Shaping the crazy future in the IT sector through directed evolution of software systems

Transcription

1 Shaping the crazy future in the IT sector through directed evolution of software systems Stelian Brad, PhD (Engg.), PhD (Econ.) President Cluj IT Cluster

2 the crazy future my risky job for today to introduce some driving rules that might help to design sustainable product & business solutions in the moving sands & storming sea IT world

3 low-predictable IT business world platform battlefield more and more platforms..??? platforms nested into platforms high cost of multiple-platforms very tight space for strategic and operational errors very short time for any competitive advantage difficult to generate clear differentiation strong networking effect winner takes all how to avoid fashion practice? which is the best practice in this context?

4 Rule #1: Look for strong stickers to better understand patterns and lines of evolution

5 borderless enterprise real-time information empowered user life-cycle value Need to develop sustainable IT product-service strategies in strong symbiosis with these influencers software-defined anything cloud/client architecture mobile device diversity web-scale IT social networks virtualization interoperability big data analytics semantic web mobile apps smart machines personal cloud hybrid cloud and IT as service broker internet of everything ********* computational needs in various industries strong influencers from IT product systems to IT product-service systems

6 Rule #2: build your future by breaking through the evolution

7 more and more focus on RAD Frameworks for Eco-System Computing for software renovation, re-engineering, and migration of legacy systems (Unified Apps on a Single PaaS) rethink of solutions that scale up to very large distributed systems involving multiple languages and levels of abstraction, a large number of developers and users, and huge amounts of data support for co-evolution, traceability and synchronization between all artefacts used and produced during software development automated support for software evolution and maintenance more social & focus on Unified Social User Experience (UX) more big data-driven & hybrid big data backend technologies need estimate and predict changes, effort and productivity advanced programming languages for fast / productive programming libraries / open source / infrastructure agile methods for product development dynamic software adaptation more cloudy & more mobile breakthrough software development agile & resilient

8 breakthrough traditional design design for excellence Deep Customer Segmentation More Content for the Customer-as-Buyer Deep Understanding of Buyer-as-Purchaser Software Design with User Experience Upgradeability User Experience after Sale Usability Correctness Learnability Serviceability *** Efficiency Intuitiveness Functionality

9 5 8 more profit from business model innovation than from product innovation from a traditional software product to a cloud solution and integrated soft-hard solutions give software itself for free and make the money by selling integration, deployment, support services and other goods build free platforms that create a strong customer lock-in & sell services sell expertise and content instead of selling only hardware and software B2C Software Companies new revenue streams as software becomes free hybrid businesses B2B Software Companies IaaS PaaS SaaS (integrate) safety, control, libraries, tutorials, plug-and- breakthrough traditional business models move outside the comfort zone

10 freemium consumption subscription tiered loyalty discounts perpetual license prepayment for discounts bundling module discounts volume discounts highly customized pricing offer price premiums duration commitments discounts periodic discounts for innovation adoption regional pricing market deep segmentation regional promotions channel discounts upgrades grades breakthrough business monetization maximize value for each customer

11 breakthrough traditional innovation focus on lean innovation apply Probe-Test-Evaluate-Learn-Refine cycle pivoting both product and business model clear demonstration of value-for-money market-driven evolving prototype more focus on WOW and KANDO effects not only technology :: more expert content

12 Rule #3: Adopt reverse thinking paradigms

13 extended view of innovation innovation is also about passing crises without compromises and losses big crisis point big crisis point big crisis point big crisis point dynamics is becoming too high don t increase the speed along the stream; speed-up the right direction

14 dynamics back-up functions redundancy contingency plans strategic alliances lean prototyping dynamics reliability asymmetry : more pivoting concurrent development fast pre-planning discard and recover teams complexity dynamics strategic alliances strategic planning in open source ecosystems collaborative networks holonic organization capacity don t let dynamics to push you on its way use more shortcuts and wormholes

