The importance of ‘Services’ as a means to both grow revenue and create a reoccurring business revenue stream is well accepted, but increasingly Enterprises find they are competing on the quality of their Services. Traditional measures focus on customer responsiveness and satisfaction, balanced with competitive cost/price reduction, achieved by using recognized multi-point action plans. But IoT and AI are introducing a game change to existing Service Maintenance as well as placing Service Management in the front line of Digital Business transformation.
The Digital Services economy is transforming the role of Services from add-on revenue, after a successful product sale, to the basis for the entire Enterprise Business proposition in the shift from ‘Goods to Outcomes’. Customer expectations of this new generation of Service centric contracts are high. Field Service organizations should aim to play a key role as early implementers of Digital Technology in their existing operations.
Field Service Managers are unlikely, to lead Enterprise strategy, but they should aim to play an active role using their long practical experience, now supplemented with new knowledge on applying Digital technology capabilities.
The early adopter market of ‘try it and see what works’ in applying IoT sensing to machines to record breakdowns, or better still, to provide advance warning of potential failure has finished. Case studies, featuring well-known global enterprises, are available to define best methods to maximize business value across a wide range of industry sectors and deployment types. IoT sensing is well on the way to transforming Operational Management using data that was quite simply previously unavailable.
Field Service Management, is a constant set of dynamic events, requiring complex multiple factor optimizations, since the advent of Mobility various Field Service Applications have done much to improve efficiency. IoT adds ‘real time’ data inputs from machines, engineers, and any other dynamic source, creating a comprehensive and cohesive ‘Digital’ picture across the Field Service operation. The real value comes from making use of the this new rich Digital data through the introduction of AI, (Augmented Intelligence).
The ability to ‘Read’, all events, and activities, as they are happening, makes previously unrecognized facts, links and issues visible, but the Digital Business transformation lies in new capabilities in applying Intelligence to optimize the ability to ‘Respond’.
The complex mix of events and activities that make up Field Service Management ranging have long benefited from well-designed process oriented Enterprise Applications. Increasing the data available to the Field Service Application suite by using IoT inputs has obvious benefits, and Software vendors have been quick to add IoT based capabilities. Now leading Field Service Management software vendors are adding new Intelligent features to take optimization to a further level.
The trap of focusing on ‘Read’, through mass IoT sensor deployments, without the corresponding focus on ‘Respond’ application capability, is perfectly illustrated in the sad story of a major airport operator. Keen to improve lift utilization for passengers in their terminals seventeen data values were specified for IoT sensing to track the operational parameters of each lift. The resulting mass of data both flooded processing and network capacity with the result that only three sensors in each lift are now in use.
The route to value is usually realized better by starting with Business identified ‘Respond’ capabilities that offer the highest value. The capabilities, and limitations through lack of data, of the existing Field Service Management software implementation, and its latest upgrades, are an effective and practical starting point.
Selectively applying IoT sensing in support of the existing Field Service Management application new functionality linked to the areas identified for improvement is a fast track to incremental improvement. It also builds the foundation for the introduction of transformational change in the wider deployment of IoT and AI based Digital Technology. It’s important for Field Service professionals to recognize the basics of the wider picture of changing technologies and impacts on business that Digital Technology is introducing.
Enterprise IT applications provide Systems of Record for transaction recording to create the data necessary to enable across enterprise-automated processes. The internally focused Enterprise Back Office operations have been transformed by the era of ERP Systems of Record. In externally driven dynamic operational areas, such as Field Service Management, a different approach is required increasingly referred to as Systems of Engagement. First identified by Geoffrey Moore the term embraces all technology that allows an Enterprise to ‘engage’ with activities and events that are not part of its controlled internal Systems of Record.
Systems of Engagement have emerged through social tools, mobility, Apps, and of course IoT, all of which revolve round unstructured activities, and events, that fall outside the capabilities and requirements for IT Systems of Record. The technologies of CAAST, Clouds, AI, Apps, Services and Things, come together to transform an Enterprise capability to ‘Read and Respond’.
