Moving to Microsoft Dynamics 365 in 2021
As organizations will undoubtedly be looking for ways to increase efficiencies, lower costs, and improve productivity for 2021, one of those initiatives to consider should be Microsoft Dynamics 365. Over the years, many businesses have purchased CRM and/or ERP systems to manage their business operations, while others are still relying on spreadsheets and word documents. With Dynamics 365, businesses can manage, drive, simplify, optimize and streamline their business processes much more efficiently, while enabling a true vision for digital transformation to come alive. Dynamics 365 also allows a company to break down silos, connect disparate systems, integrate stand-alone apps and consolidate them as one unified, intelligent suite. Ask yourself the following questions: Did your business face productivity challenges either before or during the lockdown? Are you spending too much time and too many resources collecting data from all of your various systems to try to get a clear picture of your business? Are you using multiple applications to manage your different business processes? Are some in the cloud while others remain on site? Do you spend a lot of time collecting and organizing customer and sales data? Does your company have spreadsheets and other documents that are used to track and manage tasks and activities? If you answered “yes” to any of these questions you could be an ideal candidate for Dynamics 365. People who use documents, spreadsheets and multiple versions of business productivity software to manage their business have a big challenge on their hands. For example, let’s consider a company that uses a CRM and a ERP system to oversee its business. With CRM, you could create a customized a view of all your related information such as marketing, sales, customers and service offerings. And with your ERP you could monitor HR, commerce, projects, inventory, accounting, finance, and supply chain. Okay, these traditional methods sound good so far. Ask yourself the following questions: First, these are isolated systems that operate with disconnected business code and logic. Second, these platforms are complex, slow, cumbersome, and very expensive to deploy and integrate — especially if they are not cloud based. Third, they are also difficult and costly to operate, maintain and update. The good news is that Dynamics 365 accounts for all these challenges as it eliminates complexities and unifies disparate systems. It eliminates the need to operate and maintain all of these local systems individually and it removes the challenge of trying to get a holistic view of all your business data. Instead of living in a world that is spread out throughout your business in various documents, calendars, different contact lists, schedules, emails, forecasts, inventory, and so much more, why not take advantage of enterprise-grade-level, cloud technology? If price is your concern, these world-class technologies are quite affordable nowadays. Dynamics 365 can bring together and unify your CRM and ERP systems and their respective capabilities. This will enable you to streamline your business, break down silos, connect intelligent services, join business apps, establish a digital transformation roadmap and reduce costs for deployment, upgrades and maintenance. You’ll achieve a 360-degree view of your operations as all of your business data flows seamlessly within one platform and across your enterprise – it uses a common database so that all entities and data are tightly connected. Next, let’s consider the cloud. With Dynamics 365, you can take advantage of one central cloud-based, intelligent business app that is all-in-one. The SaaS model (Software as a Service), is ideal for small and medium-sized businesses to take advantage of an enterprise-grade technology that has traditionally been cost prohibitive to them and enjoyed exclusively by larger-sized organizations. With SAAS, strategies, people, processes, systems, apps and data are tied together. And you pay for only what you use with the “pay-as-you-go” model. In summary, this becomes your business management solution to run your entire ecosystem and with the cloud, you could provide approved users access at any time from any location. Another advantage of Dynamics 365 is that it provides extensibility with Microsoft Power Platform to extend its capabilities and functionality even further; specifically: Microsoft Power Apps is a low code app that helps you modernize your processes. You can integrate third-party apps right inside Dynamics 365. Microsoft Power Automate provides digitization and robotic process automation of workflow to eliminate repetitive and manual tasks. Microsoft Power BI enables you to receive real-time analytics, easy-to-understand visualizations, infographics, dashboards and reports that can be shared with all business levels to make informed decisions. Microsoft Power Virtual Agents allows you to utilize plug and play virtual chat bots so that you can address internal and external customer needs. One of the issues that companies often ask about is security. What’s great about Dynamics 365 is that it’s all unified so that an administrator only needs a single sign on to