As the investment in digital transformation projects continues to grow, so does the number of failed initiatives. How can companies maximize their chances of success?
A wave of digital transformation projects has swept through industry in recent years, as a combination of technologies promise smarter, more productive ways of working. According to a major survey of businesses in the UK, US, France and Germany1, digital transformation efforts are accelerating. With respondents planning to spend over 10% more on digital transformation projects in the next 12 months, compared to the previous year.
This scramble to reap the benefits of digital has left many companies struggling to show substantial improvements. Only 14 percent of business executives polled by McKinsey in September 20182 said that their digital transformation efforts resulted in sustained performance improvements. With just 3 percent reporting complete success at sustaining change.
That makes digital transformation projects seem like a pretty poor bet. But is that really the case? Why do so many digital transformation projects fail and what’s the best way for companies to shift the odds in favor of success?
The good news is that the most common reasons for under-performance are relatively easy to identify. As are the solutions – provided you know what to watch out for.
Define your goals
The sheer breadth of what most people mean when they talk about digital transformation creates a major obstacle between the desire to benefit from digital transformation and achieving that goal in practice.
A bewildering array of smart technologies can be applied across almost every aspect of the business, from cloud delivery and machine learning to the Industrial Internet of Things (IIoT), data analytics and artificial intelligence. Choosing the right technologies is a key factor impacting the chances of success. The McKinsey research showed that organizations with more successful transformations tend to deploy more digital technologies than others. For example, 45% of all respondents at companies with successful transformations use IIoT. Compared to 33% of customers with unsuccessful digital transformations.
And if the choice of technologies is confusing, where best to apply them and how to measure success can be even more difficult to pinpoint. All too often this leads to a lack of focus, with no clear value proposition and no clear end point.
This makes digital transformation a hard sell in the C-Suite, who see proposals for a long-term project that demands major investment of time and resources without a predictable and easy-to-measure way to guarantee a rapid return on investment (ROI). No wonder CIOs face an uphill struggle to get sponsorship from the rest of the board.
The answer is to break down the concept of digital transformation into manageable chunks. Trying to tackle too much at once leads inevitably to mission creep and project fatigue.
Instead build support for a series of smaller, self-contained projects in carefully defined areas that can quickly deliver measurable benefits. Succeed in one area first, learn the lessons and then apply them to the next iteration. It’s a familiar approach to anyone involved in ‘agile’ delivery, where proponents break down a larger project into a series of short chunks or ‘sprints’. Each of which delivers a parcel of benefits before moving on to the next.
Senseye’s Predictive Maintenance solution, Senseye PdM, answers all these points.
- It delivers a clearly defined set of measurable benefits in the form of drastically reduced downtime (typically 50%), reduced maintenance costs and improved efficiency.
- These benefits result in an average payback of less than three months.
- Senseye PdM is a ‘ready-made’ product, not a platform that requires customization, meaning that deployment is quick, and results can be seen within 14 days of use.
Users are the ultimate judges
It’s not only the company leadership that needs to be convinced about the wisdom of adopting new technologies and ways of working. The personnel who are going to be using the proposed new digital solutions are just as crucial. Without proper buy-in at the user level, even the most sophisticated solution is never going to be embraced and used properly. Meaning it can never deliver the hoped-for benefits.
The answer is to get users involved early so they can check that any proposed solutions include the key attributes that will make their working lives easier. If you’re looking for a solution to help you transition from planned maintenance to predictive maintenance, for example, it needs to be something that maintenance personnel will find easy and convenient to use. It’s all about enabling people to make better decisions.
Going it alone is a big risk
Trying to do too much in-house is another common stumbling block.
Many organizations have their own data analysts. In the case of schemes focusing on maintenance regimes, these in-house experts may even be able to model the behaviour of an asset. Even if a company is fortunate enough to have the resources to build a robust, customized data model, they’ll soon come up against deployment issues as they try to create a front-end to suit a variety of potential users. Ultimately, the resources and time required to come up with an acceptable in-house solution are likely to be prohibitive.
The answer is to engage a provider with access to a well-proven generic model, such as the Senseye PdM. The chosen partner should have a strong industrial understanding in addition to expertise in data analytics. This will ensure that the chosen solution won’t be tripped up by practical considerations such as usability.
Senseye PdM provides the ultimate, practical solution for Predictive Maintenance.
- Algorithms can only deliver good results when presented with good quality data. Senseye’s industrial experience working with a range of industries and assets and strong partner network enables us to advise companies on the optimum instrumentation to monitor the behavior of each asset or asset class.
- Senseye PdM easy-to-use interface offers clear maintenance advice, which is tailored to match the priorities of users. Training typically takes less than one hour.
The challenges of digital transformation are very real. However, recognizing the biggest potential pitfalls and taking steps to avoid them gives companies the best possible chance of becoming a success story, not a casualty.
Want to find out more? Read our blog on how to derive genuine business value from data science or book a demo of Senseye PdM and begin a digital transformation that will deliver real business benefits and a rapid return on investment.