Insightful Analytics – The next level
✓Afterspyre provides proprietaryanalytics with machine-learningcapabilities to enable insight
✓It combines Quantitative andSemantic Analytics
✓Incorporates powerful capabilitiessimilar to Graph Database
✓Afterspyre provides a singlepoint of all information (Catalog /Models)
Afterspyre Use Cases
✓Discover and leverage your Organizational DNA
✓Use Ranking Analytics for effective selection of:
a. Strategic objectives
b. Initiatives
c. Market opportunities
d. Vendors
e. Technologies
f. Process Evaluations
g. Product Features
Afterspyre Use Cases
✓Two Model Semantic Comparisons
a. Process listings between twoorganizations during mergers andacquisitions
b. Compare features between two or moresoftware applications
✓Affinity Analysis to identify possiblecause and effects
✓Correlation Analysis to understandstrengths of relationships, e.g. productionand errors
Introducing a Sample Company
Dolbk IncorporatedMultiple business divisions: Manufacturing, Technology,
Healthcare with an in-house dedicated analyst team
Analyst Team Mandated to Build and
Leverage the organizational DNA
Examining Elements of Organization DNA
Supporting Organizational Enablers
(IT Supporting Environment is here)
Product / Service Offerings (Product Models)
Perceived market needs (Market models)
The Processes Used
(Process, Workflow and other action models)
The business environment (Economic and other models)
Why you deliver to the market
What you deliver to the
market
How you deliver to the market
The process enablers
The DNA is captured in Afterspyre’s Catalog
Enriching the Catalog with Attributes
• The analyst can enrich the collected data within Catalog
• Using the Attribution functionality
• Enumerations can be added or selected from the built in library
Why the Analogy-Structure defines Organizational DNA
• DNA is made up of a chain of base pairs of chromosomes
• Afterspyre utilizes collections, on pairs of information or Matrix Models
• E.g. Technology related to processes
• Form the base pairs of Organizational DNA.
• Done using the List / Matrix Model Functionality
Processes - Technology
Risks - Technology
Start with Relationship Base Pairs• A suite of Matrices represents Organization DNA
• Matrices of Relationship Pairs can be created manually or imported by the Analyst
• Matrices relate to each other through rows/columns just like a genome
Afterspyre Discovery of Matrix Pairs
• Afterspyre Relationship Discovery Wizard enables the analyst to auto-discover relationships between Matrices in a unified Catalog.
• Afterspyre also has the ability to interpret these suite of models similar to using a Graph database
Viewing the Organizational DNA
• Like a Graph database, the analyst can navigate thecombinations/linkages
• An analyst can easily generate and visualize these relationships
• Display features provide zoom capability to isolate and zoom into areasof key concern and interest
Organizational DNA Diagrams
• The analyst can step through andfollow multiple paths
• In order to trace the connectionsbetween different key elements ofthe organizational structure
• And better understand mis-alignments and potential issues
Ranking using a Machine Learning Algorithm
• Once issues are identified, Improvement Actions, or Initiatives are requiredto address areas of concern
• Ranking Analytics, based on machine learning algorithms, enable analysts toeffectively analyze alternatives, such as, initiatives, market opportunities,vendors, prioritize product features etc.
Alternate visualization of Rankings
• Analyze, visualize and compare using different combinations ofrankings
• Visual representation, such as 4-Box analysis, highlightrecommendations based on the selected attributes, enabling easyidentification of value adding alternatives
Two Model Semantic Analysis
• Import multiple processes from the respective BPM tools into Afterspyre
• Compare processes with those of the target company
• Identify similarity/differences between two sets of processes
• Ensure the process are suitable for consolidation or integration
Evaluating Process Fit (Possible Acquisition)
Items:
Things in A –not B
Things in B –not A
Semantic and Sentiment Analysis
Affinity Analysis - Which Processes based on Location use are Candidates for Improvement?
7 Materials Processes and 10 Locations
Machine Learning, Affinity Algorithm Capability
Implication is that “Identify Supplier” and “Deliver Supplies” are
commonly related as are “Manage materials” and
“Deliver Supplies”So Deliver Supplies may
be a point of improvement
Correlation Matrix- Which highly correlated items would you focus on?
15 Processes and 7 performance
factors
Machine Learning, Correlation Matrix Algorithm Capability
The high correlation of cost and transport time indicates
an opportunity for improvement opportunity in
transport time.
Business Analytic WizardsSupporting Core and Solution Management Methods
Innovation SWOT
Risk Management
Strategic Impact
Force Field Analysis
Root Cause Analysis
Solve Business
Issues
Draw Clear & Targeted Conclusions
Provides Quantitative & Qualitative Insights
Leverage Semantics Trapped in Other Tools
Robust Analytics
Relate Subjective & Objective Attributes
Shared Catalog
In-built Methodologies
Uncover Hidden Opportunities
Benefits
