Yes it can, and ideally should be. We would suggest looking at transitions in two ways:
- Type A – Where there is an ability to influence ‘what’ is being transitioned and ‘how’… i.e. what is the ‘to-be’ operating model as a result of the transition. In this case, there would be sufficient time and data to use Maven™ to arrive at the ‘to-be’ model.
- Type B – Where the client has taken the basic decisions, and there is limited time for due-diligence. In case a strong process understanding exists PRIOR to starting the due-diligence, this would take approximately 2-3 weeks to build the model in Maven™. If not, it may be possible to complete all modules of Maven™ within time constraints – but you might want to use whatever possible AND keep enhancing the model as the other stages of the transitions progress (e.g. training)…. before go-live.
Key point – once you build the model, operations / change can then take over from there to optimize the process further.
Users may be of two types - Basic user (inputting the base models into Maven™) and Advanced user (analytics to arrive at ‘to-be’ models). Both these users should have a process excellence/ business analysis skill/ mentality.
Base user characteristics – Some experience with the business domain, has done some process modeling. Training time ~ 2 weeks.
Advanced user – Black belt type person with experience in implementing change initiatives. Training time (post basic training) ~ 2-4 weeks.
Maven™ specialists are typically available to help mentor/ coach/ review with respect to the first few engagements.
- Digital definition of existing operating model (visual tool)
- Operating model optimization (“to-be” state)
- Cost reduction
- Cycle time reduction
- Controls configuration and effectiveness
- Ideal use for processes that have multiple activities across multiple teams (across locations)
- Can be used even where multiple processes are run but across different business areas (not inter-related). While this is an not ideal use (as compared to related processes), the following can be achieved in such cases:
- Shared services across these business areas (common functions)
- Cross-skilling – e.g. in an assignment, there were 8 different queues… each of which did not have scale – hence leading to large buffers by queue to address time and control coverage requirements. In this case Maven™ recommended cross skilling and creating 3 teams; hence reducing FTEs by 20% with better controls! This was done keeping in mind – volume patterns, turn-around time requirements by team, skills, controls (e.g. need to keep activities separated)
- Point optimization within these processes by business area
- Business problems – below is a typical set of business problems that Maven™ helps to address
Maven™ does not speak to industry benchmarks by process. But it enables the user with analytics that can help with benchmarking initiatives within the process model:
- Differences by geography (e.g. by activities, by completion time, by controls)
- Differences by product/ asset class (e.g. why does card type ‘a’ take more time to acquire than card type ‘b’)
An advanced user can look at the following analytics to make initial hypothesis:
- Cycle time issues (where are the delays/ bottlenecks)
- Utilization by team by hour
- Team skill clusters (simple / medium/ high complexity)
- High effort activities by team
- Controls – over-controlled OR under-controlled, cost of control
- Other types of analytics available:
- Automation index (opportunities to automate further)
- Volumes/ mode of communication – e.g. ‘x’ emails by team by day
- Time constraints – where are the EOD, BOD, wait times (e.g. reverse SLAs) and deadlines (should some of these be challenged?)
- Cluster analysis – which clusters create bottlenecks, maximum effort. Clusters are a logical grouping of activities by lifecycle (e.g. application processing, KYC, underwriting, closing, booking)
- Shift planning
- Delays by hour with reasons – activities causing, reason (capacity OR office time)
- Infrastructure (seat) utilization
- Controls – compensating controls (too much could mean over control!), how much time risks are open for
To our knowledge, there are no comparable tools that cover the breadth and depth of functionality with respect to operating model design and change as Maven™ does.
There are certainly great tools in the market that address specific aspects of an operating model…. process repository/models, simulation engines, risk & controls, HR complexity/ skills etc.
Maven™ differentiators are:
- Ability to look at an operating model in totality – due to this the speed to arrive at ‘to-be’ optimized models is a few weeks. Existing mechanisms and tools take 3-6 months (OR more) to arrive at ‘to-be’ state
- Better results – Maven™ algorithms help with ‘multi-variate’ optimization to help identify ‘a’ point on the efficient frontier (refer diagram below). The efficient frontier is a curve based on ‘current constraints’ ….. cost v/s time v/s controls.
The key difference as compared to existing tools is that Maven™ provides ‘an’ answer on this curve as compared to simulation points (e.g. Monte Carlo). The issue with simulation is that it is just that…and it is time consuming, is probabilistic, needs advanced statistics, there are far too many different points without pointing to any in specific… how do you choose where you want to be with any degree of assurance?
While it is important to provide Maven™ the right data (accurate, complete), it is noted that
- One can start a project with data that is “reasonably” complete and accurate (e.g. for Average Handle Times (AHT)). Maven™ has certain built-in checkpoints that one can use for validations (e.g. % of rework, high effort activities graphs that a business/ operations user can challenge or agree with). Further, even with somewhat incomplete or imperfect data, Maven™ will provide sufficient analytics to help identify optimization/ improvement opportunities. As the questions become more searching and detailed/specific, and the power of Maven™ becomes apparent, the user will be able to determine the advantage of providing more and better data.
- The model is available with the user in digital format… hence, as data points become more accurate (or change), one can come back to Maven™ and easily change the specific data.
AHT variance: This can be captured using ‘decision’ boxes in the process map. So, if there is an activity that takes 3 minutes or 15 minutes depending on the complexity, break this into 2 activities using a decision box.
- Volume arrivals through the day can modeled as input
- In case there are different volumes for most days with spikes on a particular day of the week (or month/ quarter), we recommend building 2 models – one for the normal and one for the spikes. Analyze the different outputs to arrive at ‘the’ optimal model (capacity, temps, work timings, skills etc).