Why is SELLEA unique?
Thus far, banks wishing to improve targeting capabilities were presented with two alternatives:
- The implementation of industry solutions or building of own analytical platforms
- Both approaches require large up-front investments and demand long implementation cycles
- These implementations also have an uncertain ending due to project complexities, levels of bank’s IT and infrastructure readiness and internal capabilities to breed analytical resources
Until SELLEA, CEE banks wishing to boost their sales results through direct-selling and campaigning activities have been presented with a choice between the two distinct alternatives for improving their target selection capabilities:
1) Industry Solutions
The standard vendor approach to development of Industry Solutions commonly presumes ‘laboratory conditions’ with regards to product definitions related to a specific market, IT infrastructure and data requirements, and as a result creates systems that demand similar conditions just to be implemented.
In addition, the competition between vendors of such products breeds complexity in an attempt to create as comprehensive a product as possible and gain the ‘competitive advantage’ when comparing one’s offering against another’s. The consequence usually being a combination of overly-ambitious data-models and subsequent data-transformations that require input data definitions and data completeness to strictly follow the presumptions made during product development. Implementation of Industry Solutions in CEE frequently produces following shortcomings:
- Long projects with many postponements due to less-than-perfect data and IT infrastructure found at banks during the actual implementation, with few missing data items commonly preventing the project from continuing,
- Unreliable output, as data is taken at a very granular level and transformed based on its expected (not actual) meaning, and where one mistake in mapping affects a chain of consequent transformations,
- Demanding system maintenance, as all changes to other systems have to be cascaded to many granular forms of data and subsequent transformations within the system,
- Loose definition of system ownership, as data transformations are often too complex for business users and too business-specific for IT departments to take over.
Building an own analytical platform is the better of the two approaches
and is the ultimate goal for banks that are determined to embed data
analysis into their selling processes
Provided that the bank has experienced resources or is well coached during the development process the project is more likely to succeed and truly meet business requirements
However, a decision to build an analytical platform also raises several business considerations such as the feasibility of business case when looking at the size of investment, expected return and time in which this return will be achieved
2) Own Analytical Platform
The more sensible alternative for CEE banks is to build own analytical platforms as they are the ones who best understand own data and recognise the business purpose for its utilisation. This approach also allows phased development and building of internal capabilities.
Provided that internal resources are experienced or well coached during the development, such approach is probably the best for most CEE banks to select.
However, during the development of such a platform there will always be at least a few business considerations to address:
- What is the expected return based on the size and potential of client-base? These projects are long, resource-intensive and often as costly as Industry Solution implementations.
- What is the real time-to-market? The project’s end-result is not a selection of target group – but the ability to analyse client-base and select target groups based on the findings, the end of this project only becomes the beginning of another: the project of utilising the analytical platform.
- Are internal resources capable of providing good selections and in which time-frame? Associated with this there are also considerations on sustainability when relying on external help during the initial model developments.
- Demanding system maintenance - similarly to Industry Solution approach - analytical platforms tend to collect the data at the near-lowest level of granularity.
SELLEA is designed to provide immediate results It addresses key pain-points in above approaches through a combination of quick deployment, immediate and easy usage, and near-effortless maintenance SELLEA provides target lists based on data which is available and without requiring analytical capabilities from the bank
3) SELLEA, the third Alternative
SELLEA is created by consultants who have experienced both above alternatives through many implementations, who appreciate the benefits of each approach and are also aware of their shortcomings. Through these projects consultants have learned the dynamics which are commonly found in CEE banks and recognise that there are often more infrastructural requirements and demands on human resources than there is time to meet sales targets.
The respect for these dynamics is embedded into SELLEA, the system which is designed to provide immediate results. This unique design consists of three main elements:
- Quick Deployment
- Immediate and Easy Usage
- Near-Effortless Maintenance
Fast time-to-market is achieved through minimal and purposeful selection of required input data and defined set-up procedure. Ideally, the complete system utilises fifty (50) data-fields, but it is configurable and functional in accordance to data which is available: both in terms of which fields are delivered (missing fields will not be used - weights of models that require the field will be lowered) and in terms of actual content of delivered fields (if we don’t have an average balance, we will use an end-of-month balance, but its effect on the final score will be lowered). Thus, by its definition: the implementation of SELLEA will always be quick and have a predictable end-date.
The system is made to provide immediate target group selections, it is not there to provide ability to analyse potential candidates and decide how to make target groups. SELLEA is used though two simple selections: the Sales Objective (e.g. Credit Cards) and the Quantity of Leads (e.g. 2,500) - thereby assuring that no business training and zero IT involvement is required to use the system.
SELLEA requires the same data inputs (one loading procedure which runs every month) and periodical updates only in case that new Sales Objectives are added to the system and bank desires to utilise them (new data fields may be required if Investment Funds is added to available Sales Objectives).