Industrial Transformation / Digital Transformation

New! Survey Snippets: How Analytics Leaders Manage Metrics


Introducing Survey Snippets

LNS Research has started a blog series called Survey Snippets that will include call-outs from our recent survey data and compelling insights for manufacturing executives. The first blog post of this series is about analytics’ role in a company’s Industrial Transformation (IX) program, and how leaders in this field are leveraging metrics to distinguish themselves from the rest.

Analytics Leaders definition

In our research on Analytics That Matter, we have identified 23% of the market as “analytics leaders” who are aware of and understand analytics and are seeing dramatic impact in their operations. The rest of the market- “analytics mainstreamers”- consists of companies that haven’t started an analytics program, and also companies that have started one but haven’t been successful at it yet.

Although analytics is one of the critical components of an IX program, a lot of manufacturers don’t leverage it ideally to gain maximum benefits. Companies should be aware that just implementing analytics does not guarantee success of their broader IX program. Supporting this, our research shows that even some of the analytics mainstreamers with an analytics program are not able to see value to their operations. The Analytics leaders, however, are already seeing dramatic impact- our research data shows that they are 2.5 times more likely to have made significant progress and success in their overall IX program. One of the ways they are differentiating themselves is how they manage metrics.

Tracking metrics is good, but not good enough

Manufacturers (analytics leaders and mainstreamers alike) are collecting terabytes of shop-floor data every day, enabling them to track more metrics than before.

In our recent Analytics That Matter research, we surveyed more than 300 manufacturers on their analytics program. We asked the survey takers what metrics they are tracking, and what they are including part of their Industrial Transformation program. The chart below shows that both the analytics leaders and mainstreamers performed pretty much similar in tracking metrics. But the leaders significantly outperformed the mainstreamers in including these metrics in their IX program improvement goals.

Percentage of Metrics-1

Why should metrics be included in the IX programs

Now that we know the leaders are including tracked metrics part of their IX program, let’s see why it is valuable. Our research on IX readiness has shown that Industrial Transformation programs are more successful when they are led with a business-focused strategic objective and supported by metrics aligning to that objective. Mapping metrics to business outcomes also helps the plant personnel better understand how their discrete actions impact overall business performance.

Value Chain

The above graphic gives some insights on translating metrics to business operations. On-Time delivery, one of the most adopted metrics in the list, impacts several points in the value chain. Any customer satisfaction related IX program should definitely have OTD as part of its goals. Similarly, a company’s IX programs should be supported by metrics corresponding to its objective.

Proactive metrics and big data analytics

Once a company connects its operational metrics to business performance, the next step LNS recommends is to identify other proactive operational metrics that can help improve the overall IX goal metrics. For example, if improving OEE by 15% is one of the IX goals, the next step should be to identify other actions or behaviors that can proactively improve OEE.

This is where big data and analytics is valuable- companies can use perform analytics on their plant-floor data to identify previously unknown relationships. For instance, insights from big data analytics could reveal that operator training and engagement could positively correlate to higher OEE, and productivity. In that case, operator training metrics could be used as a proactive metric to improve the IX goal of improving OEE.

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