First of all this is my last chance to graduate my MBA, please support me carefully as i must success… attached “Business_Research_Project_FINAL_+Failed+.PDF” is my failed MBA business research, below the comments from my Supervisor, why i am failed; Feedback from: (Supervisor) Justification of study in terms of theory / practice: the study is highly timely and appropriate for investigation – it touches on important conceptual, theoretical and practical aspects of artificial intelligence (AI) management and innovation strategy. AI needs careful definition at the outset and framing within wider contemporary technology management issues. The company selected for investigation needs further introduction – what does it do and how ? How – specifically – will AI impact ? Objectives and research questions: The research questions are appropriate – the stated focus of investigation on ‘service desk operation’ should allow for an in-depth examination of a particular (key) operational area. The RQs need to be translated into focused information-gathering through expansion into carefully considered interview questions and/or questionnaire design.
These can be designed in a tailor-made way to illicit insights form different staff / customer groups. Report structure and narrative: The report structure is broadly appropriate. The link between AI and innovation in business development needs to be made clearer and could be usefully explored further throughout the report narrative. The use of English is unclear in places and overall the report lacks focus. There is some non-relevant content in some sections. Literature review: This offers some helpful perspective and some interesting / important business development issues around AI and innovation strategy are touched on. The potential advantages of AI are presented and the use of examples is helpful. Some definitions are required (e.g. ‘deep learning’). AI is evolving rapidly and more up-to-date references would be helpful. Too many (370+) references are listed at the end – are these all cited ?
Research methods: A detailed case study approach is appropriate. Avoid generic research methodology considerations and focus on exactly what was done and why – provide clear details. The interviews need more explanation – who was interviewed (role ?) and why ? Not clear why broad financial results are included – how do these help to answer the RQs ? (the author recognizes that “the analysis of financial statements (of AtoS) does not reveal much that can explain the impact of AI on innovation & strategy”). The term “archival research strategy” requires more explanation / justification. Findings / results: Some relevant insights from interviews are presented – again, who was interviewed and why. The quotes are very general in nature – more detail and linkage to RQ’s is required. Analysis of findings / synthesis with literature review (discussion): The cross-cutting nature of AI is usefully explained. Some helpful general points are made – this section lacks focus though. Key areas (e.g. intellectual property considerations) need to be interrogated further given their critical role.
The author states that the “collected data is analysed using various statistical techniques such as content analysis” – is this true ? ‘Content analysis’ requires definition. Conclusions and recommendations: These sections need expanding and the recommendations lack focus – they do not relate (specifically) to the findings of the research undertaken. How (specifically) can AI help address customer needs / service at AtoS and/or assist with operational matters ? Overall comments: The highly timely nature of AI makes it a great topic for investigation and the work touches on some important contemporary considerations around innovation management and strategy. Unfortunately the work lacks focus and reads like a lengthy essay rather than a focused research investigation. How – exactly – might AI help to address customer service needs in AtoS and what are the lessons for other companies ? previous orders , please download all documents as well should be helpfully… 7381442 7372189 7242871 important uploads and information 7180722 Havard
Reference (for each fact reference accordingly ( name/year/ page) use min. 40 – 60 Atos Website links as reference please Company Link: https://atos.net/de/deutschland specific to AI company link https://atos.net/en/products/codex-ai-suite Link to Ascent 2020 produced in 2016 by Atos Scientific Community: https://atos.net/content/mini-sites/journey-2020/index.html Link about the Atos Scientific Community: https://atos.net/en/insights-and-innovation/scientific-community use the meetings notes below Meetings and discussion between Jan. – Jul 2018 Monchalin, Eric MI technical lead architect meeting 5th January 2018 AtoS creates with MI (Machine Intelligence) the understanding of AI (Artificial intelligence) to understand the step by step process by AI, for that the input will be analyzed and outcome controlled to guarantee the correct process… in future there will be nothing what we can not reused in MI to AI, important is always the input and expected output what we can control with MI… our budget is over 3 years 200Mio, what we get additional sponsored by the government, customer focus is here not given! target would be to control MI to get automatically output from AI by any data input… Caminel,
Thierry AI Overall Lead meetings on 7th March, 10th May, 15th June 2018 7th March Summary: AtoS kick very late in that segment and is still try to get the right position.. We working in a partnership with Siemens (50/50 budget) by 500Mio over 3 years and sharing both our output and innovations, hereby is Siemens focusing on Mindsphere and Atos on Security innovations… target is to catch our compitors what are running in upfront (with an earlier start), what will be not easy… please contact Oble, Frederic for more details on the Project… additional materials are shared 10th May During the discussion and meetings with others i would like to ask how organized we are, as i shared my personal opinion and get from Thierry confirmed that the issues in AtoS is;”we are still not organized to kick off pro-actively and every division is focusing on their own needs, no regular meetings are set up or progress tracked on a proper way” personal note: Atos to be success is to shortly to streamline all divisions under specific focus and requirements, have regular meetings to share knowledge and lessons learned, after your (my name) discussion i agree that will be shortly arranged as you focus that out in our regular discussions Oble,
