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It’s not how you bowl, it’s how you roll ! BAM! Wat was het weer een supertoffe avond samen met alle collega’s. Eerst een stevig spelletje bowlen met bubbels voor de winnaars. Daarna lekker eten met een glaasje om te klinken op elkaar. We had a blast! 😊😊😊
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Recentelijk organiseerden we een in house SAFe Agilist opleiding voor een groep medewerkers.
Interessante en ‘must have’ kennis om onze klanten die in deze setting werken en denken te ondersteunen.
Het Scaled Agile Framework is gemaakt om zoveel mogelijk mensen in de organisatie te betrekken bij het ontwikkelen en opleveren van bedrijfsoplossingen.
SAFe draait om je snel kunnen aanpassen, zowel op het gebied van snel veranderende klantvraag als op het gebied van nieuwe technologische ontwikkelingen.
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Konato heeft in februari een gastcollege gegeven bij Erasmushogeschool Brussel. Het doel was de studenten toegepaste informatie op weg te zetten in het domein project management. Dit in het kader van hun integratieproject om zo hun project structureel te leren indelen, afhankelijkheden leren ontdekken en afstemming tussen de teams te verzorgen.Door toepassing van user story mapping en met de basisprincipes van project management in het achterhoofd was deze oefening geslaagd. Daarnaast werden tools zoals Jira, Confluence en Bitbucket ter beschikking gestelt zodat ze de studenten hun project verder kunnen uitwerken met de nodige tools. Dank aan de collega’s Nico en Maarten, de docenten van EHB maar zeker ook aan de studenten. We kijken al uit naar de resultaten van het integratieproject ????
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Intelligent automation (IA) is seen as the next phase of process automation. A few years ago, robotic process automation (RPA) was introduced in many industries across Banking, Insurance, Retail, Logistics and Telecom. Although we see that many traditional RPA deployments are still failing. Reasons are complex business processes, including many rules, exceptions or even processes which are not known end-to-end. Introducing only an RPA solution will not solve this issue of dynamic processes. A proper process management is still needed in the organizations to make the process automation successful. A process centric view is still needed from the beginning, process analysis and optimizations are still part of the solution.
Besides this, the operational costs of a process automation are still increasing in organizations. Changing UI’s, processes, forms and documents will impact the automated tasks. The introduction of intelligent automation can solve these issues. These tools can recognize changes in forms, UI and processes by using AI and can correct the automated processes by using machine learning.
Intelligent process automation, supported by process management will become rapidly the next-generation operating model. We see that vendors like UIPath, Blueprism,… are adapting their tools, so the next phase of digital transformation can be started.
– Nico Schaetsaert
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Bimodel IT is a two-tiered IT operations model which was introduced by Gartner around 2014. It defines the two tiers as “Mode 1, traditional and sequential, emphasizing safety and accuracy, also referred to as exploitation. Mode 2 is exploratory, nonlinear, emphasizing agility and speed.
Each mode will require a different management approach. Processes, organizational structures and people will be different. The pitfall of this model is to just start splitting the IT-systems into these different modes. Splitting the IT-landscape in legacy systems, CRM, ERP, mobile apps,… . Two separate IT groups working at different speeds will not lead to organizational performance. This problem is already raised in many academic reviews on ambidexterity in organizations. It is the balance between exploration and exploitation which will lead to organizational performance.
This shows the need for a proper IT governance, organization structures, hybrid models combining best of both worlds. Forcing an organization into a ‘exploratory’ mode will result in organizational issues, impacting the performance of the organization. Don’t forget that ‘innovative’ companies like Apple have supporting processes which focus on efficiency otherwise they don’t manage the selling and delivery of million products each year. They succeed in combining the two modes and are not only ‘innovative’ as they bring their products into the world.
Digital transformations will handle the questions how to reach this equilibrium, where to start? Focus first on the transformation of the legacy systems? Shift to SAAS-models? Which IT project governance to use? One size doesn’t fit all, therefore the management of an organization needs to be aware of these choices, a proper enterprise architecture will guide in this process. Key is the alignment of the business strategy with the IT-strategy. Digital transformation is not only introducing a mobile app into the organizations or start working in Scrum teams. It is about focusing on the right organizational change within the company.
– Nico Schaetsaert
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Ons teamweekend was er weer boenk op! We liepen over vuur, we vochten tegen zombies in een virtuele wereld en we zwierven ‘s nachts door de bossen van Nadrin. Avontuur en plezier in het kwadraat. Collega’s, jullie waren de max!
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Afgelopen vrijdag gaven we een gastcollege aan de Erasmus hogeschool Brussel. Het was een boeiende en leerrijke wisselwerking over hoe een project op te starten, user story mapping, MVP’s , Miro en Atlassian … een hele brok knowledge sharing, waar theorie en praktijk elkaar ontmoeten. Dank aan onze collega’s Nico & Joren en dank aan EHB for having us ???? it was fun!
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CRISP-DM is the de facto standard for developing Data Mining (DM) & Knowledge Discovery (KD) projects and is thus also the most used methodology for these specific projects.
It arose after a group of prominent enterprises (Teradata, SPSS, …) analyzed the problems and obstructions that occurred during DM & KD projects. Subsequently, they proposed a reference guide to develop projects of this nature which then became CRISP-DM (CRoss Industry Standard Process for Data Mining). It is vendor-independent making it applicable to solve any DM related problem.
CRISP-DM defines six phases that need to be carried out during a Data Mining project.
Business understanding: Understanding the project objectives & requirements from a business perspective and converting this knowledge into a DM problem definition and a preliminary plan to achieve these objectives.
Data understanding: discover first insights and detect interesting subsets to form hypotheses for hidden information.
Data preparation: Transform your data into a usable form. Contains all the activities required to construct the final dataset from the initial raw data. If you proceed to the next phase without proper data preparation, your results will never attain the aspired results (garbage in, garbage out).
Modeling: Select and apply various modeling techniques on your data set. During this phase, you usually take a step back to the data preparation phase because some techniques have specific requirements on the form of data.
Evaluation: Evaluate the results of your model thoroughly and review the steps taken to build it to be certain that it properly achieves the business objectives which you defined in phase one.
Deployment: Deploy the model effectively, automate it, plug it into business processes and discuss it with the people that will be using it.
However, the CRISP-DM model still has room for improvement. Other models based on CRISP-DM propose alternative/additional phases like the Automate phase which focuses on generating a tool to help non-experts in the area to perform Data Mining & Knowledge Discovery tasks.
Another example of a phase that is not covered by CRISP-DM is the On-going support phase. It is very important to take this phase into account, as DM & KD projects require a support and maintenance phase. Maintenance can range from creating and maintaining backups of the data used in the project to the regular reconstruction of DM models. This is because the DM models may change whenever new data emerges, which may in turn cause them to be less applicable.
Nonetheless, changes like these (e.g. adding, renaming or eliminating phases) are being considered for the new version (CRISP-DM 2.0).
After comparing this process model to others (especially Software Engineering process models) the conclusion can be made that CRISP-DM does not cover many project management-, organization and quality-related tasks at all or at least not thoroughly enough. In the present day, this has become a must due to how complex projects have become.
Data Mining projects have become more, as they now not only encounter huge streams of data but also require managing and organizing big collaborating teams.
It remains to be seen if a DM engineering process model can be put together that covers the obstacles mentioned above in combination with CRISP-DM in order to adapt it to the most recent DM and KD processes.
Lode Wouters
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Het teamweekend van Abano, Konato en BIQ was weer super! Tijdens de teambuilding maakten we samen een LipDub Music video!
