As we all know, digital transformation is the novel use of digital technology to accelerate business strategy of an industry. In other words, it is the application of digital technologies to empower people, optimize processes and to automate systems of the industry to achieve a step-by-step change in business performance.
It’s no longer surprising news that manufacturing industries are going digital. Some of the most significant reasons for this on-going digital transformation are – higher customer expectations, increased connectivity and, technological improvements. Many industries have started to realize the long term benefits of digital transformation. If you too are planning to go digital, you can benefit greatly from enhanced efficiency of man and machines, optimized data use, increased scope for innovation, adoption of latest technology and overall cost reduction.
While manufacturing industries have put digital transformation on their agenda, barriers still remain. Decision-making processes in large industries are slow. Bureaucracy presents hurdles before an idea is considered acceptable by the management, and this is slowing down the process of innovation implementation.
Few top-most reasons for slowness / failure in digital transformation
1. Use of technology for the sake
Manufacturing industries must link technology investments to the business goals rather to “technology hype” in the market. In other words, technology use should always have a purpose—to support an organization’s business strategies and goals, but not to satisfy a desire to have cutting-edge technology. Separation between business and technology creates many hurdles for digital transformation journey. Notably, it can prevent cross-departmental collaboration, siloed departmental digital transformation projects etc.. – these will delay digital transformation altogether.
Some manufacturers overlook at the true purpose of the digital transformation. The transformation should support well-defined business strategies to deliver value to the organization through increased revenue, customer engagement, improved productivity or reduced costs. The purpose of the transformation is not to see how many different technologies can be implemented. Embracing technology for technology’s sake is not going to help manufacturers achieve their business goals – in fact, it could actually undermine the attempts.
The cloud is one such great example of technology that is often embraced without proper planning. Migrating to the cloud is typically one of the first steps that manufacturers take during a digital transformation. In many cases, they have not defined what they want to do once they migrate to the cloud, how their applications will run in the new environment or how the cloud can help them to meet the demands of customers or provide measurable business results. Such improper planning results into repatriation of workloads from cloud back to on-premise after a year or two. For more details, read my blog on “Why enterprises are moving their IT solutions back from public cloud to on-premise / private cloud?“.
Furthermore, virtually many of manufacturers in today’s world is a software company to some extent. Off-the-shelf solutions such as MES and ERP are no longer enough to satisfy the needs of an industry. Most manufacturers need custom solutions that are often developed “in-house”. Their IT department must still shoulder the responsibility for internal customers who need business applications while addressing the needs of external customers.
2. Replacement / upgradation of legacy systems is not so easy
One of the top-most technological challenge for manufacturers is – upgrading the legacy systems, both at machine level and IT infrastructure level. Today, many manufacturers are using control systems that are more than 2 decades old. Outdated hardware and operating systems make manufacturers stay away from integrating machines with IIoT solutions. Efficiency on the modern factory floor relies on interconnectivity, ERP systems that integrate across all stages of production and extensive accessibility to real-time data of machines. This way, legacy systems fall short of keeping pace with digitalization, and hence they prevent manufacturers from taking advantage of the technological capabilities that digital transformation aims to establish in the manufacturing floors.
Transforming a legacy system into a newer one requires tremendous amount of time and budget. Finding the skilled engineers or training the existing engineers to migrate an old system to a new one is challenging. Most of the legacy softwares in manufacturing world use outdated programming languages with missing technical documentations & discontinued support from software vendors. Original developers who had developed those legacy systems – might have left the organization or stepped into a new technology in new company. One another common problem for developers in existing organization is that – they never get a proper opportunity to work on newer technology just because organization don’t want to upgrade their IT systems.
On other hand, legacy systems are difficult and expensive to maintain, wherein sometimes vendors no longer support legacy systems. Many manufacturers attempt to replace few software components with latest technology just for showcasing that they are progressing in digital transformation journey. Eventually over the time, digital transformation either stops or fails.
Sometimes enterprise architecture of overall digital transformation journey will be a chaos, which is caused due to siloed software systems development by individual departments to achieve their department-specific goals without thinking about integration with other departments’ IT systems. The end result could be that, as the digital transformation project moves forward, its task force discovers that those siloed IT systems DO NOT work well together.!!!
