About 20 years ago, the first dashboards made their way into German companies. Today, these visualizations are considered indispensable for efficient corporate management, as they promise nothing less than comprehensive transparency at a glance. But in practice, it is often not that simple. After all, a dashboard is only as good as the key figures on which it is based. The time that goes into defining individual metrics and building in-house IT expertise is therefore well invested.
Managers at all levels need information to make informed decisions. It sounds all the more tempting to have this information in front of their eyes at the crucial time in a clear format like a cockpit. So much for the compellingly good idea behind dashboards.
However, experience shows that many of these visualizations confuse rather than inform. Often, they have grown historically and are overloaded for their current task; many do not serve the corporate strategy. Frequently, the figures displayed also turn out to be a compromise between what one would like to have and what each department can deliver with minimal effort. In the worst case, information is manipulated because employees know how to circumvent and/or trick their systems, for example, to keep figures in the green - and occasionally orange - zone.
Wrong numbers, wrong consequences
Faulty data from dashboards, then, can be a massive obstacle in shaping future opportunities, such as when deficiencies are not addressed, skills are not developed, or when dashboard review meetings devolve into pro forma events that tie up time unnecessarily. In underperforming companies, the discrepancy between what their dashboards say and true economic performance can have particularly dramatic consequences, as the confidence of banks, investors, and employees in the numbers presented erodes.
Despite the shortcomings that exist, the potential that lies in the use of dashboards is undoubtedly enormous. Three things companies should keep in mind:
The relevant KPIs must be derived from the corporate strategy. Whether a company's primary goal is to grow, to stabilize after a period of growth, or to strategically right-size must be reflected in their dashboards’ KPIs. The KPIs must reflect the strategic thrust and be taken seriously - especially if they do not (yet) show that set target have been achieved. The approach of a customer who, after investing heavily in machinery, initially defined OEE (Overall Equipment Effectiveness) as a KPI and then discarded it due to poor results in order to focus on the productivity of its workers is not suitable as a role model.
Companies must build up internal (IT) competencies. In many companies, IT is not considered to add enough value. As a result, there is a shortage of qualified personnel to keep the company up to date with important technologies and current opportunities. Sure: data experts are scarce and not exactly cheap. Nevertheless, they are "worth it" because, if used correctly, their leverage is enormous, as they can massively increase the effectiveness and efficiency of all other resources. But external experts are not a must. Companies can also start with a small team of data enthusiasts from individual departments who, with a PowerBI Pro license for EUR 10 per person per month, can create the first dashboards. All that is needed is good master data, basic data literacy, initial experience with databases and a clear commitment from management to the team and their task. The necessary starting know-how can be conveyed and/or deepened with two-day training courses.
The technology to automatically refresh dashboards with current data (see below), if desired also with a self-service function for a deep dive, is now mature. The implementation, maintenance and further development of such systems is largely commoditized. For many applications, companies do not need complex IT projects with artificial intelligence, machine learning or deep learning. The critical success factor is rather the conscientious handling of data.
KPIs must be understandable and continuously refreshed. What can a machine operator do with the sales figures for the past twelve months? Correct: nothing. He will be more interested in the number of pieces produced, total downtime or the defect rate. That's exactly what his dashboard should show - and as comprehensibly as possible.
The CTO or CEO, on the other hand, is interested in other key figures. That's why every decision-maker needs his or her own dashboard. Accordingly, leading companies no longer practice rigidly timed dashboard reviews lasting several hours, but instead work with a curated selection of information that is important to the recipient or the group of recipients. In most cases, these are no more than 40 to 45 key figures - but with real relevance for the company's success. The presentation of these figures should also be regularly reviewed and updated to the changing needs of business and decision-makers if required. Speaking of adaptation, the selection of underlying KPIs should also be reviewed regularly, preferably every three months, and updated if necessary. The world can change quickly, so KPIs can have a limited shelf life.
For some companies the above points, as basic as they sound, will resemble a mammoth task. But the distance to the benchmark is getting bigger day by day. This should not lead to the conclusion that the challenge should not be taken up at all. On the contrary: companies who have not yet seriously considered dashboards have the advantage of learning from the mistakes of others. This enables leapfrogging to the current best practice, i.e. bypassing costly teething problems.
The goal is for executives to shift their focus - from monitoring retrospective numbers to identifying tomorrow's problems early and having enough time to solve them.
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