15 zero-sum competition positive-sum competition to be the best compete shoulder-to-shoulder some win some lose competition undermines profitability in many cases to be unique (significant different) compete on strategy all (more) have success competition leads to extensive servicing of customers and more customers better served a new paradigm in strategy

16 current thinking and planning paradigm progress from the current state future thinking and planning paradigm deviation from the ideal state the big challenge: how to define ideality of a certain characteristic? hard to define ideality? don t worry define targets close to ideality! now planned now planned ideal a new paradigm for thinking and planning

17 software systems are developed in an evolutionary way nobody knows the finality of a functionality; in most cases we start with something in mind and end up with something completely different evolution can follow many ways in this context, which is the ideal system? ideality is the driving force to change the way of thinking ideality is good to push innovation to its limits, not to necessarily reach it ideality? where to look for it?

18 Rule #4: Respect the laws that govern evolution

19 history tells us about behavioural laws in software system evolution Feedback loops Continuing change Increasing complexity! Declining quality! Self-regulation Conservation of familiarity = as a software system evolves, all stakeholders focus to keep control of its content and behaviour to achieve satisfactory evolution. Excessive growth diminishes control, therefore the average incremental growth remains invariant as the system evolves Continuing growth Conservation of organisational stability! Conservation of organizational stability = the average effective overall activity rate in an evolving software system is invariant over its lifetime Conservation of familiarity!

20 increase intelligence and autonomy intelligent and higher autonomous system transition to higher-systems stable system in continuous development, but closed system with complete reconstruction :: pass to micro-levels stable system :: include encapsulated-closed sub-systems activated when running transition from an open system to a closed system stable system in continuous development :: new principles transition to new functioning principles :: instability complete reconstruction of the system stable specialized system in continuous development development of specialized systems stable system in continuous development consolidation of sub-systems into a super-system independent sub-systems laws of software system technical evolution

21 define the evolution strategy for your system even for open source systems this can work towards autonomy more useful functions principle of balanced evolution might be a wise strategic approach less harmful functions more efficient system processes 11 3 more application fields more efficient system environments 10 SE 4 higher integration into other systems towards multi-levels 9 5 deeper harmonization with other systems eliminate contradictions in the system better use of resources increase of dynamicity and controllability where and how to direct evolution?

22 Rule #5: Focus on robustness to fuel agility and resilience

23 Act creatively and broadly to intentionally destroy your dear system System now Plan the future Draw the future system Identify weaknesses and potential brilliant failures Reformulate a robust map of the future system robustness solidity to intentional destruction

24 multiple futures Robustness principles Future 1 P(1) Optimal SPSS strategy 1 piloting System today Future 2 P(2) Optimal SPSS strategy 2 Final SPSS innovative strategy Key influence factors and their potential future instances Future n P(n) Optimal SPSS strategy n adaptation Hybridization with inventive solving of conflicts between strategies SPSS = Software Product-Service System

25 Short term Medium term think in terms of multiple futures and allocate %profit on robustness understand natural directions of system evolution understand the plausible possible monitor the influence factors create evolutionary resources create evolutionary resources create evolutionary resources innovate innovate innovate Long term plan short-term actions and results crisis plan short-term actions and results crisis plan short-term actions and results crisis act nonlinear act nonlinear act nonlinear prepare to control the crisis prepare to control the crisis prepare to control the crisis design towards proper directions of system evolution control directions of system evolution control evolutionary resources unpredictability requires higher productivity and agility don t predict the future. build it

26 General rule of directed evolution 1. Collect historical data Past 4. Take decisions Present 2. Diagnose lines of evolution 5. Support the evolution process Evolutionary resources Future 3. Formulate differentiated and robust solutions to face with multiple futures Don t omit disruptors Control of Evolution is the key to Success Present is the key to Understanding Future is the key to control Evolution understand Past Past is the key for better foresight Future instead of conclusions

27 contact M ::