access. It has a full security model that restricts non access once inside. For example, someone from shipping viewing delivery information would not have access to HR records. Dynamics 365 also has multi-level approvals that can be defined within the system to enable approval at every appropriate stage – this is also supported by email notification. Another advantage of Dynamics 365 is that you can start small and grow as desired. For instance, you could start by utilizing the technology to only manage your field service operations, your projects, or your marketing effort. With the new year upon us, this could be the right time to consider this powerful business management solution. With the flexibility to start small and scale, and with the advantages as outlined such as lower costs, unification, and ease of use, why not? Also Introducing Microsoft Dynamics 365 Project Operations for project or service-oriented businesses How to create Quick Email Campaigns with Microsoft Dynamics CRM? Kirti Sethiya Kirti Sethiya is a Microsoft-certified business applications consultant at Advaiya. Kirti has been involved in a wide array of tailored digital transformation projects over the years. Contact us by filling the form below for Microsoft Dynamics 365
Transform unstructured data into usable insights for Power BI
Power BI (Business Intelligence) is a Microsoft BI tool which is widely used at every level in the organization to make confident decisions, perform ETL logic and visualize data using up-to-the-minute analytics. Here, we are targeting the issue of mixed data values coming from APIs in a single column. Targeted audience– Developer Use Case:, In figure: A column containing the Records and List of records may create issues while further expanding them due to different data types. We can expand the list and record separately, but it will duplicate columns if the data contains a similar structure to this. JSON Sample for reference: { “@timestamp”: “30-11-2020 01:31:30 PM”, “postitems”: [ { “itemCode”: “abc1″ }, { “itemCode”: “abc2″ }, { “itemCode”: “abc3″, “hours”: [{ “day”: “Monday-Thursday”, “time”: “2:00PM – 1:00AM” }, { “day”: “Friday-Sunday”, “time”: “10:00AM – 2:00AM” }] }, { “itemCode”: “abc4″ } ] } This issue can be resolved by the Power Query editor formula as given below. let #”source” = Json.Document(File.Contents(“d:pathfilename.json”)), #”tabled “= Table.FromRecords({source}), #”expandListField” = Table.ExpandListColumn(tabled, ” postitems “), #”expandRecField” = Table.ExpandRecordColumn(expandListField, ” postitems “, {” itemCode “, “hours”}, {” itemCode “, “hours”}), #”expandList2″ = Table.ExpandListColumn(expandRecField, “hours”), #”fieldForRec” = Table.AddColumn(expandList2,”Rec”, each if Value.Is([hours], type record) then [hours] else null, type record), #”fieldForList” = Table.AddColumn(fieldForRec, “List”, each if Value.Is([hours], type list) then [hours] else null, type list), #”expandList3″ = Table.ExpandListColumn(expandRecField2, “List”) #”Replaced Value” = Table.ReplaceValue(#”expandList3″, each [List], each if [List]=null then [Rec] else [List], Replacer.ReplaceValue, {“List”}), #”expandRecField2″ = Table.ExpandRecordColumn(#”Replaced Value”, “Rec”, {“day”, “time”}, {“day”, “time”}), in expandRecField2 The formula here creates a set of lists and records into separate columns. #”fieldForRec” = Table.AddColumn(expandList2,”Rec”, each if Value.Is([hours], type record) then [hours] else null, type record), #”fieldForList” = Table.AddColumn(fieldForRec, “List”, each if Value.Is([hours], type list) then [hours] else null, type list), Then expand the column with a list. #”expandList3″ = Table.ExpandListColumn(expandRecField2, “List”) It makes both the column with the same data type i.e., Records Now we merge both the columns by replacing the null values in the list column. #”Replaced Value” = Table.ReplaceValue(#”expandList3″, each [List], each if [List]=null then [Rec] else [List], Replacer.ReplaceValue, {“List”}), Now we only have a record that contains “Employee Name” in the column, and we can expand the data to be used. In figure: Column with an only record data type that can be further expanded and get Employee Name Conclusion: Here we transformed data for multiple types of values into single columns with PowerBI. Next Steps- Join us in a one-day workshop Dashboard in a Day (DIAD) and Paginated Reports in a Day (PRIAD) to understand and explore Power BI as a solution for business data collaboration.With the new year upon us, this could be the right time to consider this powerful business management solution. With the flexibility to start small and scale, and with the advantages as outlined such as lower costs, unification, and ease of use, why not? Also Know Why Microsoft Power BI is the leader in business analytics? Gain advantage of a phased approach for your next BI project. Learn How to embed a Power BI report into an application for your customers? Ankit Panchal Ankit Panchal is currently working as Senior Associate in Advaiya and has worked on Microsoft technologies for past 3.5 years and has been a SharePoint expert. Currently is working on Microsoft Power Platforms. Contact us by filling the form below for Power BI implementation and integration.
