align people analytics with the business: Identify the unique characteristics of the customer’s business context, organization context, business model, current and desired key product differentiators, real or perceived people opportunities/issues/problems. Use this information to propose people analytics objectives for optimal impact in the most direct path possible.
Work with client to define short and long term people analytics operating model: Operating model decisions include: A) centralized, decentralized or distributed? B) waterfall or agile? C) insight orientation (deductive) & dashboard projects (inductive)? D) in-sourced and outsourced components? E) Technology build, rent and buy decisions?
Offer options and examples and facilitate decisions for how the client will manage people analytics in the short-term and going forward. We will assess capabilities and budget and will put in place a 90 day plan, 180 day, and so forth...
2 Define Key Jobs & Key Talent Segments in support of Business Strategy
Research, offer options and facilitate a decision on Key Jobs and Key Competencies focus. When complete this will connect the HR strategy to intended product or service differentiators. Key Jobs and Key Talent become a central driver of people analytics design and the value of insights. Key Job and Talent segmentation is conceptually similar to the purpose of customer segmentation - something for everybody is something for nobody.
3 assess human resource and people analytics current and desired state
Assess current and desired future state of:
Diagnostic Insight Capabilities
Analytical Support Competencies
Analytical Maturity Capability
Data Collection Systems
Data Management Systems
Data Analysis Systems
Data Delivery Systems
Dashboard Design and Utilization
4 design people analytics roadmap
Propose roadmap for modern modular state of the art people analytics technical work environment (“people analytics kitchen”) that covers data collection, data management, data analysis and data delivery layers and scales from basic to advanced in under 2 years.
Modular plan will allow outputs that illustrate the value of people analytics in risk-gated phases.
Each added component will integrate with and build upon the previous components in the people analytics kitchen - reinforcing previous time and resource investments, as opposed to competing with them.
5 design Measurements
Design the fundamental measures of human factors. Define concepts, operationalize measures, assemble data, analyze & obtain feedback on in iterative sprints.
Attraction: Talent Acquisition & Selection
Activation: Capability, Alignment, Motivation and Support (CAMS Index)
Attrition: Employee Commitment & Attrition
Employee Lifetime Value, Activated Percent & Net Activated Value (NAV)
Candidate and Employee Journey
Elements of Employee Culture and Climate
Job Factor Analysis
Identify Job Families
Identify Job Levels
Identify Key Jobs
Identify Key Tasks
Identify Key Performance Factors
Identify Key Competencies
Span of Control
Key Performance Indicator Surveys (KPI) and Key Driver Analysis Surveys (KDA)
6 Design segmentation
Design segments to produce contextual relevant insight for key problem focus and business strategy intersections.
Define, operationalize and validate relevant business and problem related segmentation in iterative prototypes.
Iterative prototype development is required to obtain the feedback necessary to define segmentation to produce insight for the problem focus while at the same time ensuring the needs of intended report & analysis consumers and other downstream stakeholders are met.
Based on feedback the real work can be begin, including: designing methods to acquire additional segment-able data, changing data in systems, documenting a data transformation workflow and/or developing a mediating interface that allows for dynamic re-aggregation of base segment-able data determined by user input.
7 implement Single source of truth
The “people analytics kitchen” will aggregate all relevant data into a single data warehouse environment designed to facilitate cross source insight with standardized report delivery through modern interactive visual self-service interface with user-rights management and drill-down capability designed for the special needs of HR data.
In addition to standardized dashboard reporting, the “people analytics kitchen” will also provide an analytical data store with data re-structured for application of statistics or machine learning - e.g. a columnar denormalized data set.
8 Design ROle-CeNTERED DASHBOARDS
In theory the same data can be simultaneously repacked in multiple dashboard designs, however design effort will be extended to design dashboards around the special needs of roles, as opposed to dividing dashboards by metric category or data source. Examples of role that have unique data needs include the following:
CHRO / HRBP
Total Rewards Specialists
Talent Acquisition Specialists
Director+ Business Leaders
. . .
9 DEsign key performance indicators (KPIS)
The primary purpose of a KPI is to evaluate ongoing success at achieving some pre-defined objective. By definition a KPI is important – A) either having previously demonstrated correlation to a desired business outcome, B) having a universally agreed theoretical connection to a desired business outcome, or C) clearly representing a self-defined business value that is important.
Often people related KPIs are measured by survey - be they agreement with a statement or series of statements. Activation, Engagement, Commitment and Satisfaction are examples of survey index based KPIs. By definition, a KPI should have specific and narrow focus- therefore a KPI survey should be constrained to only a handful of questions - 10 items or less for example so a KPI survey is suitable for rapid, repeated, ongoing administration with little cost.
The primary method of analysis of a KPI survey is to report the ongoing trend (as a whole and by company segment), compare segments to each other, and provide a basis to correlate a regularly collected survey-based employee KPI with other operating and business measures captured in the same segment frame and time frame.
A KPI can be measured regular in a survey devoted entirely to just capturing this one KPI, and a KPI measure can be added to a bigger, less frequent survey. The reasons for conducting an independent KPI survey and a larger survey are different.
10 DEsign and implement key driver analysis on KPI’s
Design and implement Key Driver Analysis to provide a perspective on what actions you should prioritize to achieve maximum impact.
In a Key Driver Analysis (KDA) survey, the primary goal of the survey is to understand which of many different survey items best explain or predict a chosen consequence the company cares about – a chosen KPI. A KPI serves as the focal objective of Key Driver Analysis (KDA) survey, but do not confuse the purpose, design and analysis of the KPI survey with the KDA survey – the two are used together but totally different.
Contrary to widespread misunderstanding, the purpose of including many items on an employee survey is not to evaluate opinion on many items relative to each other - instead it is to evaluate the relative strength of the item variance to explain or predict the variance in some behavior or consequence. You ask so many questions so you can evaluate key drivers of a KPI, not because you believe all the questions on the survey should be treated as their own KPI.
Survey questions should be changed out over time based on previous analysis and theory. Once the items from the KDA have been analyzed to determine what KDA items are most and least important in explaining (or predicting) the KPI, the next KDA survey should be modified to remove those items that have little value in understanding the KPI. The removal of items, frees up room to test new items, which may prove to be more valuable than the old items that you have removed to make way for the new.
11 Model the abc’s
Develop, test and improve models of the Antecedents, Behaviors & Consequences (ABC’S) of human factors for each KPI and/or human factors of performance in key jobs.
12 REFINE EVERYTHING with INCREMENTAL ADVANCES IN science, statistics & machine learning
Use more sophisticated analytical methods if they deliver more value ...
Implement predictive people models
Implement “Rapid Prototype and Experimentation” concept.
Apply more advanced statistics or machine learning for prediction, prescription, optimization - as needed.
Apply Compensation and Benefits Conjoint Analysis - as needed.
Expand people analytics into any previously unsupported HR Centers of Excellence including Talent Acquisition, Compensation, Benefits, Employee Relations, Diversity, Health & Wellness, Learning and Development or Organization Design.
13 identify optimal decisions and evaluate actions
Implement a single metric as a measure of progress that all people decisions and actions can be related to and evaluated against.
Absent a better option identified in discovery and implementation, we will test the Net Activated Value (NAV) premise invented by Mike West. This is of the nature of what the Bain NPS analytics are, however for HR.