Lean Startup in big corporations - Lean Startup Machine Talk
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![[ex·per·i·ment] (/ikˈsperəmənt/) - noun
"A scientific procedure undertaken to make a discovery, test a hypothesis, or
demonstrate a known fact."
Synonyms : trial - test - try - attempt - essay - assay - tentative](https://image.slidesharecdn.com/lsm-presentation-130602130807-phpapp02/75/lean-startup-in-big-corporations-lean-startup-machine-talk-14-2048.jpg?cb=1669324515)
Lean Startup in big corporations - Lean Startup Machine Talk
•5 likes•1,663 views
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The main problems in big companies are well known of product managers and entrepreneurs. Ticketing culture, loss of ownership and loss of empowerment (it's like nobody is never responsible for anything), which all leads to big cycle and lead time. Context : We had all those problems when we started to build chooseyourboss.com within the biggest french web based classifieds company. our marketing team was working for 4, or 5 products at the same time. Their role wasn't always clear : were they working on the product? On the growth only? Our sales were in the same situation : they had a big product making millions, and for most of them, were afraid to sell a new product without any 'proof' that it was going to make it. I imagine that a lot of product managers and intrapreneurs have seen the same situations. What helped us is a framework we crafted during 18 months, that we called experiments. Experiments are testable and measurable actions that allow to validate or invalidate assumptions and hypothesis we make everyday as product managers.
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Lean Startup in big corporations - Lean Startup Machine Talk
- 1. Lean Startup and innovation in big corporations How experimentations helped us align dispersed teams, and assert our assumptions fast.
- 3. LS is about Customer Development & Product Development but we strongly believe it’s worthless without discipline, rigor, and processes
- 4. It needs time and follow up, on everything, from the sales pipe to the feature releases.
- 5. We want small lead times, cycle time and little waste. Why? To assert our business assumptions fast.
- 6. So, what are the main problems when innovating in big corporations?
- 7. Ticketing culture and the loss of ownership, empowerment. It's like nobody is never responsible for anything.
- 8. No follow up. No measurement. No lessons. No improvements.
- 9. We had those problems.
- 10. Well, we still have them.
- 11. But we managed to manage them.
- 12. We built a team with the minimum set of skills to tackle the problems.
- 13. No follow up. No measurement. No lessons. No improvements.
- 14. [ex·per·i·ment] (/ikˈsperəmənt/) - noun "A scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact." Synonyms : trial - test - try - attempt - essay - assay - tentative
- 15. Everything started with what we called lessons learned. It was simple slide decks containing shareable information, as metric reports and objectives.
- 16. Hypothèse Les candidats qui reviennent vont jusqu’au bout MesureConclusion 1/3 de la base est réutilisable. => Effet déceptif + Profil déjà périmé ? Mail On site Open Rate 30 % 55% Mails 240 240 Conversion rate Tunnel d’inscription fini 50% 40% Visits 35 79 Bounce 30% 25% Click rate 40 % 51% Indicateur Prévu Mesuré 28/03
- 17. We needed something better, as shareable, but with more information, like the context, the big picture solution, the actions taken, the metric following, and still, the lessons learned. We called this one “experimentation”.
- 18. Expérimentations en cours Contexte (Problème, Risque, Idée) Acquisition SEM / SEO CANDIDAT RECRUTEUR quali quanti Opportunités DMR non faite par recruteur 10% des candidats avec des offres Envoyer des opportunités aux candidats CANDIDAT RECRUTEUR quali quanti Nouvelles offres commerciales Offre startup (com’ & positionnement produit) Offre essai Offre de stage Offre cab RECRUTEUR quali quanti Commerciaux offline Pas de réussites partagées problème de confiance dans la solution manque d’info au niveau des commerciaux, manque de feedback venant des commerciaux RECRUTEUR quali quanti Commerciaux online 1 seul canal d’acquisition commercial, Commerciaux Offline Manque d’offres, problème de confiance dans la solution Développement du canal Offline RECRUTEUR quali quanti Conférence + Matchmaking Acquisition candidat + image de marque Matchmaking / Conférence dans les écoles, les salons CANDIDAT RECRUTEUR quali quanti Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Plan de contact Base inactive / qualité des profils RECRUTEUR quali quanti Page 8
- 19. Experimentation Responsable : Vincent Contributor(s) : Benoît Informed(s): Context (Problem, Risk, Idea) Envoyer offre en mode pro-actif Pb : DMR non faite par recruteur, 10% des candidats avec des offres Lessons learned Les annonces Web Tech marchent très bien Toulouse / Paris en tête Les opportunités marchent mieux que les DMR. Les candidats ne sont pas recontactés Les recruteurs n’arrivent pas forcément à contacter les candidats. Solution Big Picture Envoie des matchings à 400 candidats Si ils sont intéressés, on les propose aux recruteurs Goals Au 15/01 Candidat avec une offre suggérée: 30% Candidats intéressés : 400 Maiwenn : Tx d’ouverture improve_profile 40% Tx Rebond après improve profile : max 20% Current Metrics 434 dmr acceptées / 433 intéressées (7/02) 2079 acceptées dont 642 dmr acceptées / 1437 intéressées (18/03) Maiwenn Tx d’ouverture improve_profile 49%; (11/04) +5% Tx d’ouverture doublé (11/04) Actions • Suggestion automatique • Plan de relance pour les opportunités automatisé • Suggestion sur le profil public • Améliorer le mail d’amélioration de profil • Rediriger vers edition profil • Template + objet • Suggérer au candidat qui n’ont pas encore eu d’offres
- 20. The last thing we tried, that definitely is a complement of the previous version, takes into account the lack of follow up. It’s what we called experiments. And it worked for us, and definitely changed the way we worked as a team.