Top 5 Business Intelligence and Data Analysis Trends
The ever changing business needs, fast-moving technologies, innovative techniques – self-service business intelligence (BI), mobility and predictive analytics, have taken the world of business analytics by storm. Organizations, nowadays, have unprecedented quantities of data, and they expect much from their analytics solution. They want their data accessible quickly and easily, anytime and anywhere. Most of the companies are striving towards easy-to-use, fast, agile, and trusted modern BI and analytics platforms to create business value and deeper insights out of the data coming from diverse data sources. Let’s have a look at some of the evolving trends in BI and analytics: 1. Self-service BI and Analytics: Today, business need the useful information fast enough and most importantly at their own. They do not want to be dependent on IT for any request. Self-service BI is an approach within the BI environment which enables to access the right information instantly and easily to the right person at the right time. Many companies are providing self-service BI solutions, which relieve IT from tedious and manual processes to make the data available in a governed manner; and allows business to get the information they want from anywhere at anytime. 2. Cloud based BI and Analytics: The critical corporate data and apps are rapidly moving online, so the BI and analytics cannot be far behind. The cloud based analytics is becoming more mainstream as it offers numerous benefits including lower expenses, greater flexibility and elasticity, quicker operations and on-demand availability. Initially, the cloud-based solutions were designed for SMBs that did not have sufficient IT resources to handle the infrastructure, but today, many large enterprises are also investing in the cloud as a way to deliver the access to corporate resources quickly and easily. 3. Mobile BI: Mobile BI has quickly emerged as the easiest way to deliver real-time useful insights to business users almost anywhere using any device including smartphone, tablet, iPad or iPhone. It helps users to make data-driven decisions on-the-fly, which eventually increases company’s productivity and bottom-line. Most BI vendors are also working tirelessly in this field to strengthen their services and provide a better end-to-end solution to their customers.4. Analytics of Things: The Analytics of Things (AoT) is a new buzzword in the analytics industry after the huge popularity of Internet of Things (IoT). The AoT is a term used to describe the analysis of huge amount of data generated by IoT devices to make that data valuable. AoT is also essential as it makes connected devices smart and enables them to take intelligent decisions. In simple words, AoT is Analytics of IoT devices; which is required to make IoT devices more capable. Using Analytics of Things, organizations can understand the data that is being generated and can take necessary steps to improve their business. 5. Predictive Analytics: As the BI and analytics landscape is evolving constantly, businesses of tomorrow will be more and more focused on the future forecasts. Predictive analytics is the process to leverage the existing information and gain valuable perceptions to predict the future possibilities and stay ahead of the competition. Organizations are using predictive analytics in many different ways to uncover the future possibilities. Author Recommended 10 Keys to a Successful Business Intelligence Strategy Why Microsoft Power BI is the leader in Business Analytics? Organizations these days are producing a huge amount of data and it is important for them to invest in evolving technologies and skilled resources to be successful. They need to understand the significance and potential of BI and Analytics in achieving success. It is only with time that these trends will advance and prove its worth. Need Help in Business Analytics? Contact Us
Five techniques for successful BI adoption
The primary reason business intelligence strategies fail is the lack of alignment between organizational processes and technological factors. These core areas need to be aligned appropriately. They must receive central business focus, in a way that everyone can identify with these and thus can take an active part in fully utilizing the potential of business intelligence solutions. Business intelligence adoption rates can only increase if every employee making use of business intelligence solutions has a strong sense of involvement and ownership in all strategic areas. Strategies for successful business intelligence adoption in an organization: Defining and monitoring data quality standards during the initial implementation phase: Data quality is the primary factor that can make or break any business intelligence initiative. This is because the users will immediately judge the capabilities of any BI system by the result it generates when they use it for the first time. The results and insights generated from any BI system largely depend on the data quality, and if the initial results are promising and accurate, then only the users will show interest in using the system again, increasing the BI adoption in the organization. Real-time integration between BI system and other third-party ERP and CRM systems The real potential for generating actionable insights from any BI system is highly dependent on the successful integration of the BI system with legacy ERP and CRM databases. The