Frederic AI Project Manager meeting 21st March 2018, 25 June 2018 21st March: as project manager i see many challenges on AI, we start late and have no customer or even internal organisation set up now, we run like chicken around and all divisions are still under they own org. structure for AI… we must focus to prior the AI internal in our company! I will have a meeting with the CxO, CEO, COO of AtoS by mid of June hopefully to get the focus on our Project and upcoming visions, as we are in cooperate with Siemens the knowledge sharing is still single site done (by Siemens), what will be run in that cooperation not for long! personal note: officially we have no AI project implemented yet globally; accept: Olympic games with Cyber attack AI, where no one will be allow to share anything with you! 25th June: meeting on AI happen but no further details as of cooperation with Microsoft as a partner now for AI as well, (details shared in Media, please add), postponed to next meeting in 3rd October 2018 Olympic Games CxO AI Lead ISEC(no name) 20th April 2018
There is no chance that I can share with you, as this project is under top Security, i can share some figures on Cyber attacks what we have prevent on our System… (please check presentations attached) no further details Thronicke, Wolfgang Healthcare Lead division in AI and Service Desk Germany meeting on 22nd May 2018 AI/MI will come more and more in focus under Healthcare, we had the chance to implement a chatbox what are query health data from patients via phone (more details in *.ppt) Healthcare company (no name) who ask for regular checks on diabetes or heart attack patients for calls with particular questions to analyze them and if required to make asap appointments with the doctor/hospital, send regular reports to the hospital in the patients folder and mark all unregular events, remind customer on the regular check appointments and review further improvement on the system… implementation was done by February 2018, so our main focus this year is to stabilize the system and review for improvement,
Financial data is not allowed to be shared 🙁 (only customer cost reduction can be shared based on efforts, expected by H1 2019 to reduce the nurses/analyst by 50%) we are happy to see the go forward with AI and hope to support more and more in that sector… Tan, Daniel CxO of APAC Service Desk meeting on 20th June our global initiatives AVA (you will find in the slide decks the details please add) are still in internal pilot, to have an artificial help desk what would give instructions to our customer end users is still an acception criteria on each customer profile (or country), as the cultural acception is be done by human… we had previously an voice authentification process running over our system to allow end users to authentify themselves and reset their password according to that; outcome was that the end user acceptance in the first 8 month was great with reduction (-20%) on call volume to an service desk engineer, we saw that our analyzes looks success for the first 6month, but found out after that the end user who are use to it, returns and start to choose an Service Desk engineer to talk to… after approx. 1.5year the voice authentification stopped as there are not enough end user to use it, the previous reduction came back to normal… so result was only temporary…
AI intelligence to get run overall for all end users is in my opinion still an acception criteria depending on the end user our region APAC (Asia, Australia, Middle East and Africa) will have different culture acceptions… China, Korea, Japan, Singapore would be for sure a “GO” by other countries i have a concern on culture acceptance in my view… In general i see AI as an future innovation, what will change the Service Desk culture at all, AI will run 7/24/365 without getting tired if we maintain the system, but the analyses of an human feeling is still not transferable to an AI (System) what would effect positively understanding criteria to an end user, Business perspective is that we must go the way over AI, to market price reduction and cost reduction, but for monitoring function we are already investigating to operate more automatically with AI and will kick off a project in H1 2019 to prevent proactively via our technical tools (e.g. ticketsystem) Service Level agreement breaches, what would help our engineers to monitor and work effective as well prevent us on penalty payments (cost)… overall the GO forward for 2019 in my view…
All in all i am involved in the future work place from AtoS there are collecting analyzes and data, i assume that we hear again maybe in H2 2019 as we hope to have than more details for you… Personal note: Co-existing of AI and Service Desk for the next 5 years minimum in my view as the acceptance on human connections are still required for our generation Macry, Jay CxO of Global Service Desk meeting 22nd June as you had already a meeting with Daniel and the focus noted, we are looking global forward to proceed monitoring AI´s to protect our Service level agreement pro-actively as well future AI as a full running Service Desk the interactions on the progress is actual zero, AtoS is in AI with customers still on reactive position instead of proactive, we are looking forward to get this and marked the topic on the CxO sterrCo to our global COO Gral, Eric but still no result as we try to come out from negative numbers in our division… Duhme, Jens public Security Lead division in AI/MI meeting on 10th July 2018 we start by H2 2019 with deep learning analyzes on a potential customer request to implement security control on public locations (airport, train station, public places) we are still in the baby shoes and will catch shortly our competitors as we have already a lots of data hosted, now is to start to feed MI to get AI up and run, expected in Q2 2019 to roll out by all our customers (who are allow us), potential customers can not be shared,
1st potential revenue expected with 200Mio by Q4 2019 (and beginning 2020 per Halfyear +300Mio) with cost of One time implementation of approx. 300 Mio for One time cost implementation, running cost will be reduced by 25% potentially and effects will be felt by H2 2020, what would/can be reflected back to the customer by 2021 Security will be in future the main focus on globe our division for the Olympic games run already pilots with AI successful on cyber attacks and we will do these shortly as well on our public sector successful… personal note: Security will be more and more driven by AI and will give only an minimum requirement on human efforts, as the AI is more efficient as human eyes… so they will act only on alerts, main challenge and focus for all companies would be in future to secure now AI on cyber attacks… Eric, Gral no appointment possible, many times request without an result by questions please write me an email
