Dr. Deming's PDCA cycle continues to be the foundation for achieving success using management information and data analytics. You also need to organize a learning system and facilitate it with data. Set goals and targets based on defined KPIs, regularly evaluate and adjust them (plan, act). Consistently use data and information for analysis and action (plan, do). Use data and information to improve and innovate (do).
An important lesson learned from Jim Collins' Hedgehog Concept (2004) is that passion alone is not enough. Passion is an important starting point, as we've written previously, and a prerequisite to motivating the organization. But when passion becomes unbridled and unstructured, it becomes difficult to establish a structural change - one that is sustainable, relevant, and impactful in our modern, volatile world. You don't want to be a one-hit wonder, after all.
All those different phases of the PDCA cycle and data-driven working may sound nice, but what about the implementation? How do you keep the continuous improvement cycle going? Here are five tips for successfully implementing data-driven improvement cycles. The number one tip for data-driven working is organizing feedback on an organizational level. How can you ensure that people feel like they're in a safe environment to learn, make mistakes, and say what's on their mind?
Many organizations are stagnant. In their current forms, they've been hierarchical strongholds for decades, where craftsmanship has been reduced to mindless work and all the fun has been "managed" away. Learning remains limited to annual performance reviews. Action isn't taken until after the fact, when the mistake has already been made. Organizations that aren't in motion, that aren't constantly trying to learn and improve, eventually cease to exist. Decay affects any system that isn't maintained and developed. The organization has to be kept in motion by continuous improvement. PDCA is the perfect vehicle with which to do that. But that only works on a larger scale, where every step of the PDCA Cycle is loaded with the correct data and accompanying BI tools.
From a top-down view, data-driven management enables the (necessary) transition from the management-driven style of improvement ("papering over the cracks") to actual data-driven improvement. Autonomous, entrepreneurial employees; short-lived, modern customer-focused strategies; and flexible structures are the contours of the intelligent, data-driven organization. They're the same ingredients you need to be agile and adaptable. In short: how do you get from management-driven to data-driven continuous improvement?
It takes more than just a plan to make people take action towards continuous improvement. A good plan helps to accomplish product development, or to improve a service or capitalize on a market opportunity, but that's not the starting point that intrinsically motivates people. Martin Luther King Jr didn't say: "I have a plan!" And he certainly didn't say: "I have a planning!" He shouted: "I have a dream!" A dream is a motivational vision of the future - a plan, or planning, is only a roadmap to get there.
Part one of our NPRS case study describes how the social work program attempts to put people back on track to gainful employment. The real trick isn't putting people to work, however, but keeping them there. How did they put people to work without them backsliding? Read part II of our NPRS case study. If your only KPI is "number of people put to work" (Plan phase of the PDCA cycle) and every action is focused on this (Do phase), you're essentially creating a problem: a situation where even people who struggle with addiction, or who have no permanent residence, are put to work. But addicts or people with a complex home situation, or no home at all, are unlikely to be able to hold down a job. They often can't be sustainably employed. The odds of this group returning to the social security safety net are huge.
How do you use data to improve processes structurally? Collecting data or structuring alone is not enough. The biggest challenge is using data to really learn and improve. Interweaving (big) data with daily learning through PDCA cycles leads to the greatest value. The case study of the National Program Rotterdam South (NPRS) shows how employees used data to continuously improve. Through topics like process thinking, different learning levels, and their effects on decision-making we will show you how to develop an intelligent organization, where continuous improvement using data is the key.
"Life-saving BI", some Dutch magazines called it. "A smart logistical solution, made insightful with a dashboard", Martin Smeekes (director of ambulance care) and Anouk Schoemaker (business and BI manager) humbly describe it. However you call it, the "Call to Balloon" project earned the Safety Region North-Holland North the predicate of Smartest Organization in the Netherlands (2015). And, more importantly, 20 minutes of crucial time for patients with immediate cardiac issues that need angioplasty. Those precious minutes can mean the difference between life and death.
Passionned Group recently researched the success factors driving Business Analytics. The research also revealed a list of the biggest blunders in Business Analytics & BI projects, which hadn't been published until now. Here are the biggest blunders to avoid. Our research compared 389 organizations on countless aspects related to Business Analytics. We asked these organizations whether or not they can demonstrate their successful use of BI. The successful organizations were put into group 1, and the less successful organizations in group 2. Then we examined the differences between these groups on each individual aspect.
Data-driven improvement cycles help you to keep making the right moves quickly and reliably. But why should people want to do this? Where do they get the intrinsic motivation to want to embrace data-driven working? Why should people want to take charge and be in control? The answer is simple: because data-driven working has a huge number of benefits. This blog will cover the six most important benefits of data-driven working.