It might seem obvious to link this to the definition of the Front Office, but this term remains focused on direct Sales activities and processes, instead terms such as Systems of Intelligence, or the the Middle Office are being used. Though this maybe new to many sectors the architecture of Front Office, Middle Office and Back Office has supported high frequency financial market traders using intelligent programs to handle ‘real-time’ market data activity for quite some years. Financial markets and businesses are Digital markets and businesses making the experience directly applicable to the wider introduction of Digital Business.
The transformation of the Enterprise, including Field Service Management within it, takes place around the integration of the three ‘systems’ each with its specific tasks and technology;
Read; Systems of Engagement providing ‘Event’ data from IoT, Mobility, etc.
Respond; Systems of Intelligence driving AI optimized actions based on data
Record; Systems of Record capturing transactions to maintain historic data
To deliver; ‘The focus on ‘Read’ needs to shift to ‘Respond’’ means adopting IoT to acquire the necessary data to act upon, and increasingly deploying AI to introduce the intelligence to optimize actions. A successful adoption can start with incremental adoption to improve Field Service Management operations using existing applications.
Though there is general consensus as to the major capabilities required in a Field Service Management Application, or more likely suite of functions, at a detail level there are differences of focus. Developing new functionality upgrades based on IoT and AI capabilities has added to that differentiation of two major Field Service Management software vendors, IFS and ServiceMax. Both have invested heavily in IoT driven ‘read’ additions to their existing products, but see differences in focus in developing their ‘respond’ functionality. The role and capability of Intelligence is crucial and that introduces two further vendors whose approach extends to Field Service from the enablement of a Digital Enterprise; Salesforce Field Service Lightning and SAP Leonardo
The differences in the four vendors approaches are important to understand, as the strategic direction of their product development is likely to emphasis the initial selected focus. The following is intended to highlight key product focus, and is not intended to indicate other features are excluded.
ServiceMax; Acquired by GE as part of its strategy towards becoming a Digital Services company the focus is on product management aligned with GE investment in Digital Twins. For product manufacturers whose Digital Strategy is replace selling their products with providing the use of the product as a ‘Service’ the ServiceMax focus on Service Management of Assets is important. Key capabilities use inbuilt, or add on, IoT sensor data to feed intelligent analytics able to predict failures, or poor performance, from deviations in expected norms.
IFS; Focus is towards the complexity of Field Service activity management by adding to their suite of functional process management intelligence assessment and optimization of ‘real-time’ data inputs. The many stages and interdependencies of Field Service activities are now incorporated into the decision making process to optimize use of resources and activities. Independent Service Operators who may not have access to the inbuilt IoT sensor data will find the focus on field operations important.
Salesforce; Business model has always been based on provisioning as ‘Services’ and though best known for their ‘sales’ or Front Office capabilities, their Service Cloud integration and Einstein applied intelligence provides the Middle Office architecture underpinning a Digital Enterprise. Recent releases have seen innovative capabilities, such as visual recognition of parts, added to the Salesforce Field Service offerings. The focus remains improving revenue by increasing customer satisfaction through integrated operations.
SAP; The introduction of SAP Leonardo and ‘Systems of Intelligence’ brings IoT and AI into Digital Enterprise integration including Field Service operations. The combination of SAP HANA and ERP enhanced by SAP Leonardo capabilities around applied IoT and AI coupled with existing data allow ‘real-time’ events and activities to be combined existing processes to create Enterprise level optimization. The focus is on Digital Business outcomes, including in Field Service, as the starting point for deployment.
Field Service Professionals will recognize the value IoT and AI enhancements can bring to their existing systems. However it’s more difficult to recognize the strategic product direction of leading software vendors. In particular the implications between the development of the Enterprise Digital Strategy and selection of Software vendors should be considered. Field Service Management is ideally suited to IoT + AI function optimization and makes an excellent early area for Enterprises to test their strategy and experience Digital Business capabilities. Field Service Professionals should recognize this and make sure that their efforts form part of the overall Enterprise Digital Transformation strategy.
As usual the devil is in the detail, and that’s where the Enterprise strategic ambition for a future Digital business model will need to address to provide a key part of the evaluation and adoption of the Digital Field Service Management product.
Appendix
A listing of blogs that are providing insightful views on Field Service Management and its challenges can be found at; http://blog.capterra.com/best-resources-for-field-service-management/
