You're designing a process for your team. How can you make sure it's data-driven?

In my experience it’s equally important to know who your customer is. What have they hired you to do? What are the business drivers? Are there other reasonable alternatives? Sometimes your customer knows already knows the answer to these questions, but if they don’t, you need to press them for clearly articulated business or regulatory drivers. It’s a costly mistake to engineer a solution to something different than what your customer has requested.

A defini??o de objetivos através da metodologia SMART permitirá que os dados sejam um fator norteador deste processo, uma vez que precisará ser mensurável. A partir deste ponto, a defini??o de KPIs que monitorem o desempenho deste objetivo garantirá o embasamento técnico em dados para indicar a performance e nortear as decis?es da equipe e lideran?a.

I would start by defining the team's objectives and identifying the key outputs the process intends to achieve. With this information I would then formulate a strategy to monitor and measure these results. For example customer satisfaction as a result can be achieved by measuring customers wait time data.

Before designing a process, you must have a clear idea on what you want to achieve. However, it is equally important to take the time to collect and analyze the data in order and re-examine your objectives once you have an increased understanding of the collected data. You need to understand how all parties affected by your new process. it's also important to gather information to understand how to measure success of the new designed process.

Identifique claramente os objetivos que deseja alcan?ar com o processo. Por exemplo, pode ser aumentar a taxa de engajamento dos funcionários com conteúdo do LinkedIn relacionado à indústria.

Thorough due diligence is crucial before making any process changes. This entails collecting all pertinent data about the process to handle potential risks effectively. Start by reviewing the existing documented framework and finding the Key Performance Indicators (KPIs) associated with it. Then talk to the key people to ensure everyone understands and backs the process completely.

1)Data required for designing a process play crucial role. Additionally, not only data but all our basis and assumptions in case of non-availability of data is very vital in selection. 2)We must focus to implement system driven process and avoid human error and person based approach for which Database shall be created or make sure it is available through authenticated source. (Not to blindly trust on google search). 3)To ensure less error in considering basis and assumptions, strong session to team involve in selecting data and analysing for process Desing must go through training on how each data or parameter plays crucial role in process outcome.

After determining your goals, we must decide what data, parameters, equipment and how the evaluation will be carried out to design your process. In addition, above all, we must decide where and under what conditions the work will be done.

Identify the key metrics and data points that will help you measure the success of the process. This may include historical performance data, customer feedback, or industry benchmarks.

Even though you can know some things about data and its relevance, data collection isn’t the next thing to do, the next thing to is to design a process model that shows how the tasks will be conducted to achieve the process‘ targets. Define where the process is easy to streamline by defining work streams for stakeholders, their end to end line out, the feedbacks (which ones will you allow in the beginning) and so forth. Only after this step you can have a first clear picture where data will be produced so you can conduct the used forms, data objects, systems and - very important - align the data model with the process model to steer and control the process correctly with a first framework, that shouldn’t need much change later.

Após coletar os dados relevantes, é importante analisá-los para extrair insights e entender padr?es. Isso pode envolver técnicas estatísticas, visualiza??es de dados e outras ferramentas de análise.

In my opinion, once you have gathered enough data, it's important to set up an analysis dashboard. This will enable you to carry out a comprehensive risk analysis, which can help you to understand the anticipated effects and benefits of the decision.

Directly analysing data on papers I would recommend to check; 1) Visualise results of data on smaller scale. 2) Apply practical approach / experience based approach to data and its results on process outcome through simulations / literature survey etc. 3) Ofcourse get data in different forms to see trends and behaviour followed by critical thinking.

Use analytical tools and techniques to analyze the data collected. Look for patterns, trends, and insights that can inform the design of the process.

Because you have an already stable process frame work on place, you can now define metrics in line with data points along the process, knowing how those points (mostly tasks or tasks areas) are supposed to serve to achieve the set targets. Because you invested in an alignment framework for your process- and data model, you can survey listed an new quality and quantity dimensions and switch faster to informed and thereby productive discussions about analysis results. This way you will have a good base to define your continuous improvement process with potentials for its backlog. This will be also steered easier by communication with earlier delivering and later consuming processes to give valid feedback including items for the CIP.

Com base nos insights obtidos da análise de dados, você pode come?ar a projetar o processo. Isso pode envolver identificar áreas de melhoria, desenvolver novas estratégias ou ajustar procedimentos existentes.

1. Define the questions that you want to answer with data. 2. Find the sources of information to answer the data 3. Collect de data. 4. Clean & verify the data is correct. 5 Structure with dashboards and smart boxes (data warehouse) to analize information

Once a comprehensive understanding of the project is established, it's time to create the process map. This stage should revisit the list of objectives outlined at the start. At this point, it's beneficial to refine these objectives: add new ones as necessary and break down broad objectives into smaller, more manageable tasks. This ensures that the actions required at each stage of the process are crystal clear to all parties involved.

Based on the analysis, design a data-driven process that incorporates the insights gained. Define the steps, roles, responsibilities, and decision points clearly.

Have a look at data selection (Step 2) starting with process design now is to late, because your data selection would remain a good guess instead of an informed selection. So I have given my input there.

Once we’ve know impact of which data/ parameter has critical role in process outcome, select those and track them Analyzer them to check any deviations oout of trend etc..

Uma vez que o processo tenha sido projetado, é hora de implementá-lo na prática. Durante a implementa??o, é importante monitorar continuamente o processo para garantir que ele esteja funcionando conforme o planejado e fazer ajustes conforme necessário.

In addition to all the already mentioned elements of implementation and controlling I would preferably base this on a stable, but adaptable reporting. First of all for the team, not for top management. First framework of the reporting could be a good playground to explain the new process to the people who work with it. This is what we aim for, this is how your impact is measured. Top management should be informed about the same way, but in a condensed form. Implementation and control is dependent on Top management supporting the team by 85%. Top management is not supposed to claim the process and tell the experts how to do the job. The CIP roadmap, risks and core deliveries according to the target set up are minimum elements of the report.

Following the PDCA (Plan-Do-Check-Act) cycle, it is incredibly important to get data and analyze it repeatedly after we start the phase of implementation. If we get into the habit of gathering and reviewing data right after we start, we'll quickly begin to see how crucial it is to the initial design, and we'll get a much clearer notion of just where to make the adjustments that can turn a back-of-the-envelope collection of rough ideas into a functioning improvement.

To ensure successful process implementation, it's crucial to define measurable goals and utilize data as the primary means of tracking progress. Integrating cross-verification checks throughout the process helps guarantee adherence to user inputs. Identifying discrepancies between expected and actual results allows for timely communication with responsible parties, ultimately facilitating the acquisition of necessary data.

While designing or drafting the SOP is an art in itself, the more difficult and challenging task is to make the team adhere to it religiously. As the first rule of the rule book says, follow the rules. Everyone within the ecosystem must be well trained with the how, why and when of the SOP. There must not be any relaxation or flexibility for a specific project as it will lead to unnecessary choking/ consumption of the team's bandwidth. Furthermore, if there's a repeatitive demand of a flexibility for a situation, that should be given a brainstorming session to re-analyse the process and do the required amendment. A well maintained SOP brings in loads of inter-team trust and reliability because of the universally stable approach.

Por fim, o processo de melhoria contínua é essencial para garantir que o processo permane?a orientado por dados ao longo do tempo. Isso envolve revisar regularmente os dados, identificar áreas de oportunidade para melhorias adicionais e iterar no processo conforme necessário.

You've got to understand the process capabilities then let the data drive the project. Without knowing the process capabilitues, you're taking a shot in the dark.