Reliable sales management requires more than an overview from your CRM. You need to know how strong the pipeline really is, how much revenue is likely to be generated, and what remains on the bottom line.
Bringing together data from CRM, ERP, orders, and finance creates a single view of sales expectations and actual performance. This enables sales management to act on what is really happening, rather than relying on isolated figures and optimistic assumptions.
There is usually no shortage of sales data. The challenge is that this information is spread across CRM, ERP, order administration, finance, and separate files. As a result, there is no consistent view of the pipeline, forecast, revenue, and margin.
In practice, we mainly see the following problems:
Opportunities are created too late, remain in the same stage for too long, or are only recorded when the deal is nearly closed. Amounts and expected closing dates are not always updated. As a result, the pipeline does not provide an accurate picture of what is really coming, making the forecast less reliable as well.
Sales expectations look promising but do not always align with orders, invoices, discounts, returns, and margins. Without that connection, it remains unclear how much of the forecast is actually realized.
Targets are often based on the previous year plus a growth percentage. Without considering the pipeline, historical conversion rates, customer development, and market potential, they are difficult to explain and even harder to manage against effectively.
There are often plenty of dashboards and exports, but less insight into where adjustments are needed. Which accounts are declining? Which sales reps have insufficient coverage? Where is revenue growing while margin is falling?
Terms such as pipeline, forecast, revenue, margin, and closed-won deal are not always used consistently. This leads to discussions about the figures when the conversation should really be about the business.
A forecast is only as reliable as the underlying records. In practice, opportunities are not always created on time, remain in the same stage for too long, or have amounts and expected closing dates that are not kept up to date.
Analyzing data entry patterns and pipeline history reveals where the process is breaking down. This includes opportunities that remain unchanged for a long time, are not recorded until late in the process, move through the funnel unusually quickly, or consistently turn out differently than forecast.
This provides insight not only into the pipeline, but also into its quality.
You cannot fix poor record-keeping with a dashboard. But you can identify where things are going wrong, make targeted improvements, and track whether performance improves.
This separates sales optimism from financial reality.
A strong pipeline does not necessarily translate into actual results. Between an opportunity and its ultimate contribution to business performance are quotes, orders, deliveries, invoices, discounts, returns, costs, and margins.
Connecting CRM data with ERP, order, and financial data reveals what actually remains of sales expectations. This allows you to track differences between the forecast, order intake, revenue, and margin, and see where results are lost along the way.
This helps sales management look beyond pipeline value and revenue alone. Which customers are also becoming more profitable? Where are targets being met at the expense of margin? And which sales successes ultimately prove less attractive financially?
How strong is the pipeline, and what does it mean for the period ahead?
Gain insight into the size, composition, and quality of the pipeline. See which opportunities are likely to contribute to results and where the forecast is based mainly on optimism.
Explore how different assumptions about conversion, order intake, revenue, or margin affect expected results. Useful for forecasting, planning, and target setting.
Where are targets being met, and where is conversion falling behind?
Track progress against targets by region, team, sales rep, account, or product. Identify where results are falling short and where additional attention is needed.
Analyze how opportunities move through the funnel, where they slow down, and what proportion are actually won. This shows which stages, teams, or types of deals perform well.
Which customers, products, and deals truly contribute?
Look beyond revenue alone. Combine actual sales with discounts, costs, returns, and margin to see which customers, products, and deals truly contribute.
Identify growing customers, declining accounts, and unprofitable business. This allows you to focus more effectively on retention, reactivation, cross-selling, and upselling.
Sales information is rarely stored in one place. Pipeline and activity data reside in the CRM, orders and deliveries in ERP and order systems, targets sometimes in spreadsheets, and revenue, costs, and margin in financial systems.
We combine data from systems including Salesforce, Dynamics 365, HubSpot, Exact, SAP, AFAS, Business Central, and custom CRM systems. Order platforms, e-commerce environments, and other commercial data sources can also be included.
This creates one coherent view of:
The value lies not in yet another standalone integration, but in properly aligning definitions and processes. When CRM, ERP, and financial systems each define revenue, customer, or won deal differently, even a technically correct report remains open to debate.
Reliable sales management requires both clear commercial decisions and processes, definitions, and systems that support them. Sales Management and Sales Operations approach this from different perspectives, but need the same information.
Sales Management wants to know what is coming, where results are falling short and where adjustments are needed. This includes:
Sales Operations ensures that commercial processes and information remain reliable. This includes:
This creates a single shared view for Sales, Operations, Finance and executive management. Instead of each working from its own export or definition, everyone uses the same figures and assumptions.
Effective sales management does not start with a dashboard, but with the questions that Sales Management and Sales Operations want to answer so they can manage more effectively. We then bring together processes, definitions and data sources and build a solution that fits day-to-day operations.
We start with the most important commercial questions. How reliable is the pipeline? What revenue and margin do we expect? Where are results falling short of targets? Which accounts are growing, declining or generating less than expected?
We also agree on definitions for pipeline, forecast, revenue, margin, targets and won deals, among other things. This prevents each team from working with its own version of the truth.