integration is also essential because it should include all the departments’ data in the BI implementation phase to provide visibility for their deliverables and respective business drivers. In larger organizations, it is imperative to have the Project Management Office (PMO) manage the BI implementation project and to have a senior executive taking ownership of the implementation project. If an organization doesn’t have the PMO, the best approach is to define a project leader who will oversee and manage all aspects, from the formulation of the BI roadmap strategy to implementation on a daily basis. Business results–driven approach: An organization must always keep the focus on the strategic business drivers for developing a good business intelligence system. This approach can provide more significant insights that can turn into revenue. A constant emphasis on the business results will keep the BI project’s focus and intensity on a higher level until the project is completed. Thus, the result–driven approach will lead to successful business intelligence implementation and adoption in an organization. Identifying Key Performance Indicators (KPIs): Any organization would want to see its business intelligence applications showing an analysis of its KPIs that represent its business objectives in both the short and long run. An analysis of the KPIs will help the organization to spot the areas for improvement. A successful business intelligence strategy will always consider the company’s overall strategy and map it to align with the company KPIs. Thus, for the successful adoption of business intelligence solutions and applications, it is critical to identify and analyze KPIs from the users’ data. Selecting a flexible and agile BI application: Any user of a BI system would want an application that is flexible and agile enough to accommodate and allow changes according to the changes in indicators and requirements. A BI application that has some of the essentials features like content creation, data and its infrastructure management, and embedded analytics will undoubtedly set the foundation for the organization to implement business intelligence and thereby increasing the BI adoption rates in the organization. Conclusion: According to Zion Research, the global BI market, which accounted for 16.3 B in 2015, is expected to reach 26.5B in 2021, indicating around 9% year-on-year growth. Today, business intelligence has become the buzz word, where every organization is investing in BI systems, but very few of them can reap its full benefits. The five strategies discussed above will surely increase the BI adoption rates in the organizations and the benefits resulting from successful BI implementation.
Capabilities of dataflows against datasets
With the release of dataflows in Power BI, you being an intended user, may have a few queries in mind: what exactly are dataflows, how are they different from datasets, how should I take advantage of them, and more. Through this blog, I will attempt to address these queries you have and make an idea of dataflows accessible to you. What are dataflows? With the advancement of Power BI, you can create a collection of data called dataflow. It is an online data storage and collection tool. With its help, you can add and edit entities and brings semantic understanding and consistency to data across many sources, by mapping it to standard CDM entities. Use of dataflows in an organization: Main reasons to introduce dataflows: 1. It helps organizations to unify data from disparate sources and prepare it for modeling. With the help of dataflows, organizations can directly link their data from different data sources to Power BI with just a few steps. Organizations can map their data to the Common Data Model or create their custom entities. Organizations can then use these entities as building blocks to create reports, dashboards, and apps and distribute them to users across their organization. Further, organizations use Dataflows to transform and add value to big data by defining data source connections. With the help of a large variety of data connectors provided by Power BI and PowerApps, organizations can directly map their data from the data source. Once you load the data in dataflow, the creation of reports and dashboards in the Power BI desktop becomes easy. 2. Self-service data prep in Power BI while dealing with large datasets: As data volume grows, so does the need to have insights into it. With the introduction to self-service data prep for large data in Power BI, it is now easy to have insights into any collection of data instantly. Dataflows help organizations combine data from various data sources and perform the task. Organizations can now have their Data from multiple sources stored in Azure Data Lake Storage Gen2. Organizations can manage dataflows in workspaces by using the Power BI service. They can also map data to standard entities in the Common Data Model, which gives them the flexibility to modify data. It further helps its users work upon existing entities to customize them. 3. Different data source with a different schedule of refresh: Dataflows play a vital role, especially when our data contain two tables with unique schedule options. Dataflows help build mechanisms that can schedule refresh according to the organization plan. Dataflows can run, extract, and load data entities in workspaces. They allow the transformation of the data process on a different schedule for every query or table. 