Transforming Performance using Decision Science and AI
Media & Telecoms | Financial Services | B2B
Consulting Services
Creating the Intelligent Enterprise
Advisory Services
Our approach to data and analytics transformation is based on decades of hard-won experience
Organisations will increasingly succeed based on the capability to realise and effectively deploy a superior understanding of their customers and future customers. However, understanding and connecting to customers in the digital environment has never been more daunting. Whilst there is an unparalleled ability to collect, examine and exploit data to drive an agile, responsive and a superior customer experience, our research suggests that most organisations fail to optimise investments in data and insight. The common reason for this is an over-reliance on technology solutions coupled with a failure to tackle the cultural and operating model changes required.
Our approach to data and analytics transformation is the result of many years of experience of designing and delivering capabilities and being accountable for the improvement in business results from data and analytics. We believe there are five critical areas to consider:
Define key capability requirements by desired business strategy and objectives
Requirements must be thoroughly examined for their ability to deliver the desired financial outcomes and suitably triaged between ‘must-have’ and ‘nice to have’. The most important factor in the approach to implementation is velocity; it is crucial to configure the change programme to deliver in short, time-boxed bursts, aligned to material business benefits.
The operating model for Decision Management
Probably the most difficult component to get right, as addressing the cultural, organisation and process changes required to transform to customer-centricity is very hard work. Many organisations pay scant attention to this factor and subsequently pay the price, with returns on investment in technology under-performing expectations. It becomes particularly challenging the larger the enterprise is and the`more it is entrenched in a product/function organisation model. The operating model has two, inter-related parts: Decisions for Business and Decisions for Customers.
Integrating insight and decision science
The nirvana for most organisations and perfectly possible to create. There are four capabilities to integrate: BI (or reporting), Diagnostics, Prediction and Optimisation, Decision Management & Personalisation. Without suitable integration, an organisation will fall prey to data and insight silos and cottage industries that prevent the establishment of ‘one source of truth’. In the rush to digital transformation, the creation of Digital silos is a particular mistake to avoid.
Establishing a suitable technological ecosystem
The transformation to customer-centricity in a digital world is highly dependent on technology, an aspect that usually absorbs the greatest internal focus, largest expenditure and the attraction of the consultancy and vendor communities. Although aspects will differ, dependent on business model, the ecosystem has some core common features. One of these is the creation of both analytical and operational domains, giving the ability to report, diagnose and model ‘offline’ before committing decisions into the ‘online’ operational channels, be that push channels or interactive.
A focus on business enablement
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Business kpi holders need common goals and metrics, must be suitably trained to understand new capability. Consideration should be given to decision arbitration processes and managing the inevitable internal political conflicts.
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Product/Offer Development and management must be in tune with the agile, flexible and adaptive decisional operating model. There's no point in having the ability to optimize billions of decisions with customers if product or offer sets are under-differentiated.
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Channel owners have to be engaged in the decision process in order to suitably arbitrate targets and constraints and ensure enablement for decision outputs.
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The democratisation of data and insight with the creation of an on-demand insight ecosystem, self-service access and insight distribution can significantly speed adoption, effective exploitation and increase the efficiency of insight and analytical production.
Management & Development
We help develop the best management, data and analytical skills for your business
Personal Development and Succession Planning
Leading an analytical or decision science function or proposition team is a lonely job. No ordinary management development organisations or coaches understand the particular demands of these difficult roles. Managing upwards and with peer groups is a vital skill. So too, is the establishment, development and nurturing of effective data and analytics teams. Our long experience in leading and developing high performance decision science teams and dealing with the day-to-day demands of C-level executives means that we can offer practical advice and expertise to help you with your leadership development and succession planning.
Support for Recruitment & Selection
With such a specialist subject as data and analytics, finding and selecting the right talent to deliver what is needed and fit the culture of the organisation can be very challenging. We are not recruitment consultants but offer our assistance in the process of acquiring the right leadership skills in data and analytics. We have recruited more than a thousand data and analytics staff over many years and we have the expert knowledge that helps sort the wheat from the chaff to ensure you are investing in the right talent.