Let's take a look at a case study: a large housing corporation has a reputation for being an innovative, ambitious real estate agency. They operate in a dynamic market, which is one of the reasons they started the transition from being a task-oriented to a more completely process-oriented organization. The (SMART) goals in this transition are organizing smarter, making processes lean, and driving the most critical success factors. The company is getting ahead of the measures that are expected to come from local and European governments in the coming years. Those measures will have financial consequences.
The increasingly dynamic world and growing mountain of data impacts the way in which intelligent organizations develop their products, services, and IT. They have to be agile by working and thinking in short cycles: agile working through scrum. Traditional project management and product development according to the waterfall method has had its day. In many cases, it's too sluggish and unresponsive. The difference is not unlike repairing clothes with needle and thread instead of a sewing machine.
The world around us is changing faster than ever. But most organizations aren’t agile enough to keep up. In China they can make a new car faster than you can make a PowerPoint presentation. The agile organization requires agile employees, autonomous, self-steering teams, a decision-making layer in the organization, and excellent information provision. Here are some reasons why agile working is a necessity:
The difference between genuine key performance indicators (KPIs) and no KPIs (or false KPIs) is night and day. Genuine KPIs directly impact the three most important result areas of the organization: profit, employee satisfaction, and customer satisfaction. Normal (performance) indicators like revenue or profit margins don't directly impact all three of these, or only do so with a greatly delayed effect.
Earlier, we covered several methods of defining the right key performance indicators. Many organizations still use "false" KPIs: they may be indicators, but they're not necessarily key! There are several negative side effects of measuring performance using false indicators instead of genuine KPIs (de Bruin, 2001). This can lead to perverse incentives and negatively impact the business. Below, you'll find seven common pitfalls of working with false KPIs.
Valuable insights can be found not just in KPIs, but also in good management information systems. These insights, when used well, can really make a difference. They could, for example, instantly reveal that you can save millions of dollars. Or that the lead time in a process can be greatly reduced. Or that you can substantially increase your market share. An insight could reveal that you can increase the quality of a product with a single action. Unlike KPIs, such insights can be financial. Sometimes, these insights also contain KPIs.
Four years ago, when we published the second edition of this survey, we saw that not many ETL tools had good, reliable functionality for real-time application integration (EAI) projects. Since then, many ETL tools have added tools for real-time extraction, transformation and integration, and there has been an almost complete convergence between ETL and EAI tools into a new market which is being called Data Integration.
Not all indicators are genuine KPIs. Finding the right KPIs for your company can be a lot like looking for a needle in a haystack. To make your search a bit easier, we've described the 7 hallmarks of genuine KPIs, allowing you to identify and build on them more quickly. What sets a Key Performance Indicator apart from a regular indicator? This question is the key to a lot of the confusion surrounding KPIs. Using the 7 criteria below, you can determine if your indicator is truly Key, or just another gauge on a dashboard somewhere.
Business Intelligence is essential to the effective and efficient manage of any organization. Managers can't get insights into operational performance fast enough. Fortunately for them, BI software is becoming easier and easier to use. Managers don't have to rely on stressed IT staff to provide the right data anymore. Long live self-service BI! Right? Well, yes and no. There's a danger to using data in this way. If you don't take the limitations of self-service BI into consideration, its success rate is very slim. Our 6-step improvement plan reinforces the foundation of self-service BI.
Defining the right KPIs (Key Performance Indicators) alone won’t get you where you need to go. The biggest challenge is taking data and using it to continuously learn and improve, and eventually achieve better performances. Intertwining KPIs and (big) data with the daily process of continuous improvement using so-called PDCA improvement cycle leads to sustainable value creation. Doing this will let you reap the advantages of working with KPIs while operationalizing the results.
Earlier, we covered two different approaches to defining KPI requirements: the strategy-driven approach and the process-driven approach. Today, we're covering two other methods: the data-driven and the market-driven approach. The data-driven approach defines KPI requirements using the registered data in the information systems supporting the business operations. External data sources could also fulfill the information requirements. An intelligent organization will also consider any other potentially interesting sources. Possibly even sources that don’t exist yet, but that have the potential to generate a lot of interesting data. For example, (IoT) sensors built into pills, trucks, or plane engines. This approach works as follows:
Earlier, we covered the strategy-driven approach to determining KPI requirements. Today we'll cover the process-driven approach. Closely examining your business processes in the framework of the process-driven approach will give you insight into how your organization adds value, and how you can measure the performance of its activities. The business processes are a crucial starting point for defining the information needs and improving the performance of the organization (Kerklaan, 2009; Van Leeuwen, 1997; Tideman, 1993). This approach gives “certainty” that the required information is also relevant for the user. “Every company on earth consists of processes. Processes are what companies do” (Hammer, 1995).