4. An online data collection and storage tool Collection: Dataflows use Power Query to connect to the data at the source and transform that data when needed. You can access the data through either a cloud service (such as Dynamics 365) or a PC/Network via an on-premise gateway. Storage: Dataflows stores data in a table in the cloud so you can use it directly inside Power BI, to be more specific from Power BI Desktop. 5. Transformation of large data volume While handling past or obsolete data, let us say a two-year-old sales record, you could come across files containing many rows or columns. Such data normally take hours to refresh. Dataflow proves to be the quicker option in such cases. You can seamlessly switch from the database to the dataflow option. You may further make use of the incremental refresh settings option in dataflow, which ensures that only updated data get refreshed. Dataflow and Azure Data lake integration: With the use of dataflows, users and organizations can connect data from disparate sources, and prepare it for modeling. For using Azure Data Lake storage for dataflows, you need to have an Azure subscription and have the Data Lake Storage Gen2 Feature enabled. After setting the Azure account, you must go to the dataflow settings tab of the Power BI admin portal wherein you must select Connect Your Azure Data Lake Storage Gen2 button. Once you do that, the system will ask you for the user credentials to initiate the Azure Data Lake. Finally, click the connect button to begin. After the completion of this step, azure data lake storage is ready to use in Power BI. Connect to different data sources for Power BI dataflows With Power BI dataflows, we can connect to multiple data sources to create dataflows or add new entities to an existing dataflow. Step1: To create the dataflow, click on the +Create menu button and select the dataflow option. You will now see several options related to entity creation. If your dataflow already exists, you can select the Add Entity or select Get Data in the dataflow authoring tool. Step2: Now, select the data sources from the dialog box and search for the data source categories from the given options. Broadly, there are five categories from which you could choose your data: file, database, power platform, azure, and online platform. Step 3: After successful sign in, click the next button to continue. It will open a Power Query Online where you can perform the basic editing of your data. Finally, load the model and save the dataflow. Summary In this blog, I have explained multiple features of dataflow to show you how it has the upper hand over datasets. However, a lot depends on the user’s choice, especially the choice of the environment which the user prefers. There are situations in which dataflow enables you, the user, to have better control over and insight into your business data. By using the standard data model, schema, as defined by the Common Data Model, dataflows import the user’s business data and help in reshaping and combining data across different data sources and have them ready for modeling and creation of dashboards and reports in a short period, which earlier used to take
Business analytics to supercharge sales
Often, Sales is considered a guessing game. Businesses come up with implementation strategies, never knowing whether their efforts are worthwhile. When the revenues grow, there comes an agreement that their methods are successful and continue to move on. If there isn’t much change, we see an adjustment in the approach until the teams close more deals. However, technology has enabled sales teams to see precisely how their strategies are performing. They can monitor customer activities and link them to specific sales efforts by using analytics. With so many companies now using analytics to boost marketing and sales, companies that fail to adopt this technology will eventually find they’re losing to competition. Here are the ways businesses can supercharge their sales by using business analytics. Sales team management: Identifying patterns and drive action-oriented training to the team Your CRM’s potential insights are only useful if your sales team provides the system with accurate information. Once you have confidence in your data, you can analyze the patterns in the behavior of the opportunities in the movement through the sales funnel, and understand the successful techniques and actions that produce desired results. The software for sales analytics, including CRM, contains a range of data that allows for such evaluation with lead scoring and opportunity scoring. The analysis would yield specific actions in the sales process, which can drive your sales coaching and training practices. The insights from the analysis of sales data will answer questions like: Which reps are struggling at identifying all the buying influences? How to assign clear and balanced territories to reps and adjust as needed? Answers to these questions can help you identify and suggest specific actions with successful outcomes or identify the need for guidance to the team. To give you an idea, sales analytics will point out whether an individual rep mainly has contacts in the technical roles, suggesting that he must work on the identification of other buying influences to engage prospects in the sales process earlier. Simply put, it sums up to the reliability of your data, and identification of trends that lead to desired results. Sales