What should you know about working with analytics in Business Development?

That data is only numbers until you link it to strategy and value, plain and simple. Human-generated insights based on experience and expertise + GenAI driven data = better business development.

An open mind and no expectations are the most essential aspects. Data analysis is the key, but data will surprise you occasionally, and an open mind is the key to having correct strategy-aligned actions forward. Also, it is good to remember to revisit the analysis later after the first actions in order to understand if the situation is still the same.

In the pharmaceutical industry, analytics is crucial for business development as it enables the understanding of market dynamics, needs, and competitive landscapes through data-driven insights. Combining these approaches with different perspectives would be beneficial; therefore, as is the case in most business, evaluating them as a team is important here as well.

Data always gives better insight if interpretation is correct... Challenge is to fetch information from available or accumulated data from market, veterans, stakeholders or other sources... Data analytics can give better picture which can be helpful to take quick and result oriented decisions for sure...

Data analytics is the bridge to information and knowledge to have conclusions, relations and insights that help in decision making and efficiency improvement.

Descriptive analytic is very important to understand the current market situation and after that prescriptive analytic can be forecasted and formed as per the market trends

There are four types of analytics used in business development: Descriptive analytics: Summarizes what has happened in the past using charts, graphs, and dashboards Diagnostic analytics: Investigates why something has happened in the past using data mining techniques Predictive analytics: Forecasts what is likely to happen in the future using machine learning models Prescriptive analytics: Recommends what actions you should take to achieve your goals using optimization and simulation techniques

1 - Understand the basics. 2 - Create a culture driven by data. 3 - Apply it in your business. 4 - Use data to make decisions. 5 - Set goals.

One thing I find imperative is weighing the strategic significance of which analytical metrics you want to use. Depending on what you measure and how you measure it, you will impact the operational structure in ways you maybe did not intend. Customer satisfaction and customer retention can feel interchangeable, but working towards making customers stay and making them actually satisfied might look very different. "What you measure is what you get" also goes for your operational output. The behaviour you measure is the behaviour you get.

In the realm of Business Development, the analytical toolbox is versatile. Descriptive analytics paints a portrait of your business landscape, revealing its contours and nuances. Diagnostic analytics acts as a detective, unraveling the mysteries behind trends and occurrences, offering valuable insights into causation. Predictive analytics, akin to a crystal ball, forecasts potential scenarios, allowing you to anticipate and prepare for the future. Lastly, prescriptive analytics serves as a guiding hand, offering bespoke strategies to navigate the complexities of your unique business terrain, transforming insights into actionable decisions.

To choose the right analytics for business development, you should: 1)Define your problem and goals 2)Identify your data sources and requirements 3)Evaluate the features and capabilities of different tools 4)Compare the costs and benefits of different tools

Start by understanding what you need them for and what data you have. Look for tools that are easy to use and can grow with your business. Consider how they fit with your existing systems and how much they cost. Check reviews and support options to ensure you are getting a reliable tool from a trustworthy vendor. Before committing, try out the tools through trial or pilot programs to see if they meet your needs.

Choosing the optimal analytics tools for Business Development involves navigating a landscape of variables. Scrutinize the tools against the canvas of your data intricacies – ensure they harmonize with the depth and breadth of your information. Gauge the analytical acumen required; opt for tools that align with the complexity of your insights quest. Seek tools that seamlessly interlace with your existing systems, orchestrating a symphony rather than a cacophony. Reliability and security act as sentinels guarding your data fortress, while robust support and training ensure mastery of the analytical arsenal. In this intricate dance, finding the perfect tool is about orchestrating harmony in the analytics symphony.

Choosing the right analytics tools hinges on aligning with specific business needs and market trends. First, evaluate tools based on their capacity to integrate & analyze diverse data sources, crucial for a holistic view of the business landscape. Emphasizing tools that offer advanced capabilities like AI & ML is key, as these technologies are increasingly vital for predictive & prescriptive insights. Scalability is also critical, with a recent survey revealing that over 40% of businesses prioritize scalability in their analytics solutions to accommodate growth. Finally, user-friendliness and support services are essential, ensuring that the tool is accessible to all team members and offers robust support for maximum efficiency and impact.

Choosing the right analytics tool for BD involves aligning it with your goals, ensuring compatibility with existing data sources, and looking for essential features such as data visualization and predictive analytics. Prioritize scalability, user-friendliness, and robust security. Conduct a cost-benefit analysis, take advantage of trials, and consider the tool's support and user community. Opt for a tool that offers intuitive insights within a secure, cost-effective framework, and don't forget to check vendor reputation.

The best method is K.I.S.S: Keep It Simple Stupid The analytics are the conversation, so knowing your audience, and tailoring your insight to meet what they want to hear. Whether it’s customers, leaders or your team; meeting their perspective in the most efficient way will earn your position as “the expert” of this topic.

Communicating analytics results for business development involves translating complex data into actionable insights that can guide strategic decisions. Here are few suggestions on how to effectively communicate analytics results in a business development context: Speak Their Language: Avoid jargon and technical terms that may be unfamiliar to non-technical stakeholders. Use language that is easily understandable and relatable. Highlight Key Points: Focus on the most critical insights, and use visuals to emphasize trends, patterns, and outliers. Quantify Impact: Whenever possible, quantify the potential impact of recommended actions on revenue, cost savings, market share, or other relevant metrics.

La de comunicación de los resultados de un BI o un cuadro de mandos es fundamental para que sea de verdadero valor para la organización, El formato, la frecuencia, los destinatarios, los canales (digitales, escritos, mails, RRSS), los diferentes niveles de lenguajes y vocabulario; todo tiene que estar debidamente pensado y ejecutado de forma sistemática y automatizada.

