The ascent of analytics: A rundown

29.02.2016

How to Extract Meaning for Business - Key takeaways from a panel presented by CIO and Computerworld:

Carmen Casagranda, CIO, Cigna

David Bowie, Managing Director, SAS

Claire Govier, Head of Transformation, Strategy and Architecture, Kiwibank

David Habershon, CIO, Ministry of Social Development

It means decisions are based on evidence, and in the past that has not been entirely possible. Ministers and decision makers across government in New Zealand are looking for evidence that drives better outcomes.

We have plans in place to invest in analytics focused initiatives, which will turn our data into valuable information for frontline staff to use when they are working with clients. These initiatives will also look at how we can better use cross-agency data to form an integrated person or family view and provide wrap-around services.

Cigna sees itself as a technology company selling insurance and recognises the importance of IT to enable this. Cigna chose to take IT out of the operations department and put it on the executive table. IT is not a back-office function anymore, it is an enabler. There isn’t anything an organisation can do without technology or data. That has given analytics the priority it needs from Cigna.

It is through a combination of stakeholder management and constant showing and telling that enables people to move beyond what you’re discussing and tangibly visualise it.

We run a contact centre and a lot of reporting within the contact centre is driven out of the data warehouse, which in many cases provides data that is a day old. Demand for insight is driven by working with the people that are actually making the sales, showing them how important it is to have the information at the right time. This translates into better sales and makes for an easier conversation around analytics at the executive table.

We are constantly talking about what we are doing across all levels of the organisation, right through to board level. Being insight driven means we are aiming to have real time sales management, for example in managing our campaigns. If you have the right information at the right time, you will immediately be able to see how these are performing. Sharing information with other teams can influence the bottom line.

Part of our journey at Kiwibank around becoming an insight driven organisation is examining the data, and asking which data matters, and what the facts are actually telling us.

Organisations are now moving from reporting to real facts and data in a much shorter timeframe. So what it means for us – across different levels – is to really drive the quality of the decision-making but also as a community, keeping up with that demand from the various decision makers.

How do we constantly innovate, and how do we constantly reinvent how we are presenting data and options

Organisations that are insight driven are those that recognise data is an enabler of strategy. Great analytics is not about the answers you get, it’s the questions you ask. Empowering people to own the data and the tools and capabilities to ask the right questions is important to drive the business forward. That stems from creating an insight driven culture and giving people across the organisation the level of insight they need to do make smarter business decisions.

A few years ago analytics was a back office function, it was to give answers to the business. Now it is increasingly coming forward to the business and making it easy to use through approachable analytics. Approachable analytics is the key to getting more people using analytics in the organisation. It is about making it accessible to a broadening base. This requires organisations to have the agility of a start-up but the resilience of a blue chip company.

It is important to keep in mind that an insight driven organisation is not just about the analytics technology but equally about people, talent and leadership. You need a culture of insights that allows people to ask the right questions of the data they have, and then make decisions based on the insights generated. Having insights is the first step. Doing what it takes to turn insights to action is the key.

A couple of years ago, we launched a massive programme called Welfare Reform, which completely changed the welfare system in New Zealand. Alongside that was an investment approach where we pioneered new techniques for looking at which people are in most need and needing more intervention.

It was very interesting to hear about the insight and evidence that will aid in the professional ability and judgement for people on the ground.

At the Ministry we were concerned about long-term welfare dependency. We need to assess in real-time the best chance of success for people and decide everything before the person comes to our door. What the data and insight does allow you to do is understand where your best areas are to put in resources. Moving ahead, the next thing is to concentrate on real-time decision making.

So from a more traditional approach of seeing what happens from large pieces of data, we are moving quite rapidly into real-time analytics, where the machine will help make a decision in real time, or the machine will make a decision by itself.

Providing we have fail-safes in place, you can make far more efficient use of your resources this way.

Data is debunking myths all the time. Governments traditionally work in silos. Child protection area does not know what is happening within the health or education system. But when you bring that data together in a research type context, we make it available and help more agencies make better decisions about where to focus resources.

But there are also complex privacy concerns, and we need to be careful about using evidence.

We are on the threshold of harnessing the power of analytics. But there is an important dimension – the ethical dimension. Just because you can do something doesn’t mean you should.