effort effectiveness: Exercise data into everyday sales activities Every company operates its sales team differently. A one-off product company does not have the same requirements as a company based on a recurring revenue model. Both companies, though, depend on their sales to reach revenues and profitability targets. In addition to using insights from historical data for the improvement of your sales team performance, you can provide prescriptive guidance to sales professionals on how to improve their chances of making a sale. It can include strategic suggestions for market or account in a specific vertical where demand for a certain product is higher than others, or tactical ideas like product bundling and up-selling or cross-selling of some products that have sold well together in the past. A salesperson often makes more than a hundred calls a day. Using data analytics can be very valuable for deal scoring, determining which opportunities are worth picking up and which ones should be a part of marketing nurture campaigns. The perception that specific calls would be more productive and successful will increase confidence and lead to better interaction with the customer and closing the deal. Sales analytics can be useful for personal interactions, as well. For instance, sales professionals can use data to address pricing questions on the spot. The sales reps can gain tremendous credibility by showing average prices of recent sales for companies located in the same region, vertical or company sizes, to the current prospect. Often this is done on a mobile device during the meeting. Such types of data and analytic benchmarks allow the salesperson to understand how their customers pay attention to a specific price and how flexible and elastic they are in accommodating discounts. Closing thoughts In sales-oriented organizations, the role of data is shifting. It is evolving from management reporting to the development of a strategic tool for sales managers and sales teams. Nonetheless, this change requires overcoming the initial resistance to data quality and reliability barriers and gaining an organizational buy-in. With analytics as a motivator and incentive, the organization can ensure that sales managers and individual representatives are in control of their achievements. The organization can build a highly effective sales team that is capable of prioritizing, taking ownership and making good choices using data as a strategic tool to drive revenue and profits. We, at Advaiya, help you with the right planning, implementation and adoption of business analytics and business applications tailored for your business, enabling you to make better decisions, deliver superior customer experience, increase productivity and induce technology-led innovation.
Gain more value by prioritizing your data initiatives
For our esteemed clients, we are regularly conducting a data discovery workshop to identify information needs related to visibility, control, and information related to business intelligence. These are NOT the typical discovery sessions you may be familiar with, as our clients find this very valuable. At a high level, we conduct these workshops to understand their key objectives, what kind of decisions they are trying to make, how they measure success in different organizational units, what are the data sources and applications from which they want to create reports and insights. The outcome of this exercise is intense and comes in the shape of – A road map and architecture document Initiatives Projects for data integration, aggregation, and warehousing Creating a common taxonomy to use List of various dashboards and reports Since these workshops involve different stakeholders from business and IT and various horizontal functions, everyone has a different priority set and viewpoint on what challenges they are trying to solve (or what makes them awake at night). How to prioritize rationally and thoughtfully is part of our engagement, where we use a framework to prioritize which things to take in the first phase, and what we can plan for later phases. Firstly, we determine what dimensions are affecting prioritization – these could be different based on in what industry or domain the organization is running their business. These can be functional areas, organizational roles which require this information, geographical regions, data sources that need to be integrated, amount of structured and unstructured sources. Let’s look by an example of a healthcare organization – a hospital which is providing patient and clinical services. For those, dimensions would be – Functional Areas Finance Clinical Patients Organizational levels C Level Executives Doctors Clinicians Other dimensions Multicity operations Different hospital management and clinical management applications Datastores residing on-premise and on cloud The second attribute is the purpose of that initiative which can be classified as – Visibility – of what is happening on a regular interval Control – related to compliance or action needed if something goes beyond the baseline Information – Understanding and further analysis So, for each dimension (which could be a combination of dimensions), we put purpose and identify a final set of initiatives for prioritization. To do the prioritization, we generally check for three things and discuss with stakeholder to rate each initiative based on: Strategic Impact Hard impact – Quantifiable Soft impact – Meaningful Complexity