3. Most of Proof-of-Concepts (PoC) developed using new technology never go to production
Today most large companies are looking at the potential of AI/ML, and despite significant investments, hiring data scientists and investing time and money, data science fails to take things to the production. One of the biggest challenges present in AI/ML is that a large majority of models are not deployed in production. On other side, lot of people in the enterprises have realized that typically when you have any kind of machine learning or data science work, it goes from a few weeks to develop the model, takes far longer when we talk about placing the developed models into production, maybe more than a year till the model is put into production.
As the market for AI technologies and techniques matures and grows, companies need more and better access to innovative AI models, applications and platforms. Unless things are in production, there is no return on investment. One of the essential things in data science is choosing the right problem and chasing the right solution. But, due to complicated technical details, people get caught up on and find themselves a year later having added zero value. Often in data science, projects end up being more complicated in comparison to the business value they are meant to produce.
In a Gartner’s survey of more than 3000 AI aware C-level executives, only 20% reported having AI production, and 80% said they are developing, experimenting and contemplating the use of AI. In another report by Mckinsey, the firm found that out of 160 reviewed AI use cases, 88% did not progress beyond the experimental stage.
4. Employees’ resistance to change from manual to digital way
Employees do not like the idea that Artificial Intelligent (AI) or bots will now do their jobs. The fear that new technologies will threaten their jobs will cause them to consciously or unconsciously resist the changes. Employee resistance is probably the biggest obstacle to change initiatives in an organization. Sometimes machine operators in manufacturing floor are not willing to adopt digital solutions as they have got used to manual work (paper/data entry) which they are doing since many years.
When the matter comes to executives or leaders, if things have been going well in their industry, they may not resist change because they fear that the change will not result in improvement. Focusing only on their part of the operation, they fail to realize that change is needed in order for the organization to stay competitive.
Digital transformation requires change, especially in employees involved in the manufacturing process. This is extremely difficult — not only does leadership need to be aligned, but the whole organization often needs a cultural shift with winners and losers.!! Once leaders recognize the need for change in organizational culture and mindset, they must look for key players who can accept the challenge and become change agents or champions. These change champions must inspire and connect people across departments to introduce cross-functional collaboration to an organization.
On other side, organizations should incorporate training programs to assess and develop technology, leadership and change management skills. A carefully curated team with cross-functional experience shall be formed which will have dedicated focus on digital transformation initiatives and targets. As and when key players remove boundaries between departments and people, they may face another challenge – unlocking “tribal knowledge”, without which their efforts might fail to produce a productive work environment for digital transformation to succeed.
5. Knowledge gap between departments or user groups
One of common issue in manufacturing industries is knowledge / educational gaps between departments, where some user groups are (highly) knowledgeable about digital technology and others are not – particularly between the IT and operational technology (OT) user groups. It is the knowledge locked away in siloed departments and shared only between learned groups of people, often subject-matter experts. And it is frequently a challenge for departments / user groups to work together to make the digital transformation project successful.
One possible way to overcome such barrier is to invest in training for workers to educate them in digital technologies and make them understand benefits of digital transformation projects. Preemptive cross-functional training and education can prevent considerable confusion between people as they start to work with applications outside of their regular areas of expertise.
Technology is making our manufacturers focus on improving the responsiveness and agility because of changing customer demands and market conditions. If we can reduce the time it takes us to create, receive, schedule, and process a client’s order, there is nothing like it. With this, manufacturers will be able to match production cycles and the emerging product demand levels closely. The more successfully an organization can match those two essentials, the more agility they can pump in their operations.
6. Cybersecurity concerns
Many manufacturing companies are seeing an increase in cyber-related incidents associated with the control systems used to manage industrial operations. These systems can range from programmable logic controllers and distributed control systems to embedded systems and industrial IoT devices. Collectively, these control systems make up the operational technologies (OT) that allow facilities to operate.
OT system–related investment decisions are often made on the factory floor by leaders within operations, with less involvement from corporate IT and security departments. This can lead to a myriad of different technologies, often with different security control capabilities, that will likely need to be integrated to and then managed using existing IT network infrastructures.
