If an organisation wants to gain the full benefits of Workforce Management (WFM), then the criticality of data and information needs to be recognised.
As organisations move toward more customer-centric strategies and distributed or remote teams, optimising the workforce is becoming critical to ensuring the right people are assigned to the right jobs at the right time.
More than ever before, workforce management has evolved into a more integrated, demand-oriented process that includes changes in personnel requirements and objectives when scheduling staff. Optimising the workforce relies on having relevant data and information available, yet surprisingly, many organisations focus on business processes and pay lip service to the underlying data.
If data and information are critical success factors for successful WFM, why are they so undervalued?
Customer Centricity, Mobility and Optimisation: Key Drivers in Successful WFM
If we look at the key drivers within WFM, there are three powerful forces driving the demand to enhance Workforce Management capability, which we explore here.
Customer Centricity
“Customer is King” was a catchcry that many of us would remember from when we were kids. The reborn obsession of putting the customer first is again driving product and service personalisation.
Organisations need to be re-organised to provide and support this level of differentiation and therefore need to tackle complex workforce management challengers such as rostering.
By way of example, in the health care industry, recent government legislation has empowered the ‘customer’ to be more active in choosing who and what support they need to receive. An elderly person who requires help with everyday tasks such as shopping, showering, home care and so on can now choose who they engage, rather than just engaging an organisation to provide the service.
Distributed and remote workforces
The arrival of coronavirus has accelerated the need for distributed teams and remote workforces. In essence, organisations will increasingly require both their staff and contractors to deliver as a service on a demand-driven basis.
This has enormous implications for how organisations manage their workforce.
Playing this forward, the distributed staff and contractors may provide the same service which, prima facie, does not seem problematic. However, how can the organisation ensure availability and compliance is met, for example, fatigue policies where there is no visibility of the services performed outside of the organisation?
Optimisation
As ‘big data’ and ‘small data’ take their well-deserved place at the table, organisations are demanding predictive analytics with which to make informed decisions.
Historical reporting has lost a lot of its value as the world is rapidly changing and customer-centricity drives demand. Planning is now based more around predictive analytics than historical reports. The ability to reliably predict customer demand and produce an optimised workforce to support it has never been more complex or challenging.
Quality, Timely, Accurate and Reliable Data – Thank God you’re here!
It may be blindingly obvious that data and information are critical success factors in providing the benefits that can be realised through WFM optimisation, yet so many projects do not weight their importance accordingly.
The first step for many organisations moving to WFM is to standardise business processes. Historical processes will almost always deviate across an organisation as Roster Managers adapt their processes to meet the specific demands of the businesses (and almost always will do so with historical data).
As negotiations and process changes are worked through, a solution is built and configured and then three, two, one … Go….
Um, well, maybe not.
Operational Data Challenges
Let’s provide some context with a common example of an end-to-end process, “People to Pay” is automated. The HR System talks to the Rostering System, which in turn talks to the Time and Attendance System, which talks to the Award Interpretation System, which talks to the Pay System. On the surface of it, it appears a sequential process and data is easily managed, right?
A simple example of a problematic relationship could be the Operational Hierarchy contained in the HR system, which may (for very good reasons) not reflect the Operational Hierarchy in the operations. Off the bat, there is a problematic data and information relationship that need to be managed and could manifest itself in:
- Challenges to interpret and pay a higher duty for someone acting up a grade;
- Exception management issues where approvals are not supported by role changes on the day of operations; or
- A plethora of business process issues.
Automation Challenges
One of the core benefits of WFM automation is using fit-for-purpose roster patterns that a Rosterer can use to generate automated rosters. This functionality is fairly mainstream but, in our experience, rarely fully implemented. The thing that stops automation is quite simply put: data.
Without understanding the critical data elements required to enable automation, the ability generate an automated roster is limited. This is not just availability but in many instances, additional data and information such as skills, hours worked and event client preferences (for example, in the healthcare example above).
Optimisation Challenges
Individualised customer expectations have made workforce optimisation a key business challenge. Capturing information about customer behaviour and turning raw data into actionable insights provides the ability to ensure satisfactory customer impact.
This data then needs to support alignment with the WFM process. Simply optimising a roster based upon historical reports will not meet the changing demands faced by business. A conscious approach that integrates customer insights into roster optimisation is a key to high performing organisations.
The value of critical data and information
It is clear that if WFM is to be successful, then organisations who want to derive the real benefits of automation must focus on the criticality of data and information for an optimised workforce.
The spate of failed WFM projects provides sufficient evidence that without a data and information strategy, the complexity of implementation can derail a transformation project and limit its success.
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