How data speeds up transaction closures

M&A deals don’t fail in the boardroom They fail in due diligence. 70% of acquisitions destroy value. AI slashes due diligence time by 30-50% (McKinsey). I leveraged 8 AI tools to turn M&A From a bottleneck into a competitive edge. The result?  45% faster deal closures and fewer post-merger surprises. Here's how AI transformed our approach: 1️⃣ Contract Analysis (Kira Systems):  ↳ Extracted key terms in hours, not weeks.  ↳ Turned contract insights into negotiation leverage. 2️⃣ Data Centralization (DiligenceVault):  ↳ Eliminated version control chaos.  ↳ Aligned stakeholders instantly, speed wins bids in tight windows. 3️⃣ Data Automation (Datasite):  ↳ Automated data room setup and tracking.  ↳ Freed my team's bandwidth for actual deal strategy. 4️⃣ Legal Risk Detection (Luminance):  ↳ AI caught anomalies human reviewers missed.  ↳ Mitigated post-deal surprises by 76%. 5️⃣ IP Portfolio Analysis (PatentSight):  ↳ Quantified IP's true worth in days.  ↳ Prevented us from "paying for air" in three recent acquisitions. 6️⃣ Financial Analysis (MindBridge):  ↳ Flagged revenue irregularities before they became problems.  ↳ Financial transparency is non-negotiable. 7️⃣ Compliance Checks (ComplyAdvantage):  ↳ Automated regulatory compliance at scale.  ↳ Shielded deals from expensive regulatory traps. 8️⃣ HR Analytics (PeopleInsight):  ↳ Spotted talent flight risks pre-acquisition.  ↳ Aligned human capital to deal goals from day one. 💡 Key Takeaway: AI isn't replacing dealmakers, it's supercharging them. How are you using AI to speed up complex processes in your field? Let’s discuss 👇 ♻️ Repost this to help your network.  🔔 Follow me, Nadir Ali, for more insights on Strategy, Leadership and productivity.

Tired of inaccurate close dates? I got you. Here’s how you fix it. Your sales reps are overly optimistic when forecasting deal close dates. No forecast is accurate and deals are being pushed and pushed. You fix it by using data in the deal to set the right close date. No more guess work and an accurate close deal on every deal! Here’s the basics of it: You calibrate your close date based on the customer’s buying situation rather than subjective estimations of a sales. 𝟭: 𝗣𝗶𝗰𝗸 𝘆𝗼𝘂𝗿 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 First, pick your framework. I use MEDDIC for more complex B2B sales and BANT for simpler ones. You add this framework to required deal information your salespeople need to fill in. As an example: 𝘐𝘥𝘦𝘯𝘵𝘪𝘧𝘺 𝘗𝘢𝘪𝘯: 𝘥𝘰𝘦𝘴 𝘺𝘰𝘶𝘳 𝘤𝘰𝘯𝘵𝘢𝘤𝘵 𝘩𝘢𝘷𝘦 𝘢 𝘲𝘶𝘢𝘯𝘵𝘪𝘧𝘪𝘦𝘥 𝘱𝘢𝘪𝘯 (𝘪.𝘦. 𝘴𝘦𝘵 𝘪𝘯 𝘧𝘪𝘯𝘢𝘯𝘤𝘪𝘢𝘭 𝘪𝘮𝘱𝘢𝘤𝘵 𝘰𝘧 𝘪𝘵)? Give your salespeople multiple choice questions. Easy to fill for them and easy to reuse in calculations. 𝟮: 𝗥𝗲𝗹𝗮𝘁𝗲 𝘁𝗵𝗲 𝗮𝗻𝘀𝘄𝗲𝗿𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗯𝘂𝘆𝗶𝗻𝗴 𝘄𝗶𝗻𝗱𝗼𝘄 Next, you determine how these answers relate to the buying window. For instance: 𝘌𝘤𝘰𝘯𝘰𝘮𝘪𝘤𝘢𝘭 𝘉𝘶𝘺𝘦𝘳 𝘯𝘰𝘵 𝘰𝘯 𝘣𝘰𝘢𝘳𝘥 𝘴𝘭𝘰𝘸𝘴 𝘥𝘰𝘸𝘯 𝘢 𝘴𝘢𝘭𝘦 𝘸𝘪𝘵𝘩 3 𝘮𝘰𝘯𝘵𝘩𝘴. Translate all answers into a buying window. I use the AIDA model for it but you can be more sophisticated with the B2B journey model from Gartner. - 𝟯 𝗺𝗼𝗻𝘁𝗵𝘀 𝗳𝗼𝗿 𝗔𝗰𝘁𝗶𝗼𝗻: The buyer knows their problem and is ready to act quickly. Economic buyers and decision-makers are already engaged. - 𝟲 𝗺𝗼𝗻𝘁𝗵𝘀 𝗳𝗼𝗿 𝗗𝗲𝘀𝗶𝗿𝗲: The buyer has expressed interest and understands the solution but still needs internal alignment. - 𝟵 𝗺𝗼𝗻𝘁𝗵𝘀 𝗳𝗼𝗿 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁: They’ve acknowledged the need but are early in their evaluation process. Your champion may not yet have all the influence they need. - 𝟭𝟴 𝗺𝗼𝗻𝘁𝗵𝘀 𝗳𝗼𝗿 𝗔𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻: They’re aware of the problem, but it’s not a priority yet. You’ll need to nurture the relationship. 𝟯: 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗶𝘁 Once you’ve mapped the buyer’s journey to these timeframes, integrate it into your CRM. In HubSpot, for example, you convert the buying windows into milliseconds and use automation to calculate a close date based on the last modified date plus the defined buying window. The hidden close date field is automatically copied into the actual close date field. Tadaaa! A close date based on the customer’s actual buying window. And that my friends, is sales tech that makes sense. Happy closing ;-) P.S. If you want to have automatic close dates, but you lost me somewhere half way, that’s ok. Happy to help. P.P.S. I know you hate the like button, but if you got this far, just hit it!

