New banking… new thinking

They say money talks.  Well in the world of banking, that is often true.  But now, new entrant and challenger banks can breathe a sigh of relief.

Know your customer. It’s the oldest adage in the world but still the most valuable. But understanding the needs, wants, expectations and behaviours of today’s highly demanding and digital customers is tricky for all organisations – and most especially banks.

Banking has transformed (and then some!) in the last 10 years. In the past, banks designed services and customers took what was available. Inertia ruled – and customers largely stayed loyal. Now all that’s changed. New, exciting, personalised banking services are constantly emerging – and the bank that truly understands what different types of customers want and need now and in the future gets ahead and stays ahead. Standing still is not an option! The message is clear; if banks don’t provide the services, security, flexibility and innovation that its customers want and need – they will vote ‘with their feet’ and move to another bank that does. Simples!

But understanding complex customer behaviours, financial requirements and market developments requires highly sophisticated and often complex analysis. It’s a fact that there are some great analytics solutions on the market but until recently, these were incredibly expensive and beyond the reach of all but established banks or ‘well heeled’ new entrants. This put new banks at a disadvantage and hampered them from designing new, responsive, highly personalised solutions. But now that’s changed.

From today, advanced highly sophisticated analytic capabilities will be within the reach of ALL banks.

How? Sopra Steria, a European pioneer in digital transformation, has just announced that it has become a SAS Managed Analytics Services Provider (MASP). This will enable us to offer cutting edge, high-end analytic solutions at a cost effective price point for new entrant banks.

We will include ‘Gold level’ SAS cloud-based analytics solutions as part of our Modular Digital Banking (MDB) solution. This innovative end-to-end, fully functional digital banking solution delivers a ‘step change’ in banking service analytics capability, enabling new entrants to increase their agility and responsiveness.  Key features include:

  • A real time decision engine with integrated marketing automation and advanced analytics
  • Advanced visual analytics capability to create descriptive and predictive models
  • Enterprise grade development environment to ensure organisations can meet regulatory compliance requirements both now and in the future
  • Data modelling as well as data integration, quality and management capabilities

Interested?  Take a look at the Sopra Steria and SAS strategic partnership and find out more about affordable, advanced and innovative analytics that can help you make better decisions faster.

What are your thoughts? Leave a reply below, or contact me by email.

Products with personality – the Liquid Big Data customer experience

Digital technology is driving new forms of customer engagement that are rapidly eliminating the functional silos between online and offline retail channels. As a result many high street retailers are already experiencing falling footfall in their physical stores as customers increasingly switch to online competitors for better convenience, choice and prices.

However, these bricks and mortar (B&M) businesses could use Liquid Big Data (cloud-based analytics shared between partners, suppliers and, potentially, competitors for their mutual benefit) to integrate the physical and digital customer experience into a unique, responsive personal customer journey online competitors can’t imitate.

So what might the Liquid Big Data customer experience be like for a global retailer selling ready-to-assemble home furniture, appliances and accessories for example?  Here are some ideas…

An eidetic world

Traditionally high street retailers focus on their brand as a source of differentiation to attract customers to their physical stores. Yet conversely, digital empowers customers to focus on their specific wants or needs regardless of provide. That’s why their online competitors invest so heavily in user experience design to continually optimise how customers use their channels to browse and buy the products they sell – choice and accessibility as a form of differentiation. To combat this challenge, B&M businesses are increasingly using digital technology (such as touch screens, beacons and virtual reality) to differentiate the in-store experience as something equally empowering or seamless as being online.

However, by choosing to replicate the online experience, in-store risks ignoring a source of competitive advantage unique to B&M: a customer’s physical experience with a product and the wider environment.

Using Liquid Big Data, the retail customer experience does not have a beginning or end nor is it location specific – it’s contextual.  Powered by a smartphone app provided by collaborating retailers and suppliers, wearable technology (such as a watch or glasses) could capture the people, places and objects an individual customer likes, loathes or loves throughout their entire lives. Even if such encounters are fleeting, these moments are captured with photographic, eidetic clarity in the individual’s private cloud. The customer can then choose which of these experiences to share with the retailer via the app to create a unique, personalised shopping experience in-store every time they visit.

This could be the raised heartbeat of seeing Rome architecture for the first time – could our example global retailer offer this customer discounts on its in-store Baroque furniture offerings? Another customer loves the feel of velvet – could an in-store sales team member suggest some appropriate soft furnishings? One customer really liked his girlfriend’s coffee table she had at university three years ago – could today’s store visit be an opportunity to find something similar for their new home?

Liquid Big Data enables a high street retailer to use the eidetic physical world as a way to effectively personalise its in-store customer experience using digital technology – enhancing its existing brand as a form of differentiation that can’t be imitated by its online competitors.

