6月 032014

“Evidence-based policy development” is a term which has been in use for a number of years. However, in most cases it remains more an aspiration than a practical reality. The consciousness of using more data to underpin policy has risen, but the change in practice has been modest. The question is whether agencies are using all available internal and external data at their disposal, exploring that data to gain valuable insights, using predictive modelling to determine how different options play out over the life of the program and balancing budgets and optimal outcomes.

Typically the basis of policy proposals consist of historical data, analytical models from other agencies (such as treasuries), accepted wisdom and professional opinion. While there may be valid reasons for ministers to sometimes take a path different from what the data might suggest, it is even more important in these circumstances to model the likely outcomes in order to successfully protect the government from unintended consequences.

New generations of policy developers are likely to be far more receptive to the “scientific” approaches to policy development. However, the imperative is to provide them with access to all relevant data and tools which enable them to explore it. Another aspect to consider is that the greater quantity of accessible data (often enabled by government ‘open data’ policies) potentially expose governments to challenges by opposition parties, individuals, academics and advocacy groups who, based on their own analysis of the available data, may question the declared expected outcomes of policies and programs. It is therefore important for ministers and their agencies to be able to demonstrate the strong factual foundation of their policies and programs. Importantly, the inflection point is now since all of this is already possible – the question is whether the will to fundamentally change the current approach to policy development exists.

Pro-active Compliance Management alludes to a very significant shift in the approach to fraud, waste, error and debt management in the public sector. The current post-fact management of these issues – where money is allowed to “leak out of the system” through a “pay now – check later” approach and where agencies then spend additional funds and resources to recover some of this money – is shifting to a proactive, preventative approach. Commercial organisations, like banks, cannot afford the high costs of the “double whammy” of the post-fact approach and there is a growing recognition that governments can’t either.

The drive from governments to return budgets to surplus has heightened this consciousness. The move to on-line systems has meant that analytics can be applied to transactions and inputs to verify their validity in real time. This means that fraud and error can be trapped at the point of interaction and be effectively prevented – very much the same as financial institutions already do at the point of transactions.

An important point to be made in this context is that analytical approaches to these areas are vastly superior to business rules-based approaches. The latter creates rules based on the repetition over time of an identified activity, however it is increasingly apparent that perpetrators are just as quick to change their behaviour to circumvent detection – meanwhile considerable financial loss or debt has occurred. By contrast, analytical approaches focus on the detection of anomalies which suggest error or malfeasance. While the error isn’t identified as a particular activity or repetitive, it flags something that is outside of normal or expected behaviour. In the sphere of social services, a proactive approach translates into better social outcomes. For instance, if the vast majority of welfare recipients are entitled because of an economic need, then the recovery of over-payments exacerbates their economic hardship. Better to have prevented an overpayment in the first place.

To recover current debt carried by governments – which in the Federal Government alone is in the tens of billions of dollars – analytical approaches allow for the differentiation of treatment strategies to optimise recovery, allowing agencies to recover the most money in the shortest time from those individuals and entities in the best position to pay off their debts.

Citizen-centric Service Delivery represents a fundamental shift away from payment-centric approaches towards service delivery that is built around a holistic understanding of individual citizens. This differentiated approach looks at all the relevant factors in an individual’s life and the identification of the next best action to improve their personal, social and economic wellbeing. This is a laudable vision towards which a number of agencies are already progressing.

It is reasonably expected that over time this will result in a more engaged and participative relationship between governments and citizens which will in turn produce better outcomes for both. It recognises that the various functions supporting citizens in need exist in silos, both within larger agencies, governments and across layers of government and that this does not serve citizens well. Experience to date demonstrates that with a more holistic and cross-functional approach, citizens feel more cared for and are therefore more inclined to take greater ownership outcomes and begin collaborating with agencies in what becomes a shared endeavour.

A benefit to governments is that they are able to reduce their service delivery costs while ensuring the citizen receives the most beneficial services. From a relevant technology perspective, it is interesting to observe that many of the analytical tools developed for the commercial sector work equally well in government services. For example, a customer intelligence capability designed to use all the known data about an individual consumer to determine the next best product to sell to them is reversed to determine the next best action to assist a citizen. The challenge for major agencies is that their systems are built around eligibility assessment and payments and have very little, if any, customer intelligence, case management or service planning capability. The need for a solid eligibility assessment and payment system remains, but these additional capabilities are required if agencies are to effectively transition to citizen-centric service delivery.

tags: analytics, business analytics, Government
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3月 252009
I had the opportunity to sit in on two presentations yesterday that ran back-to-back and seemed to provide a complementary message to SAS users in government and public service. It gave me the idea to post a few comments on both.

Ben Zenick, Doing More with Less
Ben Zenick, the vice president of consulting services and co-founder of Zencos, talked to SAS users about Doing More with Less. He has a deep background in both public sector and technology, so he had a particular commitment to this topic.

