This document discusses explorative computing and its relationship to management consulting. It provides examples of how explorative computing can be used in management consulting engagements. Specifically: 1) Explorative computing uses computers, programming, and online resources to create models of domains and investigate solutions to problems. It is done collaboratively with domain experts, generalists, and tool experts. 2) A case study is described where explorative computing was used to help a baby product company analyze international markets and identify priority countries for expansion. Various models and analyses were developed during workshops to inform their decisions. 3) Explorative computing is well-suited for management consulting currently due to trends like "digital transformation

1. Explorative Computing and
Management Consulting
- A Love Affair
Presentation @ Digitalist 190322
Fredrik Döberl
Ablona

2. E & M -> Love affair
Case study: Babies
Q&A
Topics

3. My normal day to day work…

4. Ablona
Founded in 2004
4 persons
Focus on knowledge
intensive SME (software,
professional services..)

5. Explorative computing
– Using computers, programming and net resources to create a model
of domain and then use the model to investigate a large space of
possible solutions to solve a problem
– Broad and fuzzy requirements/SLA
– Done with small groups of domain experts, generalists and tool
experts
Example: Hackathons, Design Sprints, Modelling sessions
Management consulting
– A social science discipline
– Advisor to management in organizations
– Implement and maintain processes & systems
Explorative Computing (EC) & Management
Consulting (MC)..

7. Timing
– ”Digital transformation” -> Organizations must be more ”explorative”
(James March..)
Tempo
– Quick results for changing circumstances
Tools
– Wolfram, Python & Jupyter.. (notebooks) that support ”Advanced
Analytics” (math, time series, pattern matching, functional
programming, machine learning, advanced diagrams…)
– Available for non-professional programmers (i.e. management
consultants)
..a Love Affair. Why now?

8. Goto market model
– Calmark
Market intelligence
– Russian Diplomacy Analyst workbench for researcher at Institute for
Foreign Affairs
Industry Analysis
– Acquisition Analyst workbench for X
Company Analysis
– Meridium, Inuse, …
CASES

9. Save babies, see https://www.calmark.se/
CASE Goto Market model- Calmark
Phase 1 and Phase2
launch countries

10. Key questions that drove the exploration
– Lots of births..
– ..can they afford the product?
– ..richer countries, fewer births/woman..
– Where do we want to go? Corruption index
– Which countries influences others? Influence graph
Market segmentation based on this?
(code from modelling session on the next couple of slides,
coding by me during/between sessions)
Workflow from intial meeting with CEO and CFO

11. Lots of births. But what about the female population?
Code that I wrote during the meeting

12. Richer countries -> fewer births/woman.
Where do we want to go?
Searching for all countries at Wolfram Alpha
Known attribute of country

13. CEO ”Been in Laos”, … -> High CI=.. -> Indirect sales (if any..)
Finding the source before the next session
Patternmatching to extract the right data
Mapping to Entity model

14. Findclusters -> 4 segments of countries
-> Typical Managment Consulting
topics per segment:
Pricing, Direct/Indirect sales, Estimated
market shares, Production forecasts
based on these segments
Advanced analytics…

15. Prioritize in the clusters
based on ”x influences c1,
c2…”

16. Added more dimensions
– ”CE”, Healthcare structure, Birth forecasts, Homicides, Poverty, Health
spending, Education,
”Similar to ..” searches based on multiple dimensions
– Which countries are similar to Vietnam given d1, .., dk, ..
Adaption of product, Sigmoid curve instead of ”CAGR”
What else are we doing ?

17. Q&A

18. Background

19. Positive Emotions Attractor (PEA)
Embrace vagueness, contradictions and inconsistencies.
Values in a EC engagement

20. <Resursbilder>

21. Shannon, Turing and Hopper…
– Everything interesting can be represented
by {0,1}
– https://en.wikipedia.org/wiki/A_Mathe
matical_Theory_of_Communication
– All interesting procedures can be
programmed
– https://en.wikipedia.org/wiki/Turing_
machine
– Programming is for everyone.
– https://en.wikipedia.org/wiki/COBOL
Computational thinking – short history

22. Good Strategy/Bad Strategy; The Difference and Why It
Matters, Richard Rumel, 2011
Good strategy has a kernel consisting of:
– challenge
– policy
– action
(similar to standard book Exploring Strategy by Angwin et
al.)
Strategy – An operational definition