Products with personality

Harnessing the power of the eidetic world may not be sufficient long term to differentiate the in-store customer experience versus online. Although it offers a targeted customer experience it doesn’t necessarily make a customer’s relationship any closer or more intimate with the specific products a B&M business sells – a key driver at the heart of the competing online experience.

Yet the customer experience of an online retailer is ultimately a passive, limited engagement typically contingent upon the specific browsing or buying history the customer has with their channel or brand or other self-selecting activity such as social media engagement.

In response, a high street retailer with its partners, suppliers or competitors could use Liquid Big Data to take personalisation to a deeper level – use cloud based artificial intelligence (AI) to create direct relationships between individual customers and the products they sell.

The idea is to personify a product using AI with a user experience similar to smartphone personal assistants or virtual customer service agents. A customer can have a text or voice conversation with the product to explore its suitability for purchase (including reviews or endorsements) and select any desired tailoring or customisation. A customer may also enable the product AI to access his or her eidetic memories or social media profile to help shape and personalise their relationship. The AI can either be used on request or continually available to provide product updates or after sales support. In addition, products may also talk to each other in the cloud as a form of machine learning to identify potential new product designs or opportunities for complements that better meet their individual customers’ needs.

Such insights are then gathered by the retailer and participating stakeholders to inform the customer experience in-store (and beyond), support product development and address any supply chain issues.

For example, our global retailer has found that people across the world keep asking the same question about the performance of a specific brand fridge freezer it sells. Could there be a quality issue with this particular product that needs investigating? Customers in a specific region like the way the product is sold in-store by staff based on their after sales conversation with the AI – how can this be replicated in other regions where demand is falling? The collective cloud AI has also designed a new cooling, energy-efficient feature for the next model – a potential hot seller that could be delivered in collaboration with the supplier?

The potential headline benefits of a high street retailer using the Liquid Big Data customer experience include:

  • Enables new forms of personalisation and innovation deeper than anything previously available in the market by integrating real life and digital customer experience
  • Challenges the seemingly unbreakable competitive advantage of  online retailer competitors and other digital disruptors (such as platforms and social media channels)
  • Links in-store digital technology directly, explicitly with specific customer needs daily – materially lowers the risk of this investment and increase its ROI

If you would like more information about how cloud-enabled big data and analytics can benefit your organisation please contact the Sopra Steria Digital Practice.

Mind the GaaP – shared technology platforms and data analytics

The outcome of the government’s digital strategy has been higher adoption of on-line services and the introduction of new technologies – including social media, mobility, analytics and cloud computing. But as government delivers services that are simpler, clearer and faster to use it also creates increased expectations.

First, citizens demand services that are often universal but also reflect the levels of personalisation they get as private consumers. But government operates as a series of silos. Services, processes and technology reflect inward-looking departmental needs.

Second, the public finances demand that government boost productivity using innovative digital technologies. The government saved £18.6 billion in 2014-15 through various reform projects. But the savings attributable to digital transformation are significant but relatively small (£391m).

In an environment of increasing citizen demands and top-down cost reductions, how can technology help government be more responsive but at least cost?

Government as a Platform might reduce unnecessary bureaucracy and costs

Two years ago the Government Digital Service (GDS) set out to transform twenty-five major public services. Twenty digital ‘exemplars’ are now publicly accessible. GDS continues to work with departments to build these and other services in agile and iterative ways.

The next phase of the government’s strategy is ‘Government as a Platform’ (GaaP). This is the sharing of the core infrastructure of systems, technology and processes across departments. GOV.UK Verify is a good example. Rather than having to prove who you are to every government department, Verify uses certified companies (and public and private sector data) to confirm a person’s identify once and for all. Other potential platforms are payment processing, case management and appointment bookings – common services used all around government.

GaaP offers a number of potential benefits. First, enhanced user satisfaction by eliminating the need for a citizen to input unnecessary data and information. Second, cost savings by eliminating administrative procedures and processes (and associated transactions) that are not needed. Third, wider economic benefits by making the data open, as others who are unrelated to government can create new businesses that complement public services. Forth, citizens or community groups might also use this data to hold government to account.

Tailored and automated services offer even greatest benefits

In the private sector an ability to share systems and data through technology is leading to a more personalised service. A user is in full control of navigating, choosing and terminating a set of offers. Back-office integration enables the private sector to offer proactive, enhanced and efficient services.

How might this approach be applied in the public sector? At its most simple, the government might pre-fill data in an application form that it already possesses, based on taxation or benefit entitlements, and notify the citizen via email or text of any changes. But more significant improvements to the quality and cost of public services are available through the analysis of this data (a data platform), leading to earlier and more focused interventions.

For example, approximately 40% of hospital admissions in England are unplanned admissions. They are a problem for hospitals because they are costly and disruptive and increase waiting times. Vulnerable patients with complex physical or mental health needs tend to be the biggest problem.