”I wanted to provide SAS users in the public sector with innovative options for utilizing technology to increase the level of customer and constituent satisfaction, create jobs and manage and monitor policies, while having access to fewer resources, less money, and more regulation,” Zenick said. “Of course changes to the economy that have occurred since I was invited to present have put more emphasis on the concept of "Doing More with Less."

According to Zenick, now is a great opportunity to invest in technology. “A lot of the money from the stimulus bill will be appropriated to technology spending projects,” he said. “There are a lot of ways for users of SAS to truly make a difference in what we would all consider trying times. Analytics have opened the door to make very big impacts in the economy and the service you provide. The time to make a difference with technology is now.”

What are public sector pains?
According to Zenick’s research, total budget shortfalls for US states are projected to exceed US$145 billion by 2010. But the states’ remedies – reducing services, increasing taxes, etc. – only reduces demand and worsens the economic picture. Zenick hopes to stem this worsening landscape by offering the idea of using analytics technology to reduce cost and increase revenue opportunities.

Fraud, waste and abuse in healthcare claims: As of 2007, approximately 20 percent of each state’s budget goes to Medicaid program costs. Within that 20 percent is approximately 10 percent that is related to improper payments which could include fraud . Opportunity to use analytics to find potentially suspect claims before you pay.

Increase tax revenue collection through increased efficiencies: Analytics helps identify those who have a propensity to pay after a mistake has been made, identifies more accurate collection methods and forecasts future revenues.

Increase economic development efforts: Analytics reduces time spent collecting, compiling and searching for data. The technology also allows developers to proactively recruit firms by providing workforce demographics and available properties.

Zenick summed it up with a few words: “How do you make sure that you have the resources in the right place at the right time?” he posed. “These are all examples of using analytics for resource allocation – Doing More with Less. Analytics is an extremely important factor in reducing cost and increasing revenue.”

Jonathan Hornby, SAS Response: Doing More with Less.
Jonathan Hornby, Director of Worldwide Marketing at SAS, provided the second presentation in the two-parter - SAS Response: Doing More with Less. He tackled analytics product areas where government and public services could focus their energies: cost, strategy and human capital.

“These are solutions that help an organization understand how value flows and how resources get consumed,” said Hornby.

Strategy: Why is execution so low?
According to Hornby, developing a strategy at the executive level is only a small part of effective execution of a strategy. Today, there is an abundance of data. The problem lies in knowing what to do with it. During his research with some of the world’s sharpest minds, Hornby found that the first step to an effective organizational strategy focusing on Doing More with Less would be a plan for analyzing and using the data.

“It’s all about communication and understanding how metrics, objectives and goals are connected,” Horny said. “Do they correlate? Do they tell the story of how your organization needs to act?”

According to Hornby, too many organizations pick metrics and objectives that don’t move the dials. And often, organizations track far too many metrics, which rob individuals of time as they try to decipher them. All of this comes at great cost, which leads to the next section.

Cost: What is the pain?
The first step is to understand what things cost. SAS® Profitability Management does that, and for commercial organizations, it calculates profit too.

“Less than 50 percent of executives understand what drives cost, profit and value,” said Hornby. “That is the result of a March 2007, Business Week survey. If that’s true, there is much room for improvement, especially now that we are doing more with less.”

Hornby pointed out that there are many ways to cut cost without cutting bone – cuts across the board that have unintended consequences. Analytics can help organizations see waste in productivity and allow companies to get the maximum value moving forward.

Once you can “see” the cost to provide a service – either in aggregate or for a specific transaction – the next step is to understand why. That’s where SAS Activity Based Management comes in. It provides a great environment to model how cost, profit and value flows through an organization. With this knowledge, organizations can identify bottlenecks or areas ripe for improvement, unlocking vast sums of money.

People: Why worry?
According to a 2007 study by Deloitte, 39 percent of those surveyed believe they are hiring the right people for government or public service jobs. That’s even with the rigorous hiring processes in place. Further research shows that 58 percent of the workforce will be eligible for retirement in 2010 and 71 percent of those are senior executives.

According to Hornby, analytics can help organizations anticipate and map the skills gaps they are facing through attrition from retirement and churn. SAS® Human Capital Intelligence can help manage and alighn your workforce strategically.

Wrapping it up
Finally, Hornby shared a strategy/brainstorming tool. “I am currently working with Joel Barker using his ‘strategic implications wheel’ to help President Obama think through the cascade of consequences for all the regulations and stimulus plans,” said Hornby “It’s much like brainstorming. Set up an idea that you think is going to work and then bring in a crowd. Ask everyone to think of one positive and one negative implication. Then, as a group, repeat the process one more time for each of those ideas. You’ll see that there is a range of possibilities.”

For more ideas on how government and public service can do more with less,