One of the techniques I prefer for presenting analytics results in Business Development is the WHPI (Why?, How?, Prove it). The analytics results serve as a roadmap for business development, so I present them in a way that guides the audience to understand why we arrived at the discussed solution. Following this, we outline how we plan to implement the solution or collaboration. Finally, we conclude the discussion by showcasing similar projects or use cases from comparable or adjacent businesses as proof. It’s essential for the Business Development Manager to continue overseeing the solution/project implementation phase to ensure alignment between what was communicated during the analysis phase and the actual results.

In Business Development analytics, effective communication is the nexus of data and decisions. Tailor your message to your audience – be it management, team members, customers, or partners – with precision. Whether through a report or slide deck, choose a format that resonates, and employ visual aids and storytelling to illuminate key points. Decode the journey to results, providing context and interpretation. Elevate beyond data dissemination by highlighting main takeaways, unraveling implications, and offering actionable recommendations. This artistry transforms analytics into a compelling narrative, guiding your audience towards strategic and informed decisions.

When it comes to sharing analytics insights in Business Development, clarity is king. Tailoring your message to your audience is key—I've found this crucial in my experiences. Visuals and storytelling? They're like magic wands. I've seen how they breathe life into numbers, making complex data relatable and easy to grasp. And explaining the "how" behind the results? That's where context and interpretation come in, helping everyone understand the journey to those insights. Summarizing the key points and implications is a must. It's like handing out a roadmap after a great discovery—showing the way forward. And don't forget actionable recommendations; they're the fuel for action, turning insights into tangible steps for progress.

In my teachings with high performing commerical organizations, here are 10 ways to enhance your business development analytics skills: 1-Continuous Learning 2-Take Skill-specific Courses 3-Networking 4-Work on Real-world Projects 5-Obtain relevant certifications 6-Seek mentorship from experienced professionals 7-Practice solving complex business problems using analytics methodologies to sharpen problem-solving skills. 8-Enhance your communication and presentation skills to effectively convey analytical findings to non-technical stakeholders. 9-Embrace a mindset of experimentation, testing hypotheses, and learning from failures to improve analytical capabilities. 10-Cultivate a curious mindset.

Here are some resources: - 9 Skills Every Business Analytics Professional Needs - 4 Ways to Improve Your Analytical Skills: This article from Harvard Business School Online provides some practical tips on how to enhance your analytical skills. - How to Improve Your Business Analysis Skills: 6 Business Analyst Tips: This article from Pestle Analysis gives you some advice on how to improve your business analysis skills. - 8 Ways to Use Data Analytics to Improve Business Management: This article from Southern Baptist University Online shows you how organizations use data analytics to improve their business performance.

Analytical thinking matters most. Skilled can be learned from various sources. Experience and growth mindset for a product/service/solution will lead to go extra mile.

Putting aside specific tools and skills, the core is to get the basics right: - Be curious and ask questions, especially for wins. A deal closed is a valuable source of information - and ppl love talking about their successes and why it went well. - Apropos of above, qualitative insights lend context, colour and often drivers for the actual quant data. - That said, analytics is built on top of data to find the insight - which means you have to be hungry to seek, explore and analyse the data. You'll never know what you find. And what you find is usually not known to at least some other functions and therefore has insight value - Share. Be a champion of using data for decisions and enabling others to do so. Value gets created at the nodes.

I've found it comes down to reverse engineering your sales process. How many events did I have to attend to secure one meeting? How many meetings did it take to get one proposal? How many proposals did it take to close one deal? Figure out the numbers, identify how many of X you need to achieve Y, and then execute. From there, identify the lowest conversion points in the funnel, and focus on improving the bottlenecks, one at a time.

AI transforms business development into a strategic powerhouse. Picture a savvy assistant decoding data, predicting market moves, and uncovering growth possibilities. It streamlines lead generation, enhances customer connections through chatbots, and liberates time from mundane tasks. Sales forecasts and competitive insights become second nature, and personalized marketing thrives. Beyond the numbers, AI anticipates risks, ensuring we stay one step ahead. In essence, AI isn't just tech wizardry; it's our ally for smart decisions, market agility, and mastering business development dynamics.

In facility management, my industry for +15 years, Analytics play a crucial role. Specially in the modern IoT phase. They help in understanding building usage patterns, maintenance needs, and cost efficiencies. Analyze data on energy consumption, occupancy rates, maintenance history, and space utilization. Use this information to optimize space allocation, predict maintenance requirements, reduce operational costs, and enhance occupant satisfaction. Leveraging analytics allows for proactive decision-making, efficient resource allocation, and the delivery of high-quality facility services.

From my experience, it is always better to start with what question you want answered and then what does the data tell you. If we start with the data without knowing what the question is, it can lead us down many paths that might not be relevant to what you want to achieve.

In my view, there is a lot of shoehorning and emphasis on vanity metrics. One example of this is Pipeline analytics eg no of activities such as no of emails, phone calls etc. This can work well if (say) you’ve got well established playbooks/formulas in place for the target category/client personas and/or when targeting SMEs. It can often fail when you’re targeting enterprise clients with long sales cycles. Here the focus should be about tracking high quality, insightful follow-ups at regular (not daily/weekly) intervals i.e. Quality over Activity Volume. Emphasising volume over quality for this target group can often lead to pipeline churn and this is often why SME sales managers struggle to transition into Enterprise sales.