There is great excitement everywhere about big data and analytics these days. Everyday new tools and applications are introduced to help make sense of public sector data and examine ways in which this data can improve public sector effectiveness. Government agencies and departments are beginning to get anxious about capitalizing on the opportunity. Some are really joining the bandwagon, but others are quite hesitant.
For some government agencies, especially where the top management is not quite tech savvy, inferences are often made to failed projects, and systems that rack up costs and deliver little value. Many underestimate the effects of their employee and management resistance on the success or failure of information systems. Many complain about the newness of the technology or the speed with which systems become outdated.
The bottom line is – the data and technology are not the biggest issues – it’s how these tools can help management improve governance decisions, processes and service delivery.
Helping civil servants. Target the voting public. Civil servants have to decide which stakeholders to spend time with by examining their activities. Very often, they end up spending too much time with easy and familiar assignments or with people with urgent needs or with friendly persons or with people who will offer some financial gratification. Ease, urgency and cash trump importance.
Approaches that use data and analytics, structured around frameworks that capture the dynamics of the public customer, his/her needs and potential, help civil servants target clients properly and spend time more effectively. Such an approach involves:
Identifying profile characteristics (e.g. type of public service client, organisation, number of employees) that predict client potential and developing an estimate of potential for each client.
Using techniques such as collaborative filtering to identify public sector clients/prospects with similar needs and potential and suggest the best value proposition and public service approach for each stakeholder.
Closing the loop by providing an assessment of how effective client targeting was so as to inform better future decisions.
Helping public sector managers. Analytics can help public sector managers have higher impact as coaches and make more-informed decisions about issues such as territory design, goal setting, and performance management. Traditionally, managers were not ranking people on any criteria or tying rewards or corrective consequences to rankings. But if territories don’t have equal potential, the rankings don’t reflect true performance. Public servants in rich territories have an unfair advantage while those with poor territories are demotivated.
Data and analytics enable performance metrics that account for territory potential, so that public sector managers can reward the best civil servants. Such an approach involves:
Developing measures of stakeholder potential, using government and third-party data sources (e.g. demographics) and civil servant input.
Identifying the true best performers using techniques that separate the impact of territory potential from the impact of a civil servant’s ability/effort on performance.
Rewarding the true best performers, learning what they do that’s different from average performers, and sharing the learning across the public sector team.
Helping public sector leaders including politicians. Analytics can help public sector leaders improve decisions about issues such as public sector strategy, employee size and structure, and the recruiting of public sector talent. Consider how analytics can help public sector leaders design incentive and compensation plans. Traditionally, public sector workers have enjoyed flat increases across the board, regardless of performance or impact, benchmarked on history and checked against past costs versus budget. This retrospective approach can blindside public sector workers with undesired consequences in terms of effort allocation and financial risk.
A better plan results when the public sector uses data and analytics, structured around frameworks that link plan design to projected costs, public sector worker activity levels, and fairness under varied market conditions.
Such an approach would be forward-looking and improve the odds that workers will be better motivated and in a better position to switch to private sector jobs without great emptional and physical upheal often connected with being suddenly expected to be accountable to a plan and a result. Such an approach involves:
Using analytics to test the consequences of proposed plan designs, compare alternatives, and reveal unwanted side effects and financial risks.
Monitoring metrics and indicators showing a plan’s strategic alignment, motivational power, and costs.
Proactively making adjustments to keep the plan on track.
It’s not about the technology or the data. Investments in public sector data, technology, and analytics can only live up to their promise when civil servants focus first on understanding the dynamics of the fundamental decisions and processes that they are responsible for.
ANDRIS A. ZOLTNERS, PK SINHA, AND SALLY E. LORIMER