(Originally posted on Jan 26, 2022 on the Drishti blog)
Recently, we hosted a webinar on operationalizing data for Industry 4.0 with Jim Little, vice president with Simpler Consulting, an IBM company; Alex Bredemus, partner, Deloitte Consulting; and our own founder, Prasad Akella.
In Part 1 of our recap, we came to a consensus that the modes of data capture that were previously used do not scale well with current industry demands. The non-scaling data capture problem is compounded by the fact that there is more information available than ever before, which leads to a lack of context.
In this situation, a data-rich, information-poor (DRIP) environment has been created.
As I stated in the webinar, “If the focus is not on the problem, and the value created by solving the problem is not central to the exercise (referring to the use of data and new technologies), we are wasting our time.”
The tools exist to fix DRIP
Industry 4.0 gives manufacturers the tools to fix DRIP by adding context and meaning back to the data.
Currently, problem solving is often reactive, resulting in too little too late decision making. These problems are prioritized based on bottom-line numbers, processed long after the problem has occurred. By following this pattern, context is easily lost for any information attained.
Jim stated that the focus needs to shift: Problem solving occurs in a cycle of occurrence, detection, reaction and correction, given the data that is presented. Today, an enormous amount of time is spent on the first three steps. An approach to solve this, therefore, is allowing time to actually gain meaning from the data in a useful way. More time is available for the step of correction.
Once the problem is highlighted using Industry 4.0 tools like software, AI, ML and vision systems, human talent can solve the problem.
In order to implement these solutions, investment resources are needed, which requires buy-in at the senior leadership level.
How do we get the buy-in from senior leadership?
Getting line associates throughout a business to believe in an application is key to enacting a new system. But to even get the new systems in place, first, the leadership needs to believe in its value. Here are a few tips for getting leadership on board.
Provide a meaningful narrative
Collecting hard ROI dollars can be difficult. To build your case for new tech, be clear about the problem you intend to solve with the new system. Focus on the opportunity to have problems solved faster, in a more lasting way, and assign dollar values to the solution of those specific problems. Making recurring problems less frequent lowers the cost of quality in a business. Make sure to have an executive anointed as a champion to the cause. Make them take real ownership by relating the success of the project to one of their KPIs.
Alex emphasized the importance of avoiding corrective actions and customer complaints in the first place — especially in highly controlled regulatory environments like medical device manufacturing — versus tackling the costly process of mitigating complaints and fixing errors.
Make it clear to the leadership team that by making data more meaningful and useful, we can increase customer satisfaction. We are effectively reducing many of the costs of poor quality (COPQ) that are invisible, including:
- Inventory costs long term
- Motion costs
- Waiting costs
- Overprocessing cost
- Overproduction cost
- Defects
- Under-utilization of employee skill
- Excessive employee turnover
- Expense over time
- Employee morale
State the business case to leaders from their perspective
Yes, the narrative you develop is critical to capturing the imagination of the leadership team. But the most important factor in whether they invest in new technology will be the ability to provide a clear business case. Too often this is lost in the adoption of new problem-solving methodologies because all of us tech advocates get caught up in the thrill of the shiny new object and forget that it’s meant to solve a specific problem. Leadership is open to hearing the soft narrative, but needs to hear how the bottom line will be affected by an initiative.
As in the define phase of a lean initiative, we must clearly define the project scope, its stakeholders, the problem it intends to solve and specific numbers (as much as possible) that, once delivered, speak to the efficacy of the new technology.
This includes talking about cycle times, scrap, customer returns and rework time, and translating those concepts into specific values. For example, if one business case is increasing first pass yield, the statement should be “Increasing first time pass from 80% to 90% within six months, thus saving 80k USD per year.” Then you would add the operational metrics by which the number is achieved. “The savings are achieved through a reduction of 850 hours of rework time, 200 hours of inspection time and a 15% scrap reduction. ”
Once achieved, the tangential benefits of increased delivery reliability and customer satisfaction will occur — as well as the benefits of the rest of the narrative.
Leadership wants the bottom line as directly as possible. This is the best way to get the their support in an initiative. The CFO wants to know the investment versus savings gained in terms of money in order to gain buy-in. The CEO wants to know how many more units will get out the door to customers. The manufacturing VP cares about lower cycle times and waste reduction. Each of your leaders looks at the organization through a specific lens. Use the figures that most relate to them and create your value statement.
We’ll end on that thought. Industry 4.0 technology creates the potential for aiding people from separating the signal from the noise. This will augment and aid in the growth of businesses by ultimately increasing human capability, not replacing it. For the full conversation, watch the webinar here.