What are the variables involved? Which functions and locations involved? Value Cumulative $ value from the decision The opportunity cost of not taking/postponing the decision There are other factors we need to consider related to data like – data availability and relevance, data definitions, data quality, data standards, integrity, uniformity. There are scenarios where if an initiative has a quantifiable hard impact on business and providing cumulative value but complex to implement, this can become a part of phase 1 deliverable. However, it might be a case that costs and time to implement in comparison to other initiatives are more impactful; then, stakeholders can decide which to take as the first phase and what initiative can be part of the backlog. The good thing with this approach is that all stakeholders are aware and informed about the decision, and they also know the roadmap of solution implementation. We know from our own experience that this approach helps a lot. Initially, our customers were skeptical about this whole exercise but appreciated and found this valuable after completion. Let me know if you are planning a data analytics or BI initiative organization-wide or in your SBU. You may find these useful: Related services & solutions Scorecards and dashboards Read more Data discovery and aggregation Read more Intelligence Read more Leveraging data Read more Work management and business productivity Read more Information strategy Read more Data warehousing and infrastructure … Read more Insights Read more Relevant blog Artificial Intelligence: A Silver Bullet for Housing? Don’t just survive, grow through the crises with Power BI The next big thing in business applications Capabilities of dataflows against datasets Business analytics to supercharge sales The Customer Approach: Data for Decisions Not Data for Itself Are you unable to make data-driven decisions? Updates How to Use Analytics to Ramp Up Your Sales Virtual event on DAMA Portland by our President & CTO on saving resources using dataflows
How manufacturing companies gain value from BI
Business intelligence (BI) has become important in anticipating customer needs and wants, designing the product and process for the same, and deliver to specifications profitably. A manufacturing company must know which product is doing well in the market, which product is in demand, forecast demand based on past needs, purchase and stock the raw materials, store the finished goods in inventory, keep track of the sales, track payables and receivables, measure profit/loss and do more. If you are looking for a solution to get quick and valuable insights into the aspects mentioned above, BI with its features like visualization, reporting, data discovery, scorecards, and dashboards can be your best investment. Here are ways in which Business Intelligence can benefit the manufacturing industry: Informed decision-making Manufacturing industries today are processing copious amounts of data from multiple sources, and hence arises the need for the right processing and utilization of data. BI is a powerful tool in the hands of businesses who would want to extract and convert data from multiple disparate sources to gain meaningful insights. Data visualization tools can be used to get insights that can be presented in a simplified manner, along with key business matrices and KPIs. Insights help the decision-makers to make more informed business decisions. Improves operational efficiency Manufacturing units can use easy-to-navigate dashboards, comprehensive reports, and scorecards to improve efficiency. With the help of business insights, industry units can improve operational efficiency, reduce waste, enhance the quality of the product, reduce labor, material and overhead costs, negotiate effectively with suppliers, and present winning quotes to the customers. Financial management BI tools can be used for sales analysis, profit and loss analysis, raw material analysis, which can help in optimizing resources and increasing ROI. BI can be used in identifying unexplored channels of revenue and minimizing internal costs leading to increase in profit margins and reduction in unnecessary expenses. BI also helps in carrying out an in-depth cost-benefit analysis, demand-supply analysis, and helps to streamline operational procedures by monitoring and managing processes. Supply chain and logistics management By evaluating performance on a regular basis, BI can help in the management of supply chain logistics and analysis of data to ensure quality and timely deliveries, monitor freight costs by identifying fluctuation in supply and demand and optimize the value of suppliers by giving feedback on their services. Thus, BI can help in shipment performance evaluation and contract negation. Inventory control One of the most crucial aspects of a manufacturing firm is inventory control and management. BI can help in tracking and reducing the inventory costs, avoid the risk of out-of-stock situations by analyzing safety stock data, create accurate forecasts using sales information, and over-stock conditions can be predicted well in advance. Conclusion A good amalgam of manufacturing and technology by utilizing data is changing the way businesses used to work. Business Intelligence is used for visualizing and analyzing data to meet the data consumption needs of the business. If you want to gain deeper insights with data analytics to meet your information needs and make better decisions with