Walk Before You Can Run

A Blue Print for Creating an IoT Enabled Field Service Organization

Despite the enormous benefits of IoT, field service leaders face many challenges to implementing IoT platforms.   First, many of these leaders have not defined a clear outcome for IoT projects.   In other words, they haven’t created solid use case or achieved clarity around what types of actions, decisions, or benefits they can obtain from IoT.  The possibilities are endless and often overwhelming.   Second, these leaders need to create a clear road map with respect to when, how, and where they will implement IoT.  Questions often exist as to whether they should implement IoT on their existing installed base or roll-out with new product releases.   Applying IoT to an existing installed base may seem like a time-consuming and arduous task.  However, the benefits that a FSO can achieve when a large segment of their installed base is IoT enabled is significant.  Third, IoT produces a vast volume of data.  FSOs are often not sure how they will make sense of all the data or how they will ensure that actionable and measurable results will be achieved from this information.   Fourth and most importantly, many field service leaders are concerned that they must overhaul their entire service delivery processes prior to taking advantage of IoT.  This seems like an impossible order when they may have millions of dollars invested in the current ways of doing things.

Implementing IoT does not have to be this challenging or complex.  Ultimately, field service leaders desire a solution that helps them achieve actionable and measurable results in a reasonable time frame.  More importantly, they want a solution that does not bog them down with tons and tons of meaningless data and one that enables them to work with their existing service delivery processes and systems infrastructure.

Quite often, corporations that implement IoT solutions do so within the context of a Digital Transformation (DX) initiatives.  These initiatives typically involve a complete re-design of the service model.  While they have positive impact on the customer experience and share-holder value in the long run, they maybe counter-productive to the near term objectives of field service leaders to support their customers’ installed base on an efficient and productive basis.  This is because DX initiatives require corporate buy-in, multi function coordination, dedicated investment capital, and considerable time to implement, whereas field service leaders are more pragmatic and want results now.

The best approach for field service leaders is one that enables them to implement IoT in parallel to larger, corporate DX initiatives. By doing so, FSOs can realize short term gains within the context of serving their current installed base using the FSO’s existing infrastructure and service business model.  This approach reduces the requirement to re-design the entire business model and postpone the realization of results that are possible through IoT.

Field service leaders can think of this transformation as “a walk before you run” approach to implementing IoT.  It requires field service leaders to think of IoT in terms of moving from a reactive service model, to conditional, to prescriptive and finally to a predictive service model.  Reactive service is the modus operandi of most of today’s FSOs.  Service is provided when the customer acknowledges they have a problem and request a solution.  Conditional service represents the next phase in the transition to IoT.  It uses IoT technology to monitor the customers’ installed base and provide alerts to the FSO that service is required. This enables the FSO to be more responsive to customer issues, ensure first time fix, and minimize downtime.  A prescriptive model is one in which the alert includes a recommendation or instruction about what action the FSO should take next.  Predictive service goes one step further. It monitors the customer’s installed base to anticipate service events and take corrective action before they occur thus avoiding downtime altogether and eliminate operating costs and overhead from the service operation.

The time for FSOs to think about implementing IoT is when they are replacing or upgrading their Field Service Management Software.  Perhaps the requirement for IoT alone is the primary reason why a FSO would want to upgrade or replace now.  Assuming this is the case, FSOs are advised to seek out software vendors who offer IoT feature functionality as part of a complete solution. This will minimize the number of moving parts (e.g., vendors, applications) that need to be included in the solution.  This in turn will lead to reduced implementation costs, an efficient process, and less headaches for the FSO.  In addition, it will ensure that the IoT solution works within the context of existing service delivery processes and procedures as opposed to the other way around.  In this way, FSOs can walk before they run.

 

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IoT’s surprising impact on revolutionizing inventory management

Sarah Hatfield directs OnProcess Technology’s strategy for products and core service offerings, including the OPTvision platform. She brings more than 15 years of leadership expertise from previous roles in supply chain, product and program management for Comcast, Asurion and ADT.

You know disruptive technologies have reached the tipping point when non-IT pros build business plans around them. This is exactly what’s happening with IoT. Because of its ability to drive wide-ranging, game-changing improvements, IoT is starting to be used across all aspects of business operations. One of the newest, and most impactful, areas is spare parts inventory management, a key aspect of the post-sale supply chain.

Maintaining the right level of spare parts is critical. As you can probably guess, carrying excessive inventory can be prohibitively expensive. But if you have too little, you’ll slow product repairs, hurt customer experience and end up spending more money purchasing new parts for stock replenishment. The problem is, traditional best practices for managing spare parts — using time-series algorithms combined with sales forecasting, seasonality, gut instincts and simple rules of thumb to determine how many parts to stock — are woefully inaccurate because:

  • They’re static, “review-and-stock” endeavors based largely on historical demand data
  • The algorithms don’t account for variables resulting from failed parts in the field

Knowing this, many companies hedge their bets by purposefully overstocking. Others think they’re maintaining the right levels, but unknowingly overstock. In either case, they’re wasting a lot of money.

New IoT-driven inventory planning

The key to accurately stocking parts is knowing which ones are likely to fail and when they’ll need to be replaced. Some businesses have attempted to use IoT data to understand product failure impacts on inventory planning. However, most of the IoT monitoring programs are designed to respond to signal failures. Plus, IoT data collection is often haphazard and emphasizes the few pieces of equipment that are starting to fail, rather than the whole. This makes it impossible to generate a sound baseline for analyzing product performance and predicting failures — which, in turn, makes it impossible to accurately forecast spare parts needs.

The good news is there’s a new inventory planning algorithm that builds IoT-based failure data directly into the equation. Developed at Massachusetts Institute of Technology Center for Transportation and Logistics, it enables businesses to accurately forecast needs. By using this methodology and analyzing historical failure data on the entire installed base, businesses can predict the exact spare parts they’re likely to need, when and in what quantity.

The better news is that it doesn’t take a huge team to capture IoT data because not much data is needed…. Read More