The detailed analysis of historic patient level data, identification of patterns and predictive risk modelling can predict and identify ‘at risk’ individuals. Unplanned admissions can then be avoided through changes to the hospital discharge process and better co-ordination of care.

Taking it to the next level, ICT-enabled simulation and decision-support tools are also able to analyse large and complex socio-economic data sets on deprivation, crime, health, education, etc. This deeper analysis can inform early intervention and screening programmes, with resources focused on communities and individuals who most need them.

Costs can be avoided by highlighting incidences of unnecessary care or delays in treatment. And by making evidence-based information about options, outcomes and uncertainties available, patients are also in a better position to make informed choices about the treatments available to them.

This proactive approach may not be appropriate for all types of service. It will, for example, depend on access to necessary data and protection and legal access. But, when applied to high-risk and often disproportionately high cost individuals, the savings potentially far outweigh the up-front costs of investment.

What do you think? Leave a reply below or contact me by email.

The “observer effect” applied to digital transformation

A different take on GDS’s Performance Platform

The “observer effect” states that whatever you observe, by the very act of observation, it changes. Developing tools to measure the performance of a digital transformation – such as the GDS Performance Platform – is a key step of any transformation journey itself, as it can accelerate the process and guide it to bear positive outcomes.

The act of measuring is change itself

In science, the term “observer effect” refers to changes that the act of observation will make on a phenomenon being observed. This is often the result of instruments that, by necessity, alter the state of what they measure in some manner. A commonplace example is checking the pressure in a car’s tyre: this is difficult to do without letting out some of the air, thus changing the pressure.

The GDS’s Performance Platform

Started as a simple dashboard to display web traffic data on gov.uk, the Government Digital Service (GDS) Performance Platform has now become a key tool that gives departments the ability to monitor the performance of their digital services in real time, aggregating data from a range of sources including web analytics, survey and finance data.

The digital by default service standard – a set of criteria for all government services to meet – now mandates the following four key performance indicators (KPIs): cost per transaction, user satisfaction, completion rate, digital take-up. These KPIs can be used to measure the success of a service and to support decisions and planning of improvements.

Similar to the tyre pressure, the very act of measuring those indicators is influencing and accelerating the transformation process, focusing the departments’ attention to delivering efficiency and quality of service to citizens. This is a key enabler of any transformation journey and it will be interesting to see how far the Performance Platform will go in the coming years.

(Note: although this example is specific to the public sector, the above is easily applicable to private organisations too – this will the subject of another blog post).

Where next? The difference between performance and evaluation

Performance measurement and evaluation are complementary activities. Evaluation gives meaning to performance measurement and performance measurement gives empirical rigour (evidence) to evaluation.

Performance measurements do not question the objectives themselves and, therefore, stop short of any final judgement as to whether the programme or activity was good or bad – only if it was successful (or not) within the narrow confines of its mandate.

The current debate on Gov2.0/Government as a Platform is precisely around the purpose of governments in the 21st century, with two schools of thoughts arguing that it’s the profitable thing to do or, well, it’s the right thing to do.

Although a clear approach on how to evaluate the impacts this approach will have on the wider society is not yet agreed, tools such as the Performance Platform can and will inform and support this discussion.

What do you think? Does this capture the distinction between programme evaluation and performance measurement – or is there a lot more to it? Is your organisation measuring the performance of its transformation? Leave a reply below, or contact me by email.

Changing the conversation from Big Data to insight advantage

With Big Data once again we in the IT industry are falling into the same old trap of talking about inputs (volume, velocity, variety and veracity) and technology (Hadoop, Spark) rather than the desired outcomes. No wonder then that analyst groups are reporting that only a tiny fraction of Big Data proofs of concept are being industrialised and put into production.

On one level this is understandable – talking about outcomes can seem a little dry.  Highlighting the potential for revenue gains or cost savings or reducing risk (of future costs or revenue losses); or indeed the underlying elements – such as operational excellence or an enhanced customer experience – that will deliver those financial gains can seem as if the same old story is being recycled. Consequently it is much more exciting to talk about what is new, which is why the technology always seems so exciting.

But this time there is a difference. We live in the information age and work in the knowledge economy. Insight is the lubricant of both and the most sustainable advantage any business can have is better insight than its competitors. And by better I mean in breadth, depth, accuracy and timeliness.

The good thing about Big Data is that data – the raw material for insight – is in vogue when for ages it has just been seen as digital exhaust. But to make the most of the transformational opportunity that is available, we need to steer the conversation away from Big Data to what it enables, strategically. We need to use the excitement about unstructured data and the internet of things to seed the concept of insight advantage in commercial consciousness.

I believe there are six steps to achieving insight advantage. Read my article outlining those steps – the first in a series of pieces that will be published over the next couple of months.

#InsightAdvantage