BI solutions, you can get in touch with our BI experts. Related services & solutions Scorecards and dashboards Read more Data discovery and aggregation Read more Data visualization and reporting Read more Actionable analytics Read more Intelligence Read more Business analytics with Power BI, … Read more Decision making Read more Automation with Microsoft Power … Read more Business productivity Read more Insights Read more Related Blog posts Don’t just survive, grow through the crises with Power BI The next big thing in business applications Business analytics to supercharge sales Gain more value by prioritizing your data initiatives How manufacturing companies gain value from BI Benefits of business intelligence in the construction industry Gain advantage of a phased approach for your next BI project Business Intelligence trends to watch for in 2019 How to embed a Power BI report into an application for your customers Business intelligence vs. business analytics: Where BI Matches into your Corporate strategy 4 Things About BI Reporting Your Boss Wants to Know 5 ways to turn business intelligence into business growth Why Microsoft Power BI is the leader in business analytics? Powerful Decision Making with BI Updates Advaiya Announces New Virtual Events for Businesses, IT Personnel Seeking Latest Insights About Both Dashboards and Cloud Migration Microsoft positioned as a leader in the Gartner 2020 Magic Quadrant for Analytics and Business Intelligence Platforms [Press release] Advaiya announces 1,180 executives from 553 companies have now received training at its “Dashboard in a Day” workshops Decision making News about Advaiya
Benefits of business intelligence in the construction industry
The construction industry is responsible for taking up some of the biggest and most expensive projects on earth. A huge amount of capital, resources, and work goes into these projects, and this means a significant amount of data is generated. Number crunching has always been vital for this industry, considering the scale and capital involved. Though Business Intelligence (BI) has been extensively adopted by most of the sectors, it is in its booming phase for the construction industry. The construction industry needs interactive visualization of their business data to identify new growth opportunities, optimize processes, maximize margins, offer outstanding customer services, and create space for genuine innovation. In this blog, let’s walk you through some of the benefits of adopting Business Intelligence in construction: A: Business pace When business data is available to every department in real time, one will be able to take quick data-driven decisions. Centralization of data, will make the data accessible on any device through the cloud and hence reduce the administrative work. Cloud solutions have proved to reduce the workload and significantly boost productivity. BI can be used to refine the existing business processes, automation of tasks, and for better organization and prioritization of work. B: Leveraging work packages A work breakdown structure lets you keep a note of the tasks, by adding or removing some of the individual work packages. Task breakdown can be simplified by determining the quantity and type of skills needed with predictive analytics. Once the right people are matched to the right task, there will be clarity on what needs to be done and who will be doing. C: Risk scans Construction and engineering space advocate health and safety procedures most vociferously as compared to any other industry as it affects the productivity and lowers team morale if any of the crew members are injured on site. Keep your workforce away from site disasters, with the combination of predictive and prescriptive analysis. For example, with predictive analytics, you can pinpoint disaster zones to nth degree accuracy using pedometer analytics by measuring the distance covered by the crew during the work hours. Based on the pedometer analytics, the tools and heavy-duty equipment’s can be positioned to reduce fatalities. D: Deep insights In the construction industry, data sources are heavily siloed or stored at different locations, making effective data integration a challenging affair. An abundance of data can be an asset, but data mishandling or not integrating the data sources properly will lead to data silos. Every visualization tile on the dashboard is a doorway for data exploration. Selection of a tile will lead to a report which can be filtered and sorted to know the dataset behind the report, and when you run insights, BI does the data exploration for you. E: Tailored reporting Reporting is an essential step to drive business decisions. Reports interactively display data to turn it into actionable information. A report can have multiple levels of interactivity like the ability to drill down, filter, and sort, as well as additional capabilities such as self-service editing, to further explore the data for more insights. BI gathers and represents data that is ready to be analyzed. Data includes historical information, which is difficult to be traced over time. BI reporting empowers the users with the information to become experts in their area of business. In the future days to come, BI will radically transform the business of construction. The companies that embrace data analytics and the latest technologies will be able to innovate and stay ahead of their competitors. 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