While the advantages of connectivity include increased levels of productivity, faster identification and remediation of quality defects, and better collaboration across functional areas, they can also multiply the potential vulnerabilities of the smart factory. In fact, the Cybersecurity and Infrastructure Security Agency (CISA) lists 1,200+ known OT system related security issues, vulnerabilities, and exploits from more than 300 OEMs and system providers. The threat landscape for the systems that control operations of a production facility has proliferated rapidly with the increase in digitization and advanced technologies.
As smart factory initiatives continue to proliferate across the global footprint of manufacturers, cyber risks are expected to continue to increase. The cyber preparedness of many manufacturers is less mature than likely necessary to protect against not only current threats, but also new threats and vulnerabilities that digital technologies create. Manufacturing organizations should invest in a holistic cyber management program that extends across the enterprise (IT and OT) to identify, protect, respond to, and recover from cyber attacks.
Manufacturing IT departments should consider these steps when beginning to build an effective manufacturing cybersecurity platform or guidelines:
- Perform a cybersecurity maturity assessment
- Establish a formal cybersecurity governance program that considers OT
- Prioritize actions based on risk profiles
- Document the data security concept
7. Lack of support and dedication from leadership team
Digital transformation responsibility falls upon leaders at all organizational levels to recognize the need for change. It requires an industry to challenge its culture, common practices, and mindset, which are products of leadership working styles and communication. Leaders must advocate the importance and benefits of change throughout their organization and come up with a strategy to address change resistance. Without effective leadership as a driving force, a digital transformation project can fail, resulting in waste of considerable efforts, money and resources. A dedicated internal digital transformation task force containing leaders/key players and stakeholders throughout an industry must be the part of that task to succeed. This task force should be ultimately responsible for steering digital transformation initiatives towards organization’s strategic goals.
8. Opting the wrong technology partner
Opting the right technology partner for a smooth transition in adopting smart factory is important in the success of the implementation. Before picking a technology partner, make sure to assess the product offerings and support they provide. Be sure that the technology partner has both, the operational and technical experience of implementing smart factory and overseeing a project that suits your corporate culture.
Opting the right partner for continued commitment and support in their services is essential with executing smart factory implementation. It is advised to identify, assess and filter a list of vendors and pick a suitable as well a reliable technology partner for an assuring digital transformation journey. Omitting the majority of technology challenges rests with the partner you pick, hence be conscious of your technology service provider and their facilities.
Key guidelines to overcome failures in digital transformation projects
The real secret to digital success for your organization is not starting with the technology but starting with humans. As humans, we are pretty much hardwired to resist change. While we all love the idea of a digital future, we don’t actually want to change ourselves, or in worst case let us get forced to change ourselves in order to achieve digitalization. To start with digital transformation, organization has to first embrace the employees which is bottom-up strategy to make employees excited about digital. Here, organization should focus fully on the teams on the front line whose work will be directly impacted by the digital transformation.
Few key guidelines to succeed in digital transformation projects are highlighted below :
- Define proper strategy and plan as an incremental model
- Incorporate digital in company strategy and priorities
- It must be an organizational initiative rather individual department initiatives + Think big but start small
- Get vendors and partner commitment and support + Identify and upgrade infrastructure for digital readiness
- Find internal ambassadors to evangelize and lead the change + They all must show real commitment
- Bring everyone along the journey + Communicate the why (both leaders and other employees)
Reskill and upskill the workforce in digital technology immediately if needness arises
- Get out of PowerPoint and get into implementation & practice
- Pilot and prove before moving onto next use case development
Educate the leadership and operators before rollout, obtain their buy-in
- Define cybersecurity guidelines and concept, and perform pre-checks before every small rollouts
- Define change management and adoption processes – Employee work culture, employee skill, organization frameworks, operations management and many such aspects should be tailored to meet the requirements of a new digital transformation journey.
An excellent approach to launching a digital transformation in manufacturing is to identify improvement opportunities that will result in significant benefits to the customer.
However, digital transformation challenges are complex to handle. Therefore, organizations need to create a substantial ecosystem to drive change seamlessly. Before embarking upon a digital transformation journey, build a strategy to eliminate the roadblocks to digital transformation, thereby ensuring successful digitization.
Please note that, investing in emerging digital technologies won’t equate to complete successful digital transformation. People, processes, and technology move hand-in-hand to form the foundational elements while strategizing digital transformation efforts. Make informed technology investments, as it will help deliver real value both to the organization and your customers.