Fast Customer Feedback in Large-Scale SE

Theme 4 Customer Data and Ecosystem Driven Development Theme vision •  Support the advancement of data-­‐ and ecosystem-­‐driven development practices –  to improve R&D management and, –  inter-­‐organisational co-­‐creation of value •  Improve the companies’ ability to continuously validate software functionality with customers –  to increase customer value and R&D accuracy •  Improve the companies’ ability to strategically align with, amplify and accelerate in synergy with ecosystem stakeholders –  to maximize co-­‐creation of customer value Theme 4: Projects •  Project 5: Fast Customer Feedback In Large-­‐Scale Software Engineering –  Prof. Jan Bosch, Dr. Helena H. Olsson, Aleksander Fabijan •  Project 9: Strategic Ecosystem Driven R&D Management –  Prof. Jan Bosch, Dr. Helena H. Olsson •  Project 11: Ecosystemability Assessment Method –  Dr. Eric Knauss, Dr. Imed Hammouda •  Theme coordinators: –  Helena Holmström Olsson (Malmö University) –  Fredrik Hugosson (Axis Communications) Software Center Fast Customer Feedback In Large-­‐Scale SE Reporting Workshop, November 25th, 2014, Gothenburg “One accurate measurement is
worth more than a thousand
expert opinions.”
- Admiral Grace Hopper
Feature Experiment •  Limited (NO) use of a new feature. •  Why? –  Technology-­‐driven development? –  Misconception of user needs? –  Wrong assumptions? –  Misleading metrics? –  Flow vs. wow feature? –  …? •  The earlier we find out…! The ’Open Loop’ Problem Weak link to PM decision-­‐making and feature prioritisation. •  Are the prioritised features used by customers? •  Are the prioritised features generating revenue? Learn (?) Measure Build Technology-­‐driven feature development. •  Difficulties in building smaller increments. •  Difficulties deploying early to customers. High-­‐level system measurements. •  Limited metrics on feature level. •  Inability to track feature use. Interview Quotes ”…there are a lot of assumptions when questions are often answered with ”we belive, or we think this is what the customer wants…”. ”…we have such a vast amount of functions that we collect data from and not a very structured way of harvesting this data, so in the end, it is very difficult to learn from the data…”. The HYPEX Model Business strategy and goals
Strategic product goal
generate
Feature
backlog
select
Feature: expected behavior (Bexp)
implement MVF
Bexp
Gap
analysis
actual behavior (Bact)
no gap (Bact = Bexp)
Experimentation
relevant gap (Bact ≠ Bexp)
Develop
hypotheses
implement alternative MVF
extend MVF
abandon
Product
Feature Experiments: So Far… •  Existing/new feature –  No usage/lack of usage –  ”Wrong” usage –  Uncertainty on ”right” implementation •  Feature focus –  R&D level The$HYPEX$Model$
Business strategy and goals
Strategic product goal
generate
Feature
backlog
select
Feature: expected behavior (Bexp)
Bexp
Gap
analysis
no gap (Bact = Bexp)
implement MVF
actual behavior (Bact)
Experimentation
relevant gap (Bact ≠ Bexp)
Develop
hypotheses
implement alternative MVF
extend MVF
abandon
Product
Sprint 7 Results Fast Customer Feedback In Large-­‐Scale SE Companies Sprint 7: Towards HYPEX 2.0 Sprint 7: HYPEX 2.0 Product portfolio level: Product brand Product level: Product management Feature level: R&D Product portfolio Experimentation Innovative functionality Differentiating functionality Commoditized functionality Innovate new functionality Productize Improve existing functionality Commoditize Remove non value-­‐adding functionality Sprint 7: Challenges And Incentives •  Challenges –  Indirect system access –  Approval from operators –  Organizational/administrative problems •  Creation of feature logs •  Creation of project ID’s –  Difficulties in having customers share data •  Incentives –  Preventive maintenance and support •  Identification of problems and bugs –  Optimization of products •  Feature usage •  Network performance Sprint 8 Proposal Fast Customer Feedback In Large-­‐Scale SE Sprint 8: Develop And Validate HYPEX 2.0 Product portfolio level: Product brand Product level: Product management Feature level: R&D Product portfolio Experimentation Innovative functionality Differentiating functionality Commoditized functionality Innovate new functionality Productize Improve existing functionality Commoditize Remove non value-­‐adding functionality Innovation Actual customer Prio. Feature 1 #4 Friendly customer Prio. Feature 1 #3 Internal customer experiment Prio. Feature 1 #2 Prio. Feature #1 Sprint 8 Focus: Expriment Transfer Productize Differentiation Thank you! helena.holmstrom.olsson@mah.se jan.bosch@chalmers.se Software Center Strategic Ecosystem Driven R&D Management Reporting Workshop, November 25th, 2014, Gothenburg Objectives •  What? –  Improving ecosystem driven R&D management. •  Why? –  Intentional is better than ad-­‐hoc. •  How? –  By distinguishing between multiple ecosystems. –  By identifying strategies for how to manage these. –  By developing and validating an ecosystem strategy model (TeLESM). Sprint 7: Companies 3LPM: Three Layer Product Model Bosch, J. (2013). Achieving Simplicity with the Three-­‐Layer Product Model, IEEE Computer, Vol. 46 (11), pp. 34-­‐39.
