“Digital Transformation” is a broad term that can mean vastly different things to different people. Within a given company, it’s easy to gain consensus that such a thing is necessary to stay competitive, but it’s tremendously difficult to define what it looks like in practical terms—much less where to start.
Of course, it wouldn’t be feasible to lay out a sequence of steps that’s right for everyone in every industry. Instead, it’s more useful to talk about digital transformation in terms of levels of maturity, each centered around the key variable needed to make the process sustainable: return on investment (ROI). It’s not hard to argue that one must spend money to make money, but for digital transformation to be beneficial and long-lasting, it has to compliment business goals. And the expected ROI as measured against these business goals must be realistic for the current level of digital maturity. There are five such levels.
1. The Experimental Stage
An organization that is in the Experimental Stage has acquired some basic digital tools but still lacks a cohesive vision for what it hopes to achieve. Solutions built during this stage are commonly built by intellectually curious individuals attempting to solve small-scale problems. These efforts can provide an ROI well-aligned to business priorities within the area of responsibility for this individual, but these contributions are not likely to be easily scalable or repeatable.
2. The Aggregation Stage
Organizations in the Aggregation Stage are recognizable by their ongoing efforts to collect increasingly more data in one place. These efforts may vary wildly in terms of specificity. Some may narrow their focus to a specific target area of the business so they can quickly move on to the next phase of this maturity model within this scope. Meanwhile, others will attempt to collect as much data as possible with which people across the organization will be empowered to create their own solutions. Regardless of scope, for ROI to be realized at this stage, discipline is critical. Data shouldn’t be gathered and dumped in a data lake without some sort of layer of context added to it. Adding this meaning to it will help ensure it can be effectively wielded by as large a group as possible.
3. The KPI Stage
Well-designed key performance indicators (KPIs) reflect how well something is doing within a given scope (such as enterprise, division, area, or unit). An organization in the KPI Stage would hopefully leverage them in two ways. First, these KPIs would guide both short-term and long-term strategy. ROI here comes from strategic decisions being backed by evidence. Secondly, by setting tolerable ranges for KPIs, the business can be alerted when a particular group may be falling behind and in need of help. The ROI is realized here by making sure everybody in the organization is able to play their part in the overall business strategy and is getting the help they need in order to do so.
4. The Prediction Stage
Once enough data is available to form KPIs that reflect how individual groups are contributing toward overall business goals, organizations in the Prediction Stage are in a good position to forecast what state a system will be in and when. This impacts ROI in two ways. First, it is possible to carry out interventions pre-emptively if a downward trend with respect to an important KPI is detected early enough, whether this means mobilizing resources or changing strategy. The second impact revolves around the refinement of this strategy. More robust models of the interplay between variables means evidence can be more effectively wielded to achieve the intended outcome. Notice that this stage is very similar to the previous one, but the matter of timing makes it worth a category of its own.
5. The Actuation Stage
Unlike the preceding levels of digital maturity, organizations in the Actuation Stage are able to start using digital tools not just for “knowing” but for “doing.” This means an organization’s prediction capabilities have earned so much confidence that digital tools no longer just inform decisions but are able to carry them out themselves by working alongside operations teams in real-time.
An excellent example of this is Honeywell’s Advanced Process Controller (APC). Typical process control strategies make it so that an operator doesn’t have to worry about things like how far to open a series of valves in order to reach a target flow. Instead, an operator specifies a desired setpoint and the control system makes the necessary adjustments to reach this desired state. But with APC, the operator doesn’t even need to do that. Instead, the APC combines the data available to it with the predictive models it’s been provided. The APC is then able to change the setpoints directly in order to optimize the KPI it’s been instructed to. The ROI seen at this stage can be quite lucrative. Not only does automation allow for a much finer level of control that can more rigorously optimize for business-critical output variables, but it frees up human operators’ attention for other things.
Needless to say, advancing through these stages can be quite an undertaking. Many companies will begin with a jagged maturity level, meaning that they may simultaneously occupy several levels because of the different capabilities possessed by different units. Again, ROI should be a key variable for prompting leaders on where to focus. Having a clear idea of ROI should give leadership an idea for what amount of resources can be viably committed as well as what their expectations should be along the way. It’s a journey, and they have to be able to sustain it over the long-term or risk leaving a shameful amount of value on the table.
Furthermore, leaders of organizations pursuing digital transformation should strongly consider partnering up with those with experience on this journey already. There is a rich ecosystem of vendors and service providers that offer the tools and the expertise needed to develop a transformation plan, put it into action, and keep it on track. A service provider with a proven track record, in particular, can help answer strategic questions regarding which business problems should be addressed during this journey and can also help answer the tactical questions regarding how that should be done. The skills needed for such an effort can be hard to find. Even if the intent is to build these capabilities in-house, filling these roles can take precious time and the people already there are often stretched thin. Frequently, they themselves would benefit from partnering with technical experts at the intersection of traditional engineering, automation, and software development.
—Zachary Burke (Zachary.Burke@radixeng.com) is a senior systems engineer at Radix Engineering and Software. A mechanical engineer by discipline, he specializes in operational intelligence solutions for industrial companies.