We should be aware of this as analytical tools become more powerful and insightful.

Like any technology process, we have been going through a maturity model. In that model we are going from hindsight driven reporting to move into insight driven analytics.

We built a business intelligence team to address this. We had reporting decentralised across the organisation so we had lots of great work happening in different departments. This led to an age old argument of which data is the right data, and we had conversations around where the data is coming from and where the insights are being driven.

We centralised that under one team and brought in a professional BI manager to help pull the team together. We have people around the organisations building that team up. We have been pushing ahead with real-time analytics.

We are making sure we are freeing up the data so that people that actually need it make real-time decisions. We are giving that information to the right areas of the organisation so we can turn information into insights to make strategic decisions based on the quality and integrity of our data.

Next: Seeking sponsors and allies: 'Find somebody who gives a damn and work with them.'

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Data analytics can join the dots and bring things together into stories and facts that has not been done before.

Traditionally in banking, the analytical and operational teams were not necessarily hooked up, or were working in different parts of the organisation, creating different data sets for very different purposes.

It comes down to sharing data and information to really improve the story and insight behind the decisions. Analytics is helping break down those internal barriers.

A few years ago, I was working for a large bank overseas and there was a real challenge within the data warehouse team. We needed massive investment to link some analytical databases and operational data tools to try to get a level to fit and match, for marketing and legal purposes.

Traditionally we’d go to the board and write a 30- to 40-page paper and try to explain to somebody what the customer data is and why we needed to spend money on it. We could not tell them what the return of investment would be.

We had a few attempts but we did not even get to the board. We went through filters, review teams and the finance department. We eventually talked to somebody who had great success in taking papers through the board.

Instead of taking a 30-page business case, we took six slides to the board, as we were only allowed to take six slides. We showed what was happening to our credit card customers who were constantly bombarded with mail campaigns and offers from us. We used the data and the facts in a way the board would understand and hit them where it hurts in terms of risk and reputation.

We were able to tell the story from the outside in, from a customer point of view. We wanted money for this enterprise facility and suddenly it made sense. We did get the money for this and a couple of other projects as well.

So find a way to save money or reduce your risk, and find a champion and tell the story in their terms. In this case, it was about revenue.

At a practical level, first of all recognise how important your roles are to your organisations and understand that you may well be ahead of the game in terms of the knowledge and insights, things you can see.

With that, find a voice. And if your area does not have a strong voice or a sponsor, go find one. Find someone who cares.

The key thing for me is the ‘so what’ aspect of it. We know this, we found this out, but ‘so what’ Find somebody who gives a damn and work with them.

Business intelligence is one of the fastest growing industries globally right now. It is using the brilliant minds of the people in this room to actually help decipher what is valuable and pass it on to the people who need it in the organisation – whether frontline, backroom or executive level.

All of us here understand analytics and the importance of data. The world has changed and 30-page business case requirements are hard to sell. If you want to sell your vision, less is more. Turn data into a story and make it real.

Sell the story. By saying we are doing this analysis to generate insight and business value,you sell the story of why the organisation needs to invest in these tools. That will enable you to find the driving sponsor. By doing that, you can sell the vision of what everybody else is doing – getting great insights from analytics.

Analytics is having a significant impact on the investor and business landscape. There is a growing recognition that analytics can influence business strategy and have an impact on the share price of listed companies.

In the next few years, I anticipate data analytics will become a ubiquitous boardroom topic in every major organisation and the leaders of these corporations will be asked about the company’s plans for using analytics to drive revenue, improve performance and better serve their customers. Leading organisations must embed the analytics process in the way they do business and apply the insights generated to all critical decisions.

At an investor roundtable held recently, our chief analytics officer was asked by investment bankers how to recognise from the outside that an organisation “gets” analytics and is using their data strategically. The reason is that is where they want to invest their money.

The challenge the industry faces at large is finding the talent and analytical skills needed for data advantage. There is a shortage of data scientists globally and as we know data scientists are the bridge between data analytics and business decision making.

Business, government and academia need to work together to address this problem. Closing the gap won’t be easy but here in New Zealand we are partnering with the likes of Massey University to address the skills gap with our Master of Analytics program. This is critical to ensure organisations have the talent to make data-driven strategic decisions and nurture an insight driven culture.

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By Divina Paredes

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