Sprint 7 Results TeLESM: Three Layer Ecosystem Strategy Model From 3LPM To TeLESM •  What have we added? – 
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Roles Purpose Drivers Mechanisms Time dimensions Key characteristics –  Strategies •  These ecosystems have different characteristics, different purposes and different drivers. •  These ecosystems require different strategies. Product portfolio TeLESM #1: Multiple Ecosystem Layers Innovation ecosystem Differentiating ecosystem Commoditization ecosystem TeLESM #2: Characteristics And Drivers Innovation ecosystem Differentiating ecosystem Commoditization ecosystem • Collaborative • Exploratory • Risk prone • Less control-­‐driven • Competitive • Efficient • Risk averse • Control-­‐driven • Collaborative • Cost-­‐efficient • Riske averse • Less control-­‐driven Collaborative Less Control Competitive Control Driven Collaborative Less Control TeLESM #3: Time Dimension Start Exernal innovation Collaborative innovation Transfer Internal innovation Monetize Abandon Differentiating functionality Commoditized functionality TeLESM: Three Layer Ecosystem Strategy Model • 
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Innovation ecosystem Who: Customers, 3rd party developers, suppliers What: New functionality with customer value Why: Share/minimize innovation costs/risks When: High market uncertainty How: Open innovation, co-­‐opetition, partnerships Mechanisms: Product platforming, idea competitions, customer involvement, collaborative design, innovation networks etc. •  Characteristics: Collaborative, explorative, risk prone, less control-­‐driven • 
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Collaborative Exploratory Risk prone Less control-­‐driven Differentiating ecosystem • 
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•  Who: Keystone player •  What: Functionality with proven customer value •  Why: Turn innovations into core product offerings, keep internal control over value-­‐adding functionality, optimize for maximum customer value •  When: When innovative functionality have proven valuable for customers •  How: Innovation transfer, R&D management, monetizing strategies •  Mechanisms: Data-­‐driven development, patents, contracts, licenses etc. •  Characteristics: Competitive, efficient, risk averse, control-­‐driven Competitive Efficient Risk averse Control-­‐driven Me-­‐Myself-­‐I Strategy Be-­‐My-­‐Friend Strategy Customer Co-­‐Creation Strategy Supplier Co-­‐Creation Strategy Peer Co-­‐Creation Strategy Expert Co-­‐Creation Strategy Copy-­‐Cat Strategy Cherry-­‐Picking Strategy Orchestration Strategy Supplier Strategy Preferred Partner Strategy Aquisition Strategy •  Increase Control Strategy •  Incremental Change Strategy •  Radical Change Strategy • 
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Commoditizing ecosystem Who: Suppliers, competitors, developers What: Old, non value-­‐adding functionality, operation Why: Share/minimize maintenance costs When: Functionality that has become so integral to the product that it no longer offers customer value •  How: OSS, COTS, inner source, standardization, shared supplier •  Mechanisms: Open platforms and API’s, connecting services etc. •  Characteristics: Collaborative, cost-­‐efficient, risk averse, less control driven • 
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Collaborative Cost-­‐efficient Riske averse Less control-­‐
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COTS Adoption Strategy OSS Integration Strategy OSS Creation Strategy Partnership Strategy Push-­‐Out Strategy Innovation Ecosystem: Strategies Collaborative innovation Internal innovation • 
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Customer Co-­‐Creation Strategy Supplier Co-­‐Creation Strategy Peer Co-­‐Creation Strategy Expert Co-­‐Creation Strategy Me-­‐Myself-­‐I Strategy Be-­‐My-­‐Friend Strategy External innovation • 
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Copy-­‐Cat Strategy Cherry-­‐Picking Strategy Orchestration Strategy Supplier Strategy Preferred Partner Strategy Aquisition Strategy Differentiating Ecosystem: Strategies Internal innovation External innovation Collaborative innovation • 
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Increase Control Strategy Incremental Change Strategy Radical Change Strategy Core Product Offering Commoditizing Ecosystem: Strategies Innovative functionality Differentiating functionality Commoditized functionality • 
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COTS Adoption Strategy OSS Integration Strategy OSS Creation Strategy Partnership Strategy Push-­‐Out Strategy TeLESM: Validation (November 24th) (December 1st) TeLESM: Validation •  Completeness, i.e. do companies employ strategies that are not part of the model? •  Relevance, i.e. do companies use all identified strategies in practice? •  Results: –  Three additional strategies will be added to the model. –  Majority of companies use all strategies. –  Companies mix and combine strategies. –  Don’t know which strategy to pick when. –  Lack guidelines and governance for when to select what strategy. TeLESM: Strategy Validation Sprint 8 proposal Strategic Ecosystem Driven R&D Management Sprint 8 Focus 1.  The selection and combination of strategies –  When does the selection of which strategy to use take place? –  What guidance and governance are used when deciding which strategy to use? –  How can strategies be successfully selected and combined to increase strategic management of multiple ecosystems? 2.  The transfer of functionality between the different ecosystems –  When do you transfer functionality between the different ecosystem layers? –  What metrics and/or feedback help you in taking this decision? Thank you! helena.holmstrom.olsson@mah.se jan.bosch@chalmers.se