For example, we connect Salesforce, Dynamics 365, HubSpot, and custom CRM systems to ERP, order management, and financial systems such as Exact, SAP, AFAS, and Business Central.
We account for differences in how customers, products, and opportunities are recorded, as well as sales stages, currencies, order statuses, invoicing, and margin calculations. Spreadsheets, target files, and other commercial data sources can also be included.
On that basis, we develop dashboards, analyses, and operational applications for areas including:
Where needed, we add target input, scenarios, alerts, and detailed analyses, so the solution not only looks back but also helps you make adjustments.
Depending on the existing environment, we work with Qlik, Power BI, Microsoft Fabric, TimeXtender or a combination of these.
If you already have an analytics environment, we build on it when that makes sense. We can improve existing models and dashboards, add new sources, harmonize definitions, or support a migration. If you have doubts about the current approach, a Second Opinion Data & Analytics can be a good first step.
After delivery, we can also support and manage the environment, so new teams, data sources, targets, and analyses can be added in a controlled way.
For Channel Factory, we built a sales app that brings together pipeline, targets, actual and projected gross profit, margin, and hit rate. Sales management can analyze performance by region, sales territory, sales representative, account, and product. The app also highlights declining accounts, winners and losers, and revenue and margin scenarios.
For Topgeschenken, we brought together sales, orders, customer segments, partners, products, discounts, and margin. The solution supports B2B/B2C analysis, forecast orders, customer rankings, and margin trends by period and product group, among other capabilities.
For an international fashion company, we developed a sales solution covering order intake versus target, pre-orders, re-orders, customer and product performance, and returns analysis. Targets can be entered and tracked by customer, brand, and season.
Sales data rarely resides in a single system. We combine data from CRM, ERP, order management, finance, and additional commercial sources into one coherent view.
Many organizations already have a CRM, ERP, dashboards, and reports. The question is usually not whether everything needs to be replaced, but where the current information falls short and which improvement will deliver the most value.
For example, we can:
Even if the data is not yet perfect, an initial analysis can be valuable. It reveals which shortcomings affect the reliability of the pipeline, forecast, and results.
A good sales solution does not have to start out large. Above all, it should answer the questions for which you currently lack the insight needed to manage effectively.
That depends on the questions you want to use to guide decisions. We often combine CRM data with data from ERP, orders, finance, targets, and supplementary files.
The more data is available from across the sales process, the better we can connect pipeline, forecast, order intake, revenue, margin, and results.
Yes. We work with systems including Salesforce, Microsoft Dynamics 365, HubSpot, Pipedrive, SuperOffice, SAP, Business Central, Exact, AFAS, and NetSuite. Custom systems, databases, APIs, and files can also be used as data sources.
We first look at what is already in place and what data is needed. Replacing existing systems is not the default approach.
No. Completely clean data is rarely the starting point. However, poor or incomplete data entry does affect the reliability of the pipeline, forecast, and analyses.
We can identify where opportunities are missing, have not been updated for a long time, move through the funnel unusually quickly, or are only entered at a late stage. This shows which improvements will have the greatest impact and whether data entry actually improves afterward.
Yes. Combining CRM data with quotes, orders, deliveries, invoices, and financial data shows how much of the expected sales ultimately results in revenue and margin.
Differences between the forecast, order intake, and actual results can also be tracked. This shows where results fall short along the way or turn out better than expected.
Yes. Targets and budgets can be linked to regions, teams, sales representatives, accounts, products, brands, or periods, for example.
The data can come from existing systems or files. Where necessary, we can also add data entry functionality. Bonus or commission calculations can be included when the rules and source data are sufficiently clear.
Yes. We can assess and improve existing dashboards, data models, and definitions. This may involve missing data sources, inconsistent KPI definitions, slow reports, unclear analyses, or dashboards that mainly look backward and do not provide enough support for making adjustments.
If you have doubts about the current approach, a Second Opinion Data & Analytics can be a good first step.
That depends on the existing environment, information needs, and preferred solution. We work with technologies including Qlik, Power BI, Microsoft Fabric, and TimeXtender.
We prefer to build on what is already in place, as long as that makes sense from a technical and functional perspective.
No. A clearly defined question or an initial use case can be a sensible starting point. Examples include pipeline quality, forecast versus actual results, managing against targets, or insights into revenue and margin.
This allows us to validate the information needs, available data, and chosen approach before expanding the solution further.
That depends on the number of data sources, the quality of the data, the complexity of the definitions, and the desired level of detail.
A well-defined dashboard can be delivered relatively quickly. A broader solution that connects CRM, ERP, orders, and finance usually requires more analysis, modeling, and coordination.
Would you like a better understanding of what is in the pipeline, where performance is falling short of targets, and which customers, products, and deals truly contribute to revenue and margin? Barry and Eric would be happy to discuss your current environment, information needs, and a logical next step. In half an hour, you’ll know whether we’re a good fit. Email us, call us, or schedule a call right away.
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Available on weekdays between 8:00 AM and 6:00 PM (Amsterdam time)
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