Investors are making decisions in seconds—are you keeping up? When you're managing complex transactions, timing isn't just important - it's critical. Here's what real-time data actually means in practice: 1. Transaction Intelligence • Live updates on investor activities • Recent deal history • Fresh market movements • Current investment philosophies 2. Process Feedback • Immediate investor responses • Live Q&A tracking • Real-time engagement metrics • Instant deal feedback Why this matters: Investors form opinions quickly. Having data delayed by days means missing crucial opportunities to: • Address concerns promptly • Adjust deal narratives • Refine communication strategies • Show responsiveness 3 key benefits of real-time insights: 1. Better Decision Making • Spot emerging trends • Identify potential roadblocks • React to market signals 2. Enhanced Credibility • Shows deal preparedness • Demonstrates market awareness • Proves active listening 3. Stronger Relationships • Quick response to questions • Proactive problem-solving • Aligned communication What we're seeing: The most successful deals aren't just about the numbers - they're about quick, informed responses to investor concerns. Your ability to gather, process, and act on real-time data could make the difference between closing a deal or watching it slip away. #MergersAndAcquisitions #InvestmentBanking #PrivateEquity #DataAnalytics

After an hour of digging in with a prospective Topkey customer, our team discovered a common pattern with vacation rental financial processes: The #1 bottleneck slowing down month-end close? Disconnected systems between operations and accounting. Here's what happens: - Maintenance teams manually code expenses in the PMS - Finance teams manually enter expenses into the accounting system - So bills still need to be manually added to both the accounting system and PMS. This can make month-end close drag out longer than it should since expenses in the PMS don’t talk to expenses in the Accounting system. The root cause: Lack of integration between ops and finance tools. Ultimately, our prospect’s (now a new Topkey customer) aha moment came when we set them up and synced their transaction data to QuickBooks and their work order data to their PMS. Suddenly, the finance team had real-time visibility into property-level spend at the point of sale and could close the books in days instead of weeks. Three lessons learned: 1. Siloed systems are the silent killer of efficient accounting 2. Integrating ops and finance data is a game changer – a single source of truth eliminates duplicate entry and worry about any missed data 3. The key to faster closing is empowering finance with timely operational data