- 23. We decided to organize our team around “lessons learned” and “experiments”. And we built the tools to support this new organization.
- 24. The measurable aspect of those experiments gave ownership to people working on the project. The testable aspect helped us focus and align the team around credible and written goals. Follow experiments through time, weeks, sometimes months helped us empower people and make them accountable and responsible for the whole product.
- 25. This was a long process 9 months. We iterated. As everything in LS, we explored, we pivoted to find what was right for us. Annex question : is the journey or the result what made our team stronger? ( you have 4 hours ;) )
Editor's Notes
- Who are we ? built 2 startups, failed one, one side, one building.Trying to use Lean Startup practices since 3 years, after reading Running Lean.Right now : building chooseyourboss as intrapreneurs, building tools for product managers.Important : we are not ayatollahs. At beginning, we were like “monkey see, monkey do”, now we’re a little more souple =) What is important to understand is that every context is different, every market, every product is different, so what we managed to do doesn’t necessarily apply to you. But we believe that there are some lessons here. So don’t forget : there is no “absolute truth”. Lean Startup just like Agile or Lean is a way of thinking, a discipline, not predefined rules to make you successful or not if you don’t follow them.
- What we strongly believe in, after 3 years of practice in our own ventures, and also as product manager in big companies.
- From the idea to the dollars, or at least the lessonslearned
- As Lean intrapreneurs/Product Managers what do we want?Reduce the market risks
- It is important to note that we started, at the really beginning, to build a minimum viable team, with all the skills needed to implement the product, from business to engineering
- We needed to align this team around common measurable goals, and make them follow those ones, even after the “ticket” is “done”.We needed to kill this “DONE” paradigm. And give birth to a new “done
- What we gained here?The measurable aspect of those experiments gave ownership to people working on the project. They understood that their actions will be checked, and a ticket done was ok, but done needed to be “KPI compliant”.Problem, no following, no improvements, but high power inshareability and understanding, + + lessons learned. A lot of informations were needed. Here for example, the marketing was looking at us saying : what was done exactly? It was more, by us, for us. NOT GOOD YET =)
- This was the slide we were sharing to everyone every Thursday, available on dropbox. This was the high level view, with : The problems we were solvingThe segmentThe type of experimentation (quali/quanti)
- What we gained here?Here, there is an indeniable testable aspect. Expliciting clearly the problem, having to write in a small box the big picture solution, and also, the mesurable goals made the people think small, testable and try things differently. This aspect helped us focus and align the team around credible and written goalsThe main problem here, is that it was definitely lacking follow up, and be able to understand what action change what metric sometimes. Plus, this was still too clunky.In ticketing organisations, one day you talk to someone, one other day to another one, for a various number of reasons. And while some experimentations were lasting weeks/months for some of them, people were coming back and saying we should do something we already did weeks back, and we were on for explanations why we wouldn’t do that, but without the “data proofs”, and the lessons learned of that time, which would have been seriously helpful.
- What we gained here?The fact that you need to follow those “experiments” through time, weeks, sometimes months helped us empower people and make them accountable and responsible for the whole product. They understood that we were iterating on everything, constantly trying to improve, or kill, or create new things that would bring value to the customer. They were definitely still in the ticketing culture, but for operational purposes (who does what), but not for product management anymore.This definitely helped us to implicate the marketing way more than the other solutions, because anybody could come on the experiment and understand what happened, through time, and quite easily. Every action was linked to an incomeThis is not only actions on the mail but on the product itselfWe follow this mail + the landing + the high metrics > everything was shared with the sales to build up powerful presales speech for instance
- Conlusion
- What we achieved?
- Butdon’t forget =)