Research among almost four hundred organizations has shown that the famous PDCA cycle (Plan-Do-Check-Act) is crucial to achieving better business results. Not only can it improve your profit margins and drastically reduce workloads, it can also lead to increased customer satisfaction. Dr. Deming's quality cycle has proven to be the foundation of using management information and KPIs to achieve great success.
There are various approaches you can use when identifying, defining, loading, benchmarking, visualizing, and operationalizing Key Performance Indicators (KPIs). This article will discuss the strategy-driven approach, a top-down method where the mission, strategy, and goals of the organization are the starting point. To start off, we’ll answer the question of how to derive a strategy from the organization’s mission, and how to derive indicators from goals.
The number of projects, programs, and portfolios is rapidly growing all around the world. Over the past forty years, project management has become a prominent discipline that's undergone a lot of development and has become highly visible. However, despite this growth in the field, the amount of successful projects isn't growing at the same rate. Studies show that only twenty percent of all projects are completed successfully. The biggest culprits that cause failure: limited budgets, poor communication, unmotivated team members, not enough time, wrong priorities, and scope creep.
The world around you is changing. Your organization is changing. The demands the organization places on management information is also changing. There comes a point where you realize that your current tools are inadequate in this new moment. You need newer, modern Business Intelligence tools. But what should this tool be able to do? Polling the organization reveals a diverse set of needs and wants from the various employees, depending on their role in the organization. You may begin to wonder if there are any tools that meet all your needs.
In a recent poll on our website about Business Intelligence, we asked visitors to give us their opinion about the following statement: "A business intelligence track can't succeed if...". Below, you'll find the results of this poll. Respondents indicated that the chance of a BI track failing are the biggest when there are too many KPIs and the top management isn't actively involved with BI. These two options were far ahead of the other three, which were: lack of a data warehouse, wrong tool choice, or the project is in the hands of the ICT department.
Strategy maps are an excellent way to visualize and communicate the company strategy and its management. In the public sector we usually talk about policy instead of strategy. Passionned Group believes that a strategy map isn't only useful in the context of performance management, but also as an instrument for scenario planning, organizational development, and making investment decisions. A strategy map can consist of several different parts. Firstly there is the organization's mission, which communicates (as concretely as possible) what the organization wants to be, where and for whom. It's essentially a short text describing the essence of the organization. Secondly, there are the blocks, which display the most critical processes of the organization. Thirdly, there are the arrows. These arrows display the dependencies between the blocks. This is displayed in the image below.
Advice, research, and project management are serious matters that require a high degree of responsibility, involvement, and objectivity. These are our specialties. By working closely with you and your employees, and with crystal-clear communication, we deliver keen, executable advice. This is why dozens of clients have already used our services. Here are 10 reasons why you should consider contacting us.
The worldwide business intelligence and analytics software market revenue will reach 22.8 billion US Dollars by 2020, according to Statista. In 2008, the revenue for this market was only around 7 billion USD. Organizations use Business Intelligence software to perform thorough analyses to steer the course of their business operations. The demand for this software hasn't suffered from any economic crises, according to market research company Forrester. Organizations need the analyses provided by these programs, especially during economic downturns. Medium-to-small companies will purchase more BI Software. Currently, 30% of the revenue comes from these companies. Forrester expects that number to grow to 36% in the next five years.
As a leading consultant in Business Intelligence, we offer a small but high-quality range of Business Intelligence services. Our Business Intelligence guide focuses on what you want to achieve in the near future, what the business benefits are, and how to get there, in 5 steps. Where are you now? The current Business Intelligence situation will be addressed, discussed, analyzed, and compared with the best practices and newest available technologies. We will help you to quickly find out where improvements can be made.
Over the past 20 years, responsibility for Business Analytics has shifted within organizations. First BI was placed with the IT manager, later it was given to a CIO or CFO. And sometimes it was given to the CMO (Chief Marketing Officer). Now the idea is that BI & analytics will end up with the Chief Data Officer (CDO). One of the research agencies predicted two years ago that 90% of larger organizations will have a CDO in 2019. An enquiry amongst our larger customers makes it clear that this percentage is not even close to being reached.
Ethics is a discipline in philosophy primarily concerned with discerning what forms of human behaviour are acceptable and those that are not. More generally, ethics (or moral philosophy) is a sub-section of philosophy that deals with recording, defending and supporting the concept of good and bad conduct. Generally speaking, this implies that ethics deal with questions such as: How people can best live together in society?
It's said that wisdom comes with age. Does this also apply to organizations? Do they become wiser and smarter as they get older? There are examples of old-fashioned companies. They constantly reinvent the wheel, such as IBM. But think of beverage producers like the Brand (since 1340), Bols and Grolsch. They have existed, and managed to survive, for a very